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Probabilistic lifecycle analysis of earthquake-damaged buildings using building information models Gavrilovic, Stevan 2020

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PROBABILISTIC LIFECYCLE ANALYSIS OF EARTHQUAKE-DAMAGED BUILDINGS USING BUILDING INFORMATION MODELS  by Stevan Gavrilovic   B.Eng., British Columbia Institute of Technology, 2013 MASc., The University of British Columbia, 2015  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES  (Civil Engineering)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  August 2020  © Stevan Gavrilovic, 2020  ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Probabilistic Lifecycle Analysis of Earthquake-damaged Buildings Using Building Information Models submitted by Stevan Gavrilovic in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Civil Engineering.  Examining Committee: Terje Haukaas, Department of Civil Engineering Supervisor Sheryl Staub-French, Department of Civil Engineering Supervisory Committee Member Jasmin Jelovica, Departments of Mechanical and Civil Engineering Supervisory Committee Member Rachel Pottinger, Department of Computer Science University Examiner Kasun Hewage, The University of British Columbia Okanagan, School of Engineering University Examiner    iii Abstract This dissertation presents models and methods for the lifecycle analysis of buildings. Detailed models are developed that are associated with constructing, operating, repairing, and demolishing buildings. These models address an array of direct and indirect concerns, including impacts from the repair of earthquake damage. In support of cost-based decision making, a host of cost models are implemented to translate lifecycle impacts into monetary costs. The significant uncertainty in predicting earthquake hazards, material behaviour, and future costs is addressed through probabilistic modelling.    The models in this dissertation are underpinned by a new library of building components. The components contain finite elements, built-in functionality, and information required for lifecycle analysis. These information-rich building components are created from building information models, or BIMs, with algorithms that are implemented in this dissertation. Methods are presented for generating a structural model from the components, and a correlation structure is developed for random variables that are created within these components. A novelty of this work is a seismic loss estimation methodology that is based on visual damage. Models are developed that predict visual damage from the responses of high-fidelity finite element models. A new damage mesh discretizes building components into damage regions where the stresses and strains are expected to influence the damage at the surface. Resembling the approach of a repair estimator, arrays of repair actions are described for different types and extents of visual damage. The repair actions are paired with a construction database to provide enriched estimates of the repair cost and duration.  iv The new models and methods are applied to a six-storey building in order to gain new insights into the repair of earthquake damage. The building is subjected to earthquake ground motions, where it is demonstrated that the ground shaking duration, and the damage accumulated during the initial part of the shaking, influence the subsequent repairs. Next, several lifecycle analyses are performed, and wood, concrete, and steel material options are compared for the structural system. Results show that wood is the better option from a broader societal perspective.     v Lay Summary This research presents computer simulation models for the holistic analysis of buildings. A host of direct and indirect costs associated with constructing, operating, repairing, and demolishing buildings is assessed. A key goal of this work is to advance earthquake engineering, addressing sustainability as well as traditional performance criteria, such as repair cost, recovery time, and safety. The inherent uncertainties in predicting future seismic risks are addressed through probabilistic modelling.  A new library of information-rich building components is implemented in this work. Created from architectural computer models, the components provide a structural model, built-in functionality, and information required for holistic analyses. High resolution visual damage models rely on these components for detailed seismic loss estimates. Resembling the approach of a repair estimator, repair actions are selected for different types and extents of visual damage. Several studies are performed on a six-storey building to gain insights into the lifecycle cost of buildings.        vi Preface Material from Chapter 2 was published in the following conference paper: • Gavrilovic, S., Haukaas, T. (2017) “Gradient-based minimization of the uncertain cost of buildings using building information models.” Proceedings of the 12th International Conference on Structural Safety and Reliability, ICOSSAR 2017, Vienna, Austria. I am the principal author, contributing to the text, models, and results. Haukaas, T., was involved in the formulation of the major concepts, and manuscript text and structure.  Material from Chapter 3 has been submitted as a journal paper, which is currently under review:  • Gavrilovic, S., Haukaas, T. (2020) “Multi-model probabilistic analysis of the lifecycle cost of buildings.” I am the principal author, contributing to the text, models, and results. Haukaas, T., was involved in the formulation of the major concepts, and manuscript text and structure. Material from Chapter 3 was also published in the following conference papers: • Haukaas, T., Gavrilovic, S., Costa, R. (2019) “Decision criteria for optimizing the sustainability of buildings and the resilience of communities.” 11th International Forum on Engineering Decision Making, IFED, Sydney, Australia. Haukaas, T., is the principal author. I contributed material associated with the lifecycle analysis of buildings, while Costa, R., contributed material related to the recovery of communities. • Haukaas, T., Gavrilovic, S. (2017) “A computational framework for holistic life-cycle design of buildings.” Proceedings of the 9th International Structural  vii Engineering and Construction Conference, ISEC-9, Valencia, Spain. Haukaas, T., is the principal investigator. I was responsible for developing the underlying framework, models, and results.  • Haukaas, T., Gill, G., Gavrilovic, S. (2017) “Probabilistic cost models and computational framework for life-cycle design of buildings.” Proceedings of the 12th International Conference on Structural Safety & Reliability, ICOSSAR 2017, Vienna, Austria. Haukaas, T., was the principal author. Gill contributed models for energy usage, building cost models, etc., while my contribution was implementing the models and synthesizing the results.  • Haukaas, T., Gavrilovic, S. (2017) “Using building information models and comprehensive cost modeling to optimize the life-cycle design of buildings.” Proceedings of the 6th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering, COMPDYN, Rhodes, Greece. Haukaas, T., is the principal investigator. I was responsible for developing the BIM import framework, models, and results. Material from Chapter 4 has been submitted as a journal paper, which is currently under review: • Gavrilovic, S., Haukaas, T. (2020) “Seismic loss estimation using visual damage models.” I am the principal author, contributing to the text, models, and results. Haukaas, T., was involved in the formulation of the major concepts, and manuscript text and structure.    viii Material from Chapter 5 will soon be submitted to a Journal as the following paper: • Gavrilovic, S., Haukaas, T. (2020) “Environmental and human health impacts of earthquake damage.” I am the principal author, contributing to the text, models, and results. Haukaas, T., was involved in the formulation of the major concepts, and manuscript text and structure. The research presented in this dissertation was conducted by me under the supervision of Dr. Terje Haukaas, Professor at the University of British Columbia, Vancouver. I am responsible for the computer programming, and for creating the results, figures, and tables. Dr. Haukaas continuously provided feedback and advice throughout the work. I wrote the text of all chapters of the dissertation, with edits provided by Dr. Haukaas. For the material in Chapters 2 through 5, I implemented the models in the computer program Rts. I am also responsible for creating the building information model for the six-storey building studied in this dissertation. I also conducted the analyses and synthesized the results. The journal and conference papers were written in an iterative process with Dr. Haukaas.   ix Table of Contents  Abstract ................................................................................................................................... iii Lay Summary .......................................................................................................................... v Preface ..................................................................................................................................... vi Table of Contents ................................................................................................................... ix List of Tables ........................................................................................................................ xiii List of Figures ........................................................................................................................ xv Acknowledgements ............................................................................................................ xviii Dedication ............................................................................................................................. xix Chapter 1: Introduction ......................................................................................................... 1 1.1 Long-term Vision and Short-term Objectives ........................................................... 1 1.2 Motivation ................................................................................................................. 4 1.3 Scope ......................................................................................................................... 5 1.4 Background ............................................................................................................... 6 1.5 Contributions ............................................................................................................ 8 1.6 Case Study Building ............................................................................................... 10 1.7 Overview of Dissertation ........................................................................................ 12 Chapter 2: BIM Import Algorithms ................................................................................... 15 2.1 Introduction ............................................................................................................. 15 2.2 Information-rich Components from BIM ............................................................... 19 2.3 Extracting Material Information ............................................................................. 22 2.4 Extracting Geometry Information ........................................................................... 23  x 2.5 Establishing Component Connectivity ................................................................... 27 2.6 Generating Finite Elements ..................................................................................... 29 2.7 OpenSees Input File from BIM ............................................................................... 30 2.8 Correlation of Random Variables ........................................................................... 31 2.9 Conclusions ............................................................................................................. 37 Chapter 3: Multi-model Probabilistic Framework for Lifecycle Analysis ...................... 39 3.1 Introduction ............................................................................................................. 39 3.2 Overview of Costs ................................................................................................... 42 3.3 Energy Consumption .............................................................................................. 46 3.4 Water Consumption ................................................................................................ 52 3.5 Emissions ................................................................................................................ 52 3.6 Direct Costs ............................................................................................................. 54 3.7 HAZUS Earthquake Costs ...................................................................................... 57 3.8 Indirect Cost of Emissions ...................................................................................... 58 3.9 Indirect Cost of Downtime ...................................................................................... 61 3.10 Indirect Cost of Injuries and Deaths ....................................................................... 61 3.11 Resulting Lifecycle Cost Curves ............................................................................ 63 3.12 Conclusions ............................................................................................................. 78 Chapter 4: Visual Damage ................................................................................................... 80 4.1 Introduction ............................................................................................................. 80 4.2 Methodology ........................................................................................................... 82 4.3 Visual Damage ........................................................................................................ 85 4.3.1 Cracking .......................................................................................................... 91  xi 4.3.2 Cover Spalling ................................................................................................ 97 4.3.3 Cover Delamination ........................................................................................ 99 4.3.4 Core Crushing, Reinforcement Fracture, and Reinforcement Buckling ....... 100 4.4 Repair Actions ...................................................................................................... 101 4.5 Repair Cost, Duration, and Labour Requirements ................................................ 108 4.6 Study of a Shear Wall ........................................................................................... 112 4.7 Study of a Six-storey Building .............................................................................. 118 4.8 Visualizing Damage on the Computer .................................................................. 132 4.9 Conclusions ........................................................................................................... 136 Chapter 5: Environmental and Human Health Impacts of Earthquake Damage ........ 137 5.1 Introduction ........................................................................................................... 137 5.2 Methodology ......................................................................................................... 142 5.3 Study of a Shear Wall ........................................................................................... 144 5.4 Study of a Six-storey Building .............................................................................. 146 5.5 Conclusions ........................................................................................................... 156 Chapter 6: Conclusions ...................................................................................................... 158 6.1 Overview of Research and Contributions ............................................................. 158 6.2 Limitations and Future Research Directions ......................................................... 161 References ............................................................................................................................ 164 Appendices ........................................................................................................................... 180 Appendix A : OpenSees Input File ................................................................................... 180 Appendix B : Construction and Demolition Actions ........................................................ 184 Appendix C : Repair Actions ............................................................................................ 191  xii C.1 Cracking, spalling, and cover patching repair actions ...................................... 191 C.2 Cover replacement repair actions ...................................................................... 191 C.3 Component replacement repair actions ............................................................. 195   xiii List of Tables  Table 3.1 Cost matrix (numbers in the cells refer to equation numbers in the subsequent sections) .................................................................................................................................. 45 Table 3.2 RSMeans data for calculating labour-hours ( ), and crew requirements .......... 47 Table 3.3 Energy use parameters for material and worker transport and machinery use ....... 49 Table 3.4 Energy use parameters for building operations ...................................................... 51 Table 3.5 Water consumption parameters .............................................................................. 52 Table 3.6 Emissions ( ) from OpenLCA for wood, steel, and concrete ........................... 53 Table 3.7 Emission conversion factors ( ) by consumption mode and energy source .... 54 Table 3.8 RSMeans data for calculating material, labour, and equipment costs ( ) ........ 55 Table 3.9 Energy cost conversions and density factors .......................................................... 56 Table 3.10 Earthquake occurrence parameters ....................................................................... 58 Table 3.11 Cost of ReCiPe2016 impacts ( ) (Bijleveld et al., 2018a) ............................. 59 Table 3.12 ReCiPe2016 impacts from OpenLCA for wood, steel, and concrete ( ) ........ 59 Table 3.13 Human health costs of emissions ( ) (Shindell, 2015) ..................................... 60 Table 3.14 Environmental costs of emissions ( ) (Bijleveld et al., 2018b) ....................... 61 Table 3.15 Indoor casualty probabilities and fragility curve parameters (FEMA, 2013) ....... 63 Table 3.16 Shear wall, slab, and column characteristics ........................................................ 64 Table 3.17 Detailed lifecycle analysis results ......................................................................... 71 Table 4.1 Material model parameters ..................................................................................... 88 Table 4.2 Lognormal material model random variables ......................................................... 88 lkCSIγ m,nfn,sCMCkCSICkML!γ k ,mCnECnE xiv Table 4.3 Visual damage strain limits ................................................................................... 101 Table 4.4 Replacement repair action of reinforced concrete shear wall ............................... 105 Table 4.5 RSMeans data for material, labour, and equipment costs ..................................... 109 Table 4.6 RSMeans data for labour ...................................................................................... 111 Table 4.7 Crew labour and equipment requirements from RSMeans ................................... 111 Table 4.8 Repair cost and duration for pushover analysis .................................................... 123 Table 5.1 Material model parameters ................................................................................... 148 Table B.1 Concrete material CSI codes ................................................................................ 184 Table B.2 Reinforced concrete column construction action ................................................. 185 Table B.3 Reinforced concrete slab construction action ...................................................... 186 Table B.4 Reinforced concrete shear wall construction action ............................................. 187 Table B.5 Steel wide flange and glue laminated timber column construction actions ......... 188 Table B.6 Steel skin pan and cross-laminated timber (CLT) slab construction action ......... 189 Table B.7 Building demolition actions ................................................................................. 190 Table B.8 Miscellaneous project-level CSI codes ................................................................ 190 Table C.1 Epoxy-injection crack repair and spalling repair actions for all concrete components ........................................................................................................................... 191 Table C.2 Reinforced concrete column cover replacement repair action ............................. 191 Table C.3 Reinforced concrete slab top cover replacement repair action ............................ 193 Table C.4 Reinforced concrete slab bottom cover replacement repair action ...................... 193 Table C.5 Reinforced concrete shear wall cover replacement repair action ......................... 194 Table C.6 Reinforced concrete column replacement repair action ....................................... 195 Table C.7 Reinforced concrete slab replacement repair action ............................................ 197  xv List of Figures Figure 1.1 Lifecycle analysis flowchart .................................................................................... 2 Figure 1.2 Rendering of a building information model (BIM) ............................................... 12 Figure 1.3 Overview of the dissertation .................................................................................. 14 Figure 2.1 Information-rich components from IFC objects .................................................... 19 Figure 2.2 Component interface ............................................................................................. 21 Figure 2.3 Material objects in IFC .......................................................................................... 23 Figure 2.4 Geometric representation items in IFC .................................................................. 24 Figure 2.5 Extracting component geometry from IFC swept area solid ................................. 25 Figure 2.6 Extracting component geometry from IFC boundary representation solid ........... 26 Figure 2.7 Methods for establishing component connectivity ................................................ 28 Figure 2.8 Connection of slab, beam, and column ................................................................. 29 Figure 2.9 Between and within component correlation .......................................................... 34 Figure 2.10 Valid region of correlation values ....................................................................... 36 Figure 3.1 Models and classes to calculate total lifecycle cost ............................................... 44 Figure 3.2 Realistic rendering of the considered building (left) and its floor plan (right) ..... 64 Figure 3.3 Relative frequency diagrams for the total lifecycle cost ....................................... 66 Figure 3.4 Building lifetime scenario ..................................................................................... 67 Figure 3.5 Lifecycle costs by phase ........................................................................................ 68 Figure 3.6 Lifecycle cost breakdown by phase ....................................................................... 69 Figure 3.7 Breakdown of costs for manufacturing phase ....................................................... 72 Figure 3.8 Breakdown of costs for construction phase ........................................................... 73 Figure 3.9 Breakdown of costs for operations phase .............................................................. 74  xvi Figure 3.10 Breakdown of costs for demolition phase ........................................................... 75 Figure 3.11 Cost of emissions and environmental impacts for concrete material .................. 76 Figure 3.12 Cost of emissions and environmental impacts for steel material ........................ 77 Figure 3.13 Cost of emissions and environmental impacts for wood material ....................... 78 Figure 4.1 Visual damage mesh discretization ....................................................................... 84 Figure 4.2 Fibre section forces, stresses, and strains .............................................................. 86 Figure 4.3 Concrete material model stress-strain backbone ................................................... 87 Figure 4.4 Steel material model stress-strain backbone .......................................................... 87 Figure 4.5 Multi-layer shell shear wall elements .................................................................... 90 Figure 4.6 Strain at the surface of shell element ..................................................................... 90 Figure 4.7 Crack dimensions for repair quantities .................................................................. 92 Figure 4.8 Crack parameters from finite element responses ................................................... 93 Figure 4.9 Spalling repair quantities ....................................................................................... 98 Figure 4.10 Cover loss repair quantities ................................................................................. 99 Figure 4.11 Repair actions and CSI codes ............................................................................ 102 Figure 4.12 Repair action selection procedure ..................................................................... 108 Figure 4.13 Damage state fragility functions ........................................................................ 114 Figure 4.14 Visual damage at the median storey drift values of the damage states ............. 115 Figure 4.15 Repair cost of reinforced concrete shear wall ................................................... 117 Figure 4.16 Repair duration of reinforced concrete shear wall ............................................ 118 Figure 4.17 Rendering of building (top), floor plan (bottom left), and finite element model (bottom right) ........................................................................................................................ 119 Figure 4.18 Repair cost vs. building drift ratio from pushover analysis ............................... 121  xvii Figure 4.19 Repair duration vs. storey drift ratio for building pushover analysis ................ 122 Figure 4.20 Evolution of repair cost and duration during earthquake .................................. 125 Figure 4.21 Repair cost and duration at various ground motion scaling factors .................. 126 Figure 4.22 Repair cost vs. building storey .......................................................................... 128 Figure 4.23 Repair labour-time vs. building storey .............................................................. 128 Figure 4.24 Component repair cost vs. storey drift ratio ...................................................... 130 Figure 4.25 Component repair duration vs. storey drift ratio ............................................... 131 Figure 4.26 Analysis framework and class map ................................................................... 132 Figure 4.27 Finite element model (left) and visual damage (middle and right) of a reinforced concrete elevator core following an earthquake ................................................................... 134 Figure 4.28 Visual damage of the considered building following an earthquake ................ 135 Figure 5.1 Methodology ........................................................................................................ 143 Figure 5.2 CO2 from repair of reinforced concrete shear wall (notice two vertical axes with different scales) ..................................................................................................................... 145 Figure 5.3 Computer rendering of the building BIM (top) and finite element model (bottom)............................................................................................................................................... 147 Figure 5.4 Wood material model stress-strain backbone ...................................................... 148 Figure 5.5 Breakdown of earthquake costs ........................................................................... 150 Figure 5.6 Cost of emissions for earthquake damage repair ................................................. 152 Figure 5.7 Evolution of the emissions cost along the earthquake duration .......................... 153 Figure 5.8 Cost of emissions at various ground motion scaling factors ............................... 155 Figure 5.9 Cost of emissions vs. the peak inter-storey drift ratio ......................................... 156  xviii Acknowledgements  First and foremost, I want to thank my loving family. Ilina and Pavle, your love and joy has made this journey worthwhile. Sanja, you are an amazing wife and mother. Thank you for your love, for always believing in me, and for being my harbour in the storms. To my sister and brother, I am grateful for your encouragement and support in all of my endeavours. I also want to thank Sanja’s family for their help and encouragement over the years.  Professor Haukaas, I owe you an enormous debt of gratitude for your unwavering determination to make me a better scholar and researcher. Thank you for your help, advice, and your time. In our research group, I want to acknowledge the fruitful discussions with fellow students Rodrigo, Gurvinder, Seadon, Christian, Peter, and Swanand. I would also like to thank the members of my PhD supervisory committee: Dr Staub-French for the valuable advice with building information modelling, and Dr Jasmin Jelovica for the helpful discussions about finite element modelling and optimization. I owe particular thanks to the University of British Columbia for funding my research through the Four Year Doctoral Fellowship (4YF). Finally, without the love, sacrifice, and help of my parents, none of this would have been possible. Thank you for supporting me throughout my education, and for steering me down the right path in life. I aspire to provide my children with the same opportunities that you have provided me.   xix Dedication I dedicate this work to my children. Always finish what you start, give your best, and learn from your inevitable failures—knowledge is the only currency that is inalienable.   1 Chapter 1: Introduction 1.1 Long-term Vision and Short-term Objectives The aim of this dissertation is to contribute new models and insights to the ongoing advancement of performance-based earthquake engineering. Extending the performance-based initiatives of predicting the costs of earthquake damage, this work aims to provide a richer understanding of how earthquakes affect the environment and human health.   The long-term vision of this dissertation is to develop comprehensive computer simulations for the lifecycle analysis of buildings, including earthquakes. A wide range of concerns are accounted for including costs, downtime, casualties, emissions, etc. Figure 1.1 provides an outline of the lifecycle analysis framework developed here, including the various concerns mentioned above. The boxes in the figure correspond to models that are implemented in the computer program Rts, developed in this dissertation for assessing the impacts of earthquakes on buildings. The arrows in the figure show the flow of responses, from the earthquake ground motion in the top-left corner of the figure, to the total lifecycle cost on the far right. The dashed box in the bottom-right corner represents a simplified approach of calculating the repair cost of a building that is employed in Chapter 3 of this dissertation.   2  Figure 1.1 Lifecycle analysis flowchart   Predicting future earthquake impacts is only possible in a probabilistic sense, as there is significant uncertainty in the seismic hazards, material capacities, repair costs, etc. Therefore, the aim is to simulate buildings within a probabilistic lifecycle analysis framework, with models for assessing the impacts from the repair of damage due to earthquakes. Yet another long-term goal is to create a software library of building components that are intended for the holistic lifecycle analysis of buildings. These components should contain finite elements, and built-in functionality and information for lifecycle analysis.   Building information modelling, or BIM, is an important cornerstone in this dissertation. BIM is a process where architects, engineers, and contractors collaborate on a shared computer model (Eastman, Teicholz, Sacks, & Liston, 2011). This dissertation addresses a number of specific short-term objectives related to the import of a BIM and its usage in subsequent analyses. One objective is to import an Industry Foundation Classes (IFC) file from a BIM into the computer program Rts. IFC is a commonly used data format to exchange information between BIM programs. In Rts, algorithms that create information-rich ManufacturingConstructionRepairOperationsDemolitionEmissionsDowntimeDirect costVisual damageFinite element model   Human casualties $Earthquake ground motionSimplified earthquake hazard models for Chapter 3EnergyBIM 3 building components from an IFC file will be implemented. These components will contain a finite element mesh; hence, the import algorithm should include the creation of a finite element input file for structural analysis. As seen at the top of Figure 1.1, BIM is the starting point for the creation of a finite element model.  Another important objective in this dissertation is to implement and fine-tune models for an array of direct and indirect concerns, e.g., emissions, energy, costs, time, across all phases of the life of a building. The left-side of Figure 1.1 shows a suite of building lifecycle models, with arrows leading to the various concerns addressed in this dissertation. As seen in the righthand side of the figure, all concerns are translated into direct and indirect costs, to enable cost-based decision making by future stakeholders. In addition, these costs are intended to be used in building-wide analyses to identify the holistically best design.  Developing and including detailed estimates of the cost and duration of the repair of damage due to earthquakes is a key objective of this work. To accomplish this, an aim is to develop models to predict visual damage on the surfaces of building components. Using visual damage leads to improved repair estimates because it echoes the approach of a repair estimator. Based on the visual damage, a host of repair actions are determined in this dissertation for the various types of visual damage. Subsequently, these repair actions are employed to yield detailed quantities of repair material, time, labour, and equipment; thus, resulting in more complete estimates for repair.   Another major objective in this dissertation is to conduct comprehensive analyses of a real-world building. Referred to as the “case study building” in this dissertation, a six-storey building located in Vancouver, described in Section 1.6, is selected for this purpose. The analyses of the case study building will include thorough seismic loss assessments and a  4 broad range of lifecycle concerns. From these analyses, insights are gained into the repair of earthquake-damaged buildings.  1.2 Motivation In 1754 BC, the Babylonian king Hammurabi enacted the first laws addressing building safety, a precursor to the modern building codes of today. Since then, the primary focus of engineers has been the life-safety of building occupants. However, significant earthquakes over the last few decades have shown that safe, but easily damaged buildings can translate into billions of dollars in losses (Kovacs, 2010; Wood, Noy, & Parker, 2016). This inspired the birth of performance-based earthquake engineering (Cornell & Krawinkler, 2000), where engineers consider repair costs and recovery time as well as safety.  While the safety and repairability of a building are important concerns, the Bruntland report by the United Nations highlighted another troubling problem: Buildings are major polluters (Keeble, 1988). The warming of our planet is proceeding at a rate that is unprecedented over millennia. Human activity since the mid-20th century has dramatically increased carbon dioxide emissions in our atmosphere, shattering records that have remained unchallenged for over 800,000 years (NASA, 2020). Increased population, urbanization, and growth of the global middle class will only escalate the problem. Without drastic systemic changes in the next decade, humanity could face food shortages, climate refugees, and societal instability as soon as 2040 (IPCC, 2018). A key motivation of this research is to improve the sustainability of buildings. To a large extent, climate change culpability lies with the construction industry. From the time when builders fire-baked bricks in Hammurabi’s Mesopotamia, the emissions from construction have continued unabated. Today, manufacturing the concrete, steel, and wood  5 that goes into buildings still takes a toll; 11% of the worlds annual greenhouse gas emissions comes from the production of these building materials (IEA, 2019). Energy use is another key issue; the construction and operation of buildings accounts for 36% of global energy use, and almost 40% of energy-related carbon dioxide emissions (IEA, 2017). Nevertheless, as net-zero energy buildings and renewable energy usage becomes widespread, structural related impacts will increase in importance. In the context of earthquakes, which is a focus of this dissertation, the activities from the repair of seismic damage can also be a significant source of emissions (Pan et al., 2014). As a result, there is a need to integrate seismic performance assessments within a whole-building lifecycle analysis.  Buildings are complex systems, making comprehensive lifecycle analyses information intensive and challenging. This motivates the use of BIM because employing the information readily available in BIMs will reduce the time and effort to run both structural and lifecycle analyses. In addition, there is currently inconsistent technology adoption within the design and construction industry (Muller et al., 2017). A 2004 NIST report (Gallaher, Gallaher, Dettbarn, & Gilday, 2004) estimates that this costs US facilities $15.8 billion per year. Increased BIM adoption among structural engineers will mitigate interoperability challenges across the architecture, engineering, and construction disciplines, and benefit the industry as a whole.  1.3 Scope The scope of this research is limited to buildings; bridges and other civil infrastructure are not considered. The main focus in this dissertation is on the structural components of a building. However, many of the models implemented in this dissertation may be repurposed for other types of components and uses. Non-structural components, e.g., doors, partition  6 walls, windows, plumbing, are not considered, even though they may require repair after an earthquake. While non-structural building components can be a major contributor to the total earthquake losses of a building, their damage is a directly related to the performance of the structural system.   When buildings are damaged, it is assumed in this dissertation that they will be repaired to their pre-damage strength and functionality. During repair, there is no consideration for the impacts of collateral repair work, e.g., removal of finishing, utility relocation, and finishing. Another assumption is that a building remains in its original state for the duration of its life. Thus, the effects of building deterioration over time, and the impacts of building maintenance, are omitted.   The models implemented here are intended for new construction, and the retrofit of existing buildings is not studied. In this dissertation, the lifecycle of a building is separated into five phases: 1) material manufacturing; 2) construction; 3) damage and repair; 4) operations; and 5) demolition. For the damage and repair phase, the focus is on the analysis of damage due to earthquakes. Other natural and man-made hazards, e.g., wind, snow, water, blast loading, may be applicable, but not explicitly considered. 1.4 Background This research builds upon and extends the computer program Rt, developed previously in the research group (Mahsuli & Haukaas, 2013a). Rt was developed for performance-based earthquake engineering, and it was employed to calculate the cost of seismicity in Vancouver, Canada, with a large number of random variables and interacting models for hazards and structures (Mahsuli & Haukaas, 2013b, 2013c). That program is extended in this dissertation, under the name Rts, with BIM import capabilities, detailed building modelling,  7 cost models, environmental and human health damage models, etc. Rts is written in the programming language C++ (Deitel & Deitel, 2008). A basic understanding of programming terminology is helpful moving forward.   Because a central objective in this dissertation is to implement models and algorithms for computer simulations of buildings, a review of other relevant computer programs is warranted. The NHERI SimCenter (2019) provides state-of-the-art computer programs for computational simulations in natural hazards engineering. One of their products, the OpenSees computer program for earthquake engineering, is used in this dissertation for structural analysis (McKenna, Scott, & Fenves, 2010). However, the programs from the SimCenter do not consider sustainability, and they do not support the import of BIMs. Taking sustainability considerations into account, the earthquake-focused FEMA PACT tool (FEMA, 2019) provides carbon dioxide and embodied energy from the repair of seismic damage.  Alternative computer programs for addressing the sustainability of buildings include the Athena Impact Estimator (Bowick, O’Connor, & Meil, 2014). Athena is geared toward building lifecycle analysis, and it is not intended to assess the impacts from the repair of seismic damage. Moreover, Athena does not support direct BIM import; it requires a user to supply a bill of materials. The “plugin” named Tally (KieranTimberlake, 2020), for the computer program Revit developed by Autodesk, supports lifecycle analysis with BIM. Although it does so within Revit only, and it cannot be used to assess the impacts from damage repair. Other well-known lifecycle assessment programs include SimaPro (PRé Sustainability Consultants, 2019) and GaBi (Thinkstep, 2019), but they consider a far broader array of products than is the focus of this work.  8 1.5 Contributions Converting BIMs to structural models is one of the most needed uses of BIM (Ramaji & Memari, 2018). Moreover, the growing popularity of the computer program OpenSees as an earthquake engineering research tool has created a need for the generation of an OpenSees structural model from an IFC. The ability to convert IFC files to OpenSees input files allows for richer analyses to be conducted with detailed models, which is exemplified later in this dissertation. The commercial software ETABS (CSI, 2013) and StruBIM (Pereiro-Barceló & Solak, 2018) support structural model generation from IFC. However, they are proprietary platforms and do not provide input files for OpenSees. Therefore, the ability to export an OpenSees input file from a BIM addresses a gap in the existing research. A contribution in Chapter 2 is the creation of a set of algorithms to convert an IFC file into an OpenSees input file.   An overall goal of performance-based earthquake engineering is to probabilistically predict and minimize the cost of repairing buildings. Recent advancements in performance-based earthquake engineering have begun to address lifecycle concerns by including environmental impacts from the repair of damage. The research group of Professor Frangopol (Biondini & Frangopol, 2016; Frangopol, Lin, & Estes, 1997) has developed models for reliability and building lifecycle analysis, although they do not employ the level of modelling detail that is presented here. There is currently a research gap in performance-based earthquake engineering for the detailed modelling of real-world buildings and structures. A contribution in Chapter 3 is the results from a detailed analysis of the case study building. These results give insight into the role of earthquakes in the lifecycle cost of a real-world building. Recent work by Padgett and Li (2016) provides a thorough analysis with a  9 detailed building model. However, their analysis excludes the operations phase and focuses on embodied energy and carbon dioxide. A comprehensive study by Menna et al. (2013) addresses all lifecycle phases of a building. But it does not employ detailed models and it excludes many impacts that are considered here, e.g., worker transport and heavy machinery usage. Another contribution in Chapter 3 is the implementation and customization of models that consider a broad range of lifecycle concerns, from energy and emissions, to earthquake damage. These models address a gap in research by expanding the breadth of lifecycle concerns considered in an analysis while accounting for all building lifecycle phases.   Following maxims in performance-based earthquake engineering, there is currently a need to assess the cost of lifecycle concerns, e.g., environmental damage, from the repair of structures and buildings. Often, the results of environmental assessments are reported in unfamiliar units, e.g., “environmental performance scores” (Gencturk, Hossain, & Lahourpour, 2016; Hossain & Gencturk, 2016). However, without widespread adoption, such grading schemes can be ambiguous to an unacquainted decision maker, making it difficult to interpret and compare alternatives. Using a common metric of cost in dollars, the studies by Arroyo et al. (2015) and Wei et al. (2016) employ carbon taxes to translate carbon dioxide emissions into a cost. Nevertheless, there is still a gap in research for models to translate a broader range of emissions and concerns into costs. In this dissertation, models are developed that translate many concerns from the repair of damage, e.g., energy, emissions, and time, into costs.  Previous studies in performance-based earthquake engineering often employ fragility functions to predict damage (Moehle & Deierlein, 2004). An influential fragility-based loss framework is developed by Yang et al. (2009) to calculate damage and repair costs due to  10 earthquakes. That framework is now set forth in the FEMA P-58 guidelines (FEMA, 2018). However, fragility-based methods do not provide detailed repair quantities, nor the specific location of the damage. This may impede efforts to compare alternative repair actions, potentially resulting in inaccurate cost estimates. The main contribution in Chapter 4 is the development and implementation of algorithms to predict visual damage of structures subjected to earthquake ground motions. Based on that visual damage, lists of repair actions are described, yielding detailed estimates of the cost, duration, labour, and equipment requirements of repairs. In this dissertation, detailed estimates of visual damage and repair actions provide improved and enriched predictions of the impact of earthquakes.  There is a growing body of literature that considers the environmental impacts from the repair of earthquake-damaged buildings. Again the study by Menna et al. (2013) is relevant, but they exclude environmental costs. The studies by Chhabra et al. (2018) and Gencturk et al. (2016) consider ten impacts from the TRACI methodology. However, their analyses do not use detailed finite element models, nor do they translate environmental impacts into cost. Moreover, in addition to addressing damage to the environment, the analyses presented in this dissertation include the impacts of emissions on human health. In this dissertation, a more complete assessment of environmental and human impacts is presented, allowing for additional insights into the impacts of repairs after earthquakes. A key contribution in Chapter 5 is the new results of environmental and human health impacts associated with the repair of damage from earthquakes.  1.6 Case Study Building The six-storey mixed-use residential-commercial building employed in the case studies in all chapters is presented here. The building is located in Vancouver Canada, but it has not yet  11 been built. A computer rendering of the BIM of the building, developed in the program ArchiCAD for this work, is shown below in Figure 1.2. The BIM is exported from ArchiCAD into an IFC-formatted file, containing over 182,000 IFC objects. Those objects describe the geometry of the components of the building, the location of the building, etc. The building has 1,041 m2 of commercial area on the ground floor and five equally sized residential floors above. Reading information from the IFC file, using algorithms described in Chapter 2 of this dissertation, reveals that the building contains 6 slabs, 156 columns, 616 non-load-bearing walls, 165 exterior walls, 60 shear walls, 356 windows, 171 m2 of window area, 22.5 m total height, and 40 residential units. In addition, the building has a reinforced concrete shear wall in the centre that is intended to carry lateral load on the building and serve as an elevator shaft. This particular type of building was selected because it is common in the building stock in Vancouver. Because of the prevalence of this building type, any insights gained will be of value. When the BIM was created in ArchiCAD, attention was given to the structural components, as well as the building shell, i.e., exterior walls, windows, and doors. As stated in the scope section, only the structural components were considered in the manufacturing, construction, repair, and demolition modelling. Conversely, in the energy loss calculations for the building operation phase, presented in Chapter 3, the building shell was considered. Other building components such as mechanical, electrical, and plumbing are not explicitly modelled in the BIM.   12  Figure 1.2 Rendering of a building information model (BIM)  1.7 Overview of Dissertation Each chapter of this dissertation takes one step towards the long-term goal of holistic computer simulations of buildings. Chapter 2 presents the BIM import procedures, creating information-rich components containing finite elements. The BIM import capabilities are demonstrated with the generation of an input file for the structural analysis program OpenSees. Chapter 2 also presents other aspects of BIM import, such as the creation of a valid correlation matrix for the random variables that are created within the components.    Chapter 3 presents detailed models to assess the concerns, e.g., cost, time, energy, and emissions associated with constructing, operating, repairing, and demolishing buildings. Cost  13 models are implemented in Chapter 3 to translate the myriad of impacts into a final monetary cost. A comprehensive lifecycle analysis is also performed for the case study building.  Chapter 4 presents a methodology for the detailed calculation of seismic losses based on new visual damage models. A collection of repair actions is deduced from the visual damage, providing enriched estimates of the cost, duration, labour, and equipment needs of the repairs. An analysis of the case study building subjected to an earthquake examines how the repair cost is affected by ground motion characteristics.  Chapter 5 presents new results for the case study building, including more complete estimates of environmental and human health costs for a building subjected to ground motion.  A roadmap illustrating how all the chapters of this dissertation tie together is given in Figure 1.3. The top of the figure shows that Chapter 2 provides the BIM import algorithms that create the detailed structural model employed in all subsequent chapters. Chapter 3 considers all phases of the lifecycle of a building, from material manufacturing to demolition. However, Chapter 3 does not employ the new repair cost models developed later in the dissertation. That is because the new repair cost models are based on ground motion records, and such records are unavailable when probabilistically considering all possible earthquake sources near Vancouver. For that reason, the HAZUS approach is employed, considering all seismic sources around Vancouver, in conjunction with fragility curves at the building level (FEMA-NIBS, 2003; Mahsuli & Haukaas, 2013b). Conversely, the central point in Chapter 4 is to develop detailed models for visual damage, leading to a list of repair actions, and ultimately enriched estimates for the cost and time of repairs. In contrast with Chapter 3, a ground motion record is now applied as the seismic hazard. The focus in Chapter 4 is on that  14 earthquake; all other phases of the lifecycle of the building are not considered. Chapter 5 follows up on Chapter 4 in the sense that only one ground motion is considered. However, Chapter 5 broadens the scope to include the environmental and human health impacts of earthquake repairs, employing the new visual damage and repair action predictions from Chapter 4.   Figure 1.3 Overview of the dissertation  Chapter 3 Chapter 4 Chapter 5Lifecycle phasesHazard descriptionEarthquake damageConcernsFrom manufacturingto demolitionEarthquake onlyAll earthquakesourcesSingle groundmotionSingle groundmotionFragilitycurvesVisual damageAll concerns exceptenvironmental impactsOnly directcost of repairsDirect cost + environmental impactsof repairsVisual damageStructural modelEarthquakeonlyChapter 2BIM Import Algorithms 15 Chapter 2: BIM Import Algorithms 2.1 Introduction The primary objective addressed in this chapter is the creation of a set of algorithms to convert an IFC file into an OpenSees input file. More specifically, the objectives completed in this chapter are: 1) Develop a library of concrete, steel, and wood components, with built-in information and functionality for lifecycle analysis; 2) Create algorithms to import BIM models as information-rich components, and algorithms to generate a finite element mesh in the components; and 3) Develop a valid correlation matrix for within-component and between-component correlation of the random variables created during BIM import.  Advancements in BIM provide the possibility of powerful computer visualizations, increased productivity, and efficient collaboration. However, despite the potential benefits of BIM, the difficulties plaguing its adoption are a lack of standardization and interoperability challenges amongst industry practitioners (Muller et al., 2017). A highly fragmented industry landscape comes with a cost: A 2004 NIST report (Gallaher et al., 2004) estimates a $15.8 billion loss to US facilities per year. For structural engineers, the benefits of adopting BIM in their workflows are twofold: First, generating structural models from BIM will reduce design costs as an inordinate amount of time is spent creating structural models from scratch. Second, structural engineers are faced with constantly broadening analysis scopes, requiring detailed information that is readily available in BIMs. The long-term vision of this work is to create a BIM-based platform for the holistic lifecycle analysis of buildings. This will improve the structural design process by allowing structural engineers to use BIM information in a lifecycle analysis, without being experts in the details.  16 Transforming building information models, or BIMs, to structural models is one of the most needed uses of BIM (Ramaji & Memari, 2018). In most of the research on this topic, the IFC format is employed to exchange information between BIM programs (ISO, 2013). Barazzetti et al. (2015) describe a method of converting a BIM created from laser point cloud measurements into a finite element model. The research initiatives by Chen et al. (2005) and Zhang et al. (2014) involve a web-based platform that performs IFC to structural model conversion. Others have developed software interfaces to import IFC data into commercial structural analysis software such as SAP2000 (Wan, Chen, & Tiong, 2004), and PKPM (Liu, Lu, Li, & Zhang, 2010). While others map the IFC data to a structural model using a XML-based intermediary (Qin, Deng, & Liu, 2011). The studies by Wang et al. (2015), and Ramaji and Memari (2018) use IFC information to directly generate structural models. Lastly, commercial structural analysis computer programs exist that have built-in support for IFC import, e.g., ETABS (CSI, 2013) and StruBIM (Pereiro-Barceló & Solak, 2018). The prior studies have made important strides in converting IFC files to useable structural models. However, these studies do not have the capability to produce input files for the computer program OpenSees, a widely used program in earthquake engineering research.  In the present study, an IFC file is input into Rts. Next, the information in the IFC file is converted into C++ classes, the programming language utilized in Rts. The material, geometry, and connectivity information is extracted from these C++ classes to create information-rich components within Rts. Next, a finite element mesh is generated within the components. The finite element mesh is subsequently employed to create the OpenSees input file. Hence, the final output from Rts is an OpenSees input file of the finite element model.   17 Generating a useable finite element model from a BIM has its challenges. The first difficulty is establishing the type of component to be created, e.g., column or slab, and its construction material. Depending on the structural analysis type, linear elastic, nonlinear, etc., appropriate material models are specified for the finite elements. Methods are developed for extracting the solid geometry from a BIM (cross-sections, dimensions, etc.), in order to create a component. The next challenge is generating the finite element mesh from BIM geometry. Algorithms are developed for determining the connectivity between components, i.e., which components are connected, and also how they are connected. For a useable finite element model, the elements of connected components must coincide at a node to enable the transfer of force and stiffness. In the frequent case where two connecting elements do not share a node, methods are implemented to transfer the force and stiffness from one node to another.   Every component created during BIM import contains variables and many of these are created as random variables within Rts, e.g., material model parameters. Some of these random variables may be statistically dependent and thus require correlation. Correlation is important because it can influence the dispersion and accuracy of a model response, such as the collapse behaviour of a structure (Haselton & Deierlein, 2008), or the dynamic response of a building (Gokkaya, 2015). In this study, the dependence between random variables is quantified with a Pearson’s correlation coefficient. To use these coefficients in an analysis, they are organized into a correlation matrix, where one variable is correlated with another, which can be correlated with another, and so on.  Typically, a correlation matrix is constructed from measured data. However, observational data from tests involving entire structures is scarcely available. One study,  18 presented by Idota et al. (2009), tested material coupons from the components, after which the entire structure was tested. From these tests the within- and between-component correlations of the material parameters were established. Another study used regression models to estimate the component level correlations from a database of test observations (Gokkaya, Baker, & Deierlein, 2017). Aside from these studies, data is limited. Common practice involves subjectively specifying correlation values based on expert judgement (Gokkaya et al., 2017). However, subjectively specifying correlation coefficients often results in a correlation matrix that is not valid and unusable (Higham, 2002). A valid correlation matrix is positive-definite, which means that it has positive eigenvalues and a determinant greater than zero. One remedy is to “repair” the offending correlation matrix, i.e. arbitrarily adjust the correlation values until the matrix is valid (Higham, Strabic, & Sego, 2016). Another approach is to randomly generate correlation matrices that are guaranteed to be positive-definite (Lewandowski, Kurowicka, & Joe, 2009). Nevertheless, randomly generating or repairing correlation matrices necessitates the implementation of complex algorithms.  In this research a valid correlation structure is developed. A valid correlation structure ensures that the generated correlation matrix will always be valid and useable, i.e., it is positive-definite, and no further modification to the correlation matrix is required. The correlation structure accounts for both correlations within a single component, i.e., intra-component correlation, and correlations between different components, i.e., inter-component correlation.   19 2.2 Information-rich Components from BIM The concept of building “components” is central in this work. There are two ways of understanding these components. One is to think of a light wood-frame wall, consisting of timber studs, insulation, plywood, gypsum board, etc. One such wall is one component. Another way to understand components is as information-rich objects with built-in information and functionality. This extends object-oriented implementations of the finite element method, such as OpenSees (McKenna et al., 2010), in which elements contain cross-sections, which in turn contain materials. The components developed in this research are one level higher than the elements; components contain elements, among other information. The bottom-row of Figure 2.1 shows several components created in this research from BIM.  Figure 2.1 Information-rich components from IFC objects  The starting point in the creation of components is an IFC file, which contains the information from a BIM as a collection of IFC entities. In an IFC “STEP” file, shown in top-DATA;#4= IFCPERSON($,'Undefined',$,$,$,$,$,$);#6= IFCORGANIZATION($,'Undefined',$,$,$);#10= IFCPERSONANDORGANIZATION(#4,#6,$);#13= IFCORGANIZATION('GS','Graphisoft','Graphisoft',$,$);#14= IFCAPPLICATION(#13,'18.0.0','ArchiCAD-64','IFC2x3 add-on version: 3006 INT FULL');#15= IFCOWNERHISTORY(#10,#14,$,.ADDED.,$,$,$,1485840728);#16= IFCSIUNIT(*,.LENGTHUNIT.,.MILLI.,.METRE.);#17= IFCSIUNIT(*,.AREAUNIT.,$,.SQUARE_METRE.);#18= IFCSIUNIT(*,.VOLUMEUNIT.,$,.CUBIC_METRE.);#19= IFCSIUNIT(*,.PLANEANGLEUNIT.,$,.RADIAN.);#20= IFCMEASUREWITHUNIT(IFCPLANEANGLEMEASURE(0.0174532925199),#19);#21= IFCDIMENSIONALEXPONENTS(0,0,0,0,0,0,0);#22= IFCCONVERSIONBASEDUNIT(#21,.PLANEANGLEUNIT.,'DEGREE',#20);#23= IFCSIUNIT(*,.SOLIDANGLEUNIT.,$,.STERADIAN.);#24= IFCMONETARYUNIT(.USD.);#25= IFCSIUNIT(*,.TIMEUNIT.,$,.SECOND.);#26= IFCMEASUREWITHUNIT(IFCTIMEMEASURE(31556926.),#25);#27= IFCDIMENSIONALEXPONENTS(0,0,0,0,0,0,0);#28= IFCCONVERSIONBASEDUNIT(#27,.TIMEUNIT.,'Year',#26);#29= IFCSIUNIT(*,.MASSUNIT.,$,.GRAM.);#30= IFCSIUNIT(*,.THERMODYNAMICTEMPERATUREUNIT.,$,.DEGREE_CELSIUS.);#31= IFCSIUNIT(*,.LUMINOUSINTENSITYUNIT.,$,.LUMEN.);#32= IFCUNITASSIGNMENT((#16,#17,#18,#22,#23,#24,#28,#29,#30,#31));#34= IFCDIRECTION((1.,0.,0.));#36= IFCDIRECTION((0.,0.,1.));IFC STEP-Fileclass IfcBuilding : public IfcSpatialStructureElement{public:IfcBuilding();~IfcBuilding();IfcLengthMeasure elevationOfRefHeight;IfcLengthMeasure elevationOfTerrain;IfcPostalAddress buildingAddress;}; C++ ClassesIfcSlab IfcBeam IfcColumn IfcWall 20 left of Figure 2.1, each numbered line is a standalone IFC entity. These entities represent IFC objects and their attributes, such as construction material, geometry, or location within a building. The attributes of an object are given by the IFC schema (IFC4.2 at the time of writing). To make the information in an IFC STEP file available in Rts, the library IFC++ (Gerold, 2013) is used to create equivalent C++ classes for the IFC entities. The top-right box in Figure 2.1 shows an “IfcBuilding” C++ class created from its IFC counterpart. The IFC attributes of an object are instantiated as “data members” in its C++ class. That is, the C++ class of an IFC object contains as many data members as the IFC object has attributes. As shown in the IfcBuilding class in the figure, the C++ data members of the class, e.g., elevationOfRefHeight, elevationOfTerrain, buildingAddress, correspond one-to-one to the IFC attributes of IfcBuilding. Fortunately, both IFC and C++ use the concept of inheritance, where information and attributes from a “base” class are retained in a “derived” class. To understand this through an analogy consider a child, i.e., derived class, that is a descendant of and inherits traits from its parents, i.e., base class. As an example, the IfcBuilding class in Figure 2.1 is derived from the IfcSpatialStructureElement base class. The concept of inheritance is extended to the components in this work. Figure 2.2 shows a class map of selected components in Rts. The base class, shown at the top of the figure, contains information and functionality common to all components. Below the boldface class names are the “member functions,” which show the information that components provide. Through inheritance, subclasses such as walls and columns gain access to that information. In the figure, the triangle symbol signifies “is a,” which means that the “Wall Component” class is a derived class of “Component.” In turn, the wall and column classes are parent classes for the components that are created as objects,  21 such as the “Steel Column Component.” Multiple inheritance allows a component to inherit information and functionality from several parent classes. For example, information common to all reinforced concrete components is implemented once in the “RC Component” base class.   Figure 2.2 Component interface Together, inheritance and the one-to-one association of IFC attributes to C++ data members offers important advantages in the creation of components. The process of creating components requires detailed information from many IFC attributes, e.g., material and geometry. Locating attributes in an IFC file entails repeated searches over the entire collection of building entities. This is because one attribute can reference another, which might reference another, and so on, requiring extensive searching before sought-after information is found. This can be time consuming and tedious since even modest BIMs have many IFC entities. In C++, every IFC attribute exists as a data member, and these data members are readily accessible through inheritance. Hence, one only needs to find the lowest derived class of an IFC object, e.g., IfcColumn, IfcSlab, to gain access to the attributes stored ComponentgetFiniteElementMesh()getSurfaceArea() getVolume()getMaterialsList()getBuildingStorey()getConnectedComponents()getVisualDamage()getTopologicalMesh()getConstructionActions()getDemolitionActions()getCO2Emissions()getClimateChange()getOzoneDepletion()getCHEmissions()getMaxDisplacement()getMaxStress()getDisplacement(x,y,z)getStress(x,y,z)getStrain(x,y,z)getForceResponse(x,y,z)RC Wall ComponentSteel Column Component RC Column Component CLT Wall ComponentLaminated Timber ComponentgetLumberGrade()getNumberOfLaminations()getCompressiveStrengthParallelToGrain()getAllowableBendingStress()getAllowableTensileStress()getAllowableShearStress()Steel ComponentgetYieldStrength()getYoungsModulus() getDensity()getStrainHardeningRatio()getDuctilityFactor()getFractureStrainLimit()Column ComponentgetHeight()getCrossSection()getMaxDrift()getAxialLoad()RC ComponentgetCoverThickness()getCompressiveStrength()getTensileStrength()getUltimateCrushingStress()getReinforcementRatio()getReinforcementSpacing()Wall ComponentgetLength()getThickness()getHeight()getElevationArea()getPerimeter()getFootPrint() 22 in the base classes. From the attribute classes, additional information that they contain is accessed in a similar way, and so forth, making data collection for the creation of components efficient.  2.3 Extracting Material Information In IFC, construction material information is provided through an association relationship; through the object called IfcRelAssociatesMaterial shown at the top of Figure 2.3. It is seen in the figure that one way of accessing the material is through the object itself. Another way is through the IfcRelDefinesByType relationship, which allows a material to be assigned from another object, i.e., several objects share a single material.  The diamond symbol, seen under IfcRelAssociatesMaterial at the top of the figure, denotes a “contains a” relationship. As an example, the IfcRelAssociatesMaterial object in Figure 2.3 contains a material select object (IfcMaterialSelect). The material select object has either a single material definition (IfcMaterialDefinition), a list of materials (IfcMaterialList), or a set of materials (IfcMaterialUsageDefinition). In the material set, the arrangement and relative positions of the individual material layers are provided. In the material list, no consideration is given to the material positioning. Whether it is one material or many that are given, the sought-after material information is found in the IfcMaterial object. This material object provides the name, description, and category, e.g., concrete or steel grade, of a material.   23  Figure 2.3 Material objects in IFC 2.4 Extracting Geometry Information Arguably, the greatest challenge in BIM import is extracting the component geometry. Knowledge of the geometry is essential for most aspects of a building lifecycle analysis. For example, it is used in the calculations of operational energy usage, construction material quantities, and for generating the finite element mesh. In BIM, the geometry of a solid is always given in three-dimensions. IFC employs several types of geometry representations to describe the shape of a solid. It is up to the program that is exporting the BIM to decide on the type of representation it will use. Some representations are straightforward to import, while others pose unique challenges.  To find the geometry representations in the IFC hierarchy of information, the search begins at the IfcProduct class; the base class for all objects that have a geometry. Figure 2.4 shows a class map illustrating the path to the data member where the geometry of an object is IfcRelAssociatesMaterialIfcMaterialSelectIfcMaterialListIfcMaterialDefinitionIfcMaterialLayerSetUsageIfcMaterialUsageDefinitionIfcMaterialProfileSetUsageIfcMaterial IfcMaterialIfcMaterialLayerSetIfcMaterialIfcObjectDefinitionIfcRelAssociatesIfcMaterialProfileSetIfcMaterialProfileIfcMaterialIfcRelDefinesByTypeMaterial is given by the object Material is assigned from another objectIfcMaterialLayer 24 stored. As shown at the top of the figure, the IfcProduct object contains a member called IfcProductRepresentation. In turn, this member contains a list of representation items, aptly called IfcRepresentationItems. Each item in this list represents some trait of the IFC product, e.g., geometry, location, orientation. One of these items, the geometric representation item (IfcGeometricRepresentationItem), contains the sought-after geometry information. The geometric representation item is the base class for all geometry representations, several of which are shown along the bottom of Figure 2.4. These geometric representations, IfcSolidModel, IfcBooleanResult, etc., are further derived into their specialized constituents. For example, the bottom row of boxes in Figure 2.4 highlights the five geometry representations that are derived from IFC solid model class.  Figure 2.4 Geometric representation items in IFC An important concern for structural analysis applications is the cross-section geometry of a component. In IFC parlance, cross-sections are called “profiles.” In the straightforward case, cross-section information is directly found in the IFC parameterized profile definition object (IfcParameterizedProfileDef). The parameterized profile definitions provide profile information for many common structural shapes, e.g., rectangle, circle, wide-IfcSweptAreaSolid IfcManifoldSolidBrep IfcCsgSolidIfcSweptDiskSolid IfcSectionedSolidIfeRepresentationItemsIfcProductRepresentationIfcGeometricRepresentationItemIfcBooleanResult IfcHalfSpaceSolid IfcBoundingBox …IfcSolidModelIfcProduct 25 flange, channel, and angle. As the name suggests, the parameterized profile definition contains the necessary parameters to completely define a profile. For example, the rectangular profile definition class (IfcRectangleProfileDef), a derived class of IfcParameterizedProfileDef, contains the two parameters for the width and depth of a rectangular cross-section.  The highlighted boxes in Figure 2.4 emphasise two geometry representations for which algorithms are implemented in this research. In the swept area solid representation (IfcSweptAreaSolid), parameterized profiles define so called “swept areas” of a cross-section that are extruded along a vector to create a solid. Figure 2.5 illustrates this approach with a wide-flange beam, where the cross-section area, highlighted in red, is extruded along a line described by a vector. As shown by a red circle in Figure 2.5, the centroid of the cross-section is determined at both ends. These centroids are used by the meshing algorithms in Rts to distribute finite elements along the member centroidal axis. The cross-section geometry, i.e., flange thickness, web height, flange width, is given by the parameters in the profile definition (IfcIShapeProfileDef).   Figure 2.5 Extracting component geometry from IFC swept area solid Parameterized profiles exist for many of the common structural members and cross-sections encountered in practice. As a case in point, the well-known structural analysis Point1Point2“Swept Area”Extrusion Vector 26 program ETABS uses parameterized profiles to import IFC models. However, even if a cross-section is straightforward, there is no guarantee that a BIM program will export the cross-section as a parameterized profile. Furthermore, there are situations where the profile changes along the length of a member, i.e., non-prismatic members. As a result, the swept area approach is no longer applicable when cross-sections vary along the member length.  In these special cases, the geometry of a member is often given by a boundary representation, or IfcManifoldSolidBrep. Illustrated in Figure 2.6 for a square column, a boundary representation is a collection of surfaces that enclose a solid. The surfaces consist of faces, which are two-dimensional planes that are bounded by a “loop” of edges. The red triangle in Figure 2.6 highlights such a face that is bounded by three edges. An edge loop is a collection of connected lines, wherein each line goes between two vertices. This collection of faces, loops, edges, and vertices make up a “closed shell.”   Figure 2.6 Extracting component geometry from IFC boundary representation solid Vertex FaceEdgeMerge faces Calculate centroidsPoint1Point2Import geometry Create componentIfcFacetedBrepIfcClosedShellIfcFaceIfcFaceOuterBoundIfcPolyLoopIfcCartesianPoint 27  The bottom row of wireframe diagrams in Figure 2.6 shows the process for creating a column out of a boundary representation. On the far left, the raw wireframe of the boundary representation is shown with arrows pointing to a face, edge, and vertex. First, the coplanar faces are merged to form larger surfaces that are planar. Next, the centroids of these surfaces are calculated, shown as the red points in Figure 2.6. At this point, heuristic methods are employed to determine the next steps in component creation. It is known a priori what type of component is being imported, e.g., IfcColumn, IfcSlab, or IfcWall. Since it is known in Figure 2.6 that a column is being created, the surfaces with the two centroids that are farthest apart are selected as the ends of the column. The cross-section geometry can henceforth be calculated from these end faces. Similar rule of thumb methods are used to create other components. For example, if the component being imported was a slab instead of a column, then the two faces with the largest surface areas would be designated as the top and bottom of the slab. It is worth noting that it is possible to describe a solid with more than one geometry representation. Also, recall that it is up to the exporting BIM program to decide on the appropriate geometry representation of a solid. Until it becomes clear which geometry representations are standard for structural analysis applications, it will be necessary to implement algorithms for the import of all, if not the most common representations. In the meantime, some BIM programs like ArchiCAD have the option to force the geometry export into a specified representation. This is useful if some representations are unsupported.  2.5 Establishing Component Connectivity When creating components from BIMs, another important issue for structural modellers is to establish the connectivity between components. The components contain finite elements,  28 whose responses are controlled by the element boundary conditions. This means that when adjoining elements are connected, the properties of one element, e.g., stiffness, loading, influence the response of the other, and vice versa. Establishing proper connectivity between components ensures that the finite element model will represent the behaviour of the building as intended.   This research employs two techniques for establishing component connectivity: 1) Mesh to mesh intersections, and; 2) Information provided by IFC. The first approach uses computational geometry algorithms to check if the meshes of two solids intersect. An intersection occurs when one object goes through another, e.g., when a column penetrates a slab, or when the surface of one object touches another, e.g., a beam abutting against a column. The structure shown on the left of Figure 2.7 gives three examples, highlighted in red, of surface-to-surface intersections between a column, beams, and a slab. In the second approach, the IfcRelConnects object provides a connectivity relationship between components. The connectivity relationship either explicitly states that one object is connected to another, or else it provides a connection geometry that facilitates the physical connection of two objects.   Figure 2.7 Methods for establishing component connectivity IfcRelConnectsMesh Intersection 29 2.6 Generating Finite Elements Often, a finite element model is a lower fidelity idealization of the structure that it represents. The behaviour of a three-dimensional solid is approximated with lower-dimensional elements for the sake of computational efficiency, ease of formulation, and straightforward implementation. Common examples of this are illustrated in Figure 2.8, for slab, beam, and column components. In the figure, two-dimensional shell elements are spread out along the midplane of the slab, while one-dimensional frame elements are laid out along the centroidal axes of a column and beam. Clearly, the components are physically connected to one another. However, it is not clear how to connect the adjoining finite elements.  Figure 2.8 Connection of slab, beam, and column Finite elements connect at nodes, at which the force and stiffness from one element transfer to the other, ensuring the continuity of finite element responses. Ideally, connecting elements will share a node. However, many times in BIM import, this is not the case. Consider the column in Figure 2.8, upon which rests a slab. The small dark grey circles in the 1-D frame element3-D solids2-D quadrilateral shell elementsAt which node do these elements connect? 30 figure represent the finite element nodes. The node at the end of column is separated from the nodes of the slab, which lie along its midplane. It is also seen in the figure that the beam element is offset from both the slab and the column, yet it should connect to both. When two connecting elements do not share nodes, a kinematic link is used to establish connectivity between them. A kinematic link could be a rigid link, as in no deformation occurs within the link, or a flexible link, where deformations can occur within the link (Cook, 2007). Other considerations include whether it is a one-to-one connection, involving only two nodes. Or perhaps a one-to-many connection, where the connection is spread over a field of nodes. In this research, rigid links are employed to connect finite element nodes. The right-hand side of Figure 2.7 shows a rigid link, highlighted in yellow, that connects the blue column node to the yellow slab node. The rigid link connectivity is implemented as follows. First, connectivity is established between two components using the methods outlined above. Next, an algorithm searches the nodes in the connecting components, and connects the closest nodes. For column to slab, beam to beam, or beam to column connections, one-to-one connections are made between nodes. For wall to slab, slab to slab, or wall to wall connections, the line of nodes along the abutting edge is connected. Likewise for columns that abut walls and beams that support slabs. Where possible, the discretization between connecting components is synchronised so that nodes will coincide, or else to keep the lengths of the rigid links to a minimum.  2.7 OpenSees Input File from BIM In this dissertation, the computer program OpenSees is employed for the structural analysis methods, and finite element objects such as elements, cross-sections, and materials (McKenna et al., 2010). In Rts, every object from OpenSees is implemented in a “wrapper  31 class.” The wrapper class contains functionality that manages the OpenSees object, i.e., creates and destroys it when required. The wrapper classes manage the parameters that an OpenSees object may contain. That is, setting and updating the parameters in OpenSees when they change in Rts, e.g., during a sampling analysis.  To demonstrate the BIM import and finite element model creation capabilities, an OpenSees input file is created for the case study building. In order to create an input file, the wrapper class of each OpenSees object has a function to output the object as an OpenSees command. These commands are parsed by an “interpreter” to create the object in OpenSees. OpenSees employs the Tcl interpreter, while another version of OpenSees, OpenSeesPy (Zhu, McKenna, & Scott, 2018), uses the Python interpreter. Input file generation for both the Tcl and Python formats are supported in Rts.  An abbreviated version of the OpenSees input file of the case study building is presented in Appendix A. The input file is given in Tcl format because OpenSeesPy does not yet support all objects that are available in OpenSees. In an input file for OpenSeesPy, most commands contain a parenthesis, while the Tcl format does not use parentheses. In total 23,660 objects are generated in the file; 7,286 nodes, 744 rigid links, 4,440 materials, 3,744 fibres, 534 sections, and 6,912 elements. Due to the large number of objects, the input file provides select objects for brevity.   2.8 Correlation of Random Variables When a component is created during BIM import, many random variables are created in the background. For example, the BIM from the case study building has over 3,250 random variables that are created upon import. Some of these random variables are created within the components, like the concrete strength of a beam. Examples of material model random  32 variables created within a component are given later in Tables 4.2 and in 5.1. Others, like the cost of materials, or the labour rate of a construction crew, apply only at the building-level, and are given later in Chapters 3 and 4. The building-level treatment of correlation is important, but outside the scope of this study. For structural engineers, it is the random variables created within the components that are of interest. Unless otherwise stated, the random variables created within Rts are Lognormal random variables.  Before moving on, it is worth examining the Pearson’s correlation coefficient that was mentioned earlier. A correlation coefficient describes the linear dependence between two random variables as a continuous numerical value that ranges from -1.0 to 1.0. Variables that have correlation values close to -1.0 or 1.0 are strongly correlated, while a value of 0.0 implies that they are linearly independent. A negative correlation means that as one variable increases, the other will decrease, or vice versa. Inversely, a positive correlation implies that both variables will increase or decrease at the same time. When random variables have a multivariate normal distribution, Pearson’s correlation coefficients completely describe their dependence, otherwise they can be used as a helpful approximation. When n random variables are correlated, their correlation coefficients are collected in a nxn correlation matrix. A correlation matrix has 1’s on the diagonal (parameters are always perfectly correlated with themselves) and between variable correlation coefficients elsewhere. In this research, the component-level correlations are separated into inter-component, and intra-component correlations. Inter-component, or between-component correlations, address the relationship between the random variables of two different components. While intra-component, or within component correlations, considers random variables within an  33 individual component. To explain this most clearly, consider the correlation matrix, R, of two components, each with two random variables:          i and j=1,…,4 (1) where =intra-component correlation coefficient between random variables i and  j, and  =inter-component correlation coefficient between random variables i and  j. To make the distinction between inter- and intra-correlation clearer, the correlation matrix is partitioned into blocks. The diagonal blocks correspond to the intra-component correlation coefficients while the off-diagonal blocks contain the inter-component correlation coefficients. Only the right half of the correlation matrix is shown because it symmetrical along the diagonal.  Even with a simple case, such as in Eq. (1), it is easy to get an invalid correlation matrix when the values of  and  are subjectively asssigned. To demonstrate this, random values from -1.0 to 1.0 were assigned to the off-diagonal terms of the 4x4 matrix in Eq. (1), while keeping the matrix symmetrical. After 10,000 samples, less than 20% of the samples resulted in a valid matrix. For a 5x5 matrix, the probability of a valid matrix drops to less than 3% after 10,000 samples. As the number of random variables increases, i.e., the dimension of the matrix increases, this problem is greatly excaberated.  The correlation structure implemented in this dissertation always results in a valid matrix. Instead of specifying individual correlations between random variables, the proposed correlation structure uses uniform correlations for entire blocks of random variables. This is explained in Figure 2.9, which shows a correlation matrix of three concrete components. The R =1 ρ1,2 !ρ1,3 !ρ1,41 !ρ2,3 !ρ2,41 ρ3,41⎡⎣⎢⎢⎢⎢⎢⎢⎤⎦⎥⎥⎥⎥⎥⎥ρi, j!ρi, jρi, j !ρi, j 34 random variables in the figure represent material parameters, like the concrete compressive strength,  fc’, or modulus of elasticity, Ec. The diagonal blocks of the correlation matrix in Figure 2.9 contain uniform intra-component correlations . Similarly, a uniform value of  is used in the off-diagonal blocks to address the inter-compont correlations.  Figure 2.9 Between and within component correlation The next question is what values of  and  result in a valid correlation matrix? To answer this, the the number of components and random variables is varied. First, the number of components is fixed at two, while allowing for an arbitrary number of random variables within each component:   (2) ρ !ρR =1 ρ ρ ρ !ρ !ρ !ρ !ρ !ρ !ρ !ρ !ρ1 ρ ρ !ρ !ρ !ρ !ρ !ρ !ρ !ρ !ρ1 ρ !ρ !ρ !ρ !ρ !ρ !ρ !ρ !ρ1 !ρ !ρ !ρ !ρ !ρ !ρ !ρ !ρ1 ρ ρ ρ !ρ !ρ !ρ !ρ1 ρ ρ !ρ !ρ !ρ !ρ1 ρ !ρ !ρ !ρ !ρ1 !ρ !ρ !ρ !ρ1 ρ ρ ρ1 ρ ρ1 ρ1⎡⎣⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎤⎦⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥fc' ft Ec εcfc'ftEcεcSymmetricρ !ρR =1 ρ ρ !ρ !ρ !ρ1 ρ ! "ρ !ρ !ρ !1 "ρ !ρ !ρ! "1 ρ ρ1 ρ !1"⎡⎣⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎤⎦⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥ 35 Next, the number of random variables is fixed at two, while the number of components is varied:   (3) By varying the number of random variables in Eq. (2), and the number of components in Eq. (3), the upper and lower bounds of the valid correlation region are determined. The bounds of  are calculated by setting the determinant of R to zero in Eq. (2) and (3), and then solving for . Recall that for a correlation matrix to be valid, its determinant has to be greater than zero. This process was repeated for increasing numbers of components and random variables until a pattern emerged. The upperbound value of  is   (4) and the lower bound is   (5) where n=number of random variables and m=number of components. The valid correlation region for values of  and  is shown as shaded areas in Figure 2.10 (a) and (b). As the number of random variables and components increases, the valid correlation region shrinks.  R =1 ρ !ρ !ρ !ρ !ρ …1 !ρ !ρ !ρ !ρ1 ρ !ρ !ρ …1 !ρ !ρ1 ρ …1!⎡⎣⎢⎢⎢⎢⎢⎢⎢⎢⎢⎢⎤⎦⎥⎥⎥⎥⎥⎥⎥⎥⎥⎥!ρ!ρ!ρ!ρub =n−1n⋅ρ + 1n!ρlb = −n−1( ) ⋅ρ +1n ⋅ m−1( )ρ !ρ 36  Figure 2.10 Valid region of correlation values -1-0.75-0.5-0.2500.250.50.751-1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1r !ρ∞ components∞ random variables2 components2 random variablesm componentsn random variables(a)(b)00.250.50.7510 0.25 0.5 0.75 1r2 components2 random variablesm componentsn random variables∞ components∞ random variables !ρ 37 Graph (a) in Figure 2.10 shows how the valid region diminishes from two components and random variables (lighter shading), to any number of components and random variables (darker shading). Figure 2.10 (b) illustrates the valid region for an arbitrary number of components and random variables. Any values that fall within the shaded region of Figure 2.10 (b) will result in a valid correlation matrix regardless of the number of components and random variables.  When specifying correlation values there are several considerations worth noting. For intra-component correlations, the study by Gokkaya (2015) indicates that there is only mild correlation between material model parameters. For inter-component correlation, however, they describe that the opposite is true; there is strong correlation between the material parameters of different components. As a starting point for specifying correlation values, Gokkaya (2015) noted rather small values for intra-component correlation, as high as only 0.3, and a range of 0.3-0.9 for inter-component correlation. Note that these values fall within the valid correlation region of Figure 2.10 (b). Nevertheless, the inter-component correlation value depends on the spatial distribution of components within a building, consistency in materials and workmanship, and construction procedures. Strongly correlated components are those that are of the same type and spatially near each other. For example, if the two columns in Figure 2.9 are constructed at the same time, from the same batch of concrete, then a greater inter-component correlation value is appropriate.  2.9 Conclusions This research introduces a proof-of-concept for generating structural models from BIMs. With the methods implemented in this research, it is possible for structural engineers to  38 generate finite element models from a BIM with the help of algorithms. This can increase efficiency and save the time it takes to develop structural models from scratch.  Information-rich components are created, which contain finite elements, and are the main vehicle for storing BIM information for a lifecycle analysis. The process of creating components from a BIM is described, and algorithms for the extraction of the construction material, solid geometry, and between-component connectivity are developed. Future work should focus on the creation of additional components, both structural and non-structural. Also, the development of algorithms for the import of other, less-frequently used geometry representations will increase the support for generating structural models from BIM. To demonstrate the algorithms implemented in this research a BIM of the case study building is imported, and an input file is generated for the structural analysis program OpenSees.  For random variables generated during BIM import, a correlation structure is created that always results in a valid correlation matrix. This correlation structure considers random variables at the component level, accounting for within-component and between-component correlations. A direction of future research is to address the correlation of random variables that are created at the building level, e.g., the cost of material, and the cost of energy. Another potential direction of future work is implementing autocorrelation for when a random variable is sampled over time, e.g., the month-to-month cost of electricity.  39 Chapter 3: Multi-model Probabilistic Framework for Lifecycle Analysis 3.1 Introduction Two primary contributions are presented in this chapter: First, the implementation and customization of models for addressing a comprehensive set of building lifecycle concerns, from emissions to earthquake damage. Second, the detailed analysis of a real-world building, creating new insights for a six-storey building in Vancouver. The specific objectives completed in this chapter are: 1) Develop detailed and information-rich building models that consist of components with both finite elements and information required for lifecycle analysis; 2) Develop a host of models for translating lifecycle impacts into direct and indirect costs, including the cost of environmental damage, and the cost of damage to human health; and 3) Conduct a comprehensive analysis for a real-world building in order to gain new insights from the comparison of earthquake costs to other lifecycle costs. Constructing and operating buildings consumes 36% of the world’s energy and produces 40% of energy-related carbon emissions (IEA, 2017). These emissions have considerable negative impacts and it is imperative for the engineering community to improve the sustainability of construction. However, competing objectives exist; the functionality, safety, and durability of buildings is vital for the economy and modern life. The vision behind this work is to develop a tool to quantify the multitude of direct and indirect costs incurred in the lifecycle of a building, in order to identify the holistically best design.  A series of damaging earthquakes during the 1980s and 90s demonstrated that the building code objectives relating to life-safety were largely successful. However, these successes were overshadowed by billions of dollars in economic loss. In response, the structural engineering community developed procedures for cost-based design decisions  40 (Cornell & Krawinkler, 2000; FEMA, 2012; Kircher, Nassar, Kustu, & Holmes, 1997; Wen & Ellingwood, 2005; Whitman et al., 1997; Yang et al., 2009). Such cost-based procedures are referred to as performance-based earthquake engineering. In the related field of reliability-based design optimization, the use of cost as a decision basis for identifying optimal structural designs is also common (Benjamin & Cornell, 1970; Enevoldsen & Sørensen, 1994; Royset, Der Kiureghian, & Polak, 2001).  After the release of the Bruntland report by the United Nations (Keeble, 1988) the emphasis on environmental lifecycle assessment of structures has steadily increased. Lifecyle assessment includes quantifying the environmental impacts of a building throughout its service life (Simonen, 2014). Driven by the substantial environmental impacts of buildings, lifecycle assessment is emerging as a key tool for design, construction planning, and maintenance of infrastructure (Deodatis, Ellingwood, & Frangopol, 2014). Previously, substantial efforts have focused on non-structural aspects, such as reducing the energy consumption during operation of buildings (Cole & Kernan, 1996). However, with the impending shift to renewable energy and net-zero energy buildings, structural related impacts are increasing in importance.  Guggemos and Horvath (2005) and Johnson (2006) compare the environmental impacts of steel and concrete as structural building materials, but without consideration for earthquakes. Addressing earthquakes, the paper by Vishnu and Padgett (2019) describes a probabilistic lifecycle framework, considering interactions between lifecycle phases of a bridge. Narrowing the focus to structural retrofits, investigations by Tapia and Padgett (2012) and Wei et al. (2016, 2015) discuss the environmental impacts of retrofits alongside their  41 benefits. Sánchez-Silva (2016) incorporates the lifecycle concerns of deterioration and maintenance for buildings and other structures.  The research group of Professor Frangopol (Biondini & Frangopol, 2016; Frangopol et al., 1997) developed models for reliability and building lifecycle analysis, but without the level of detail in the modelling that is presented in this dissertation. The study by Arroyo (2015) considers emissions from material manufacturing and earthquake damage repair. However, they use simple models and they exclude impacts from the construction, operations, and demolition phases. Others employ more detailed modelling, but do not consider key lifecycle phases in the analysis, such as the operations (Hossain & Gencturk, 2016), construction (Chhabra et al., 2018), or demolition (Hasik, Ororbia, Warn, & Bilec, 2019) phases. The study by Menna et al. (2013) addresses all lifecycle phases of a building, although without detailed models. That study is comprehensive, but exclude many impacts that are considered here, e.g., worker transport and heavy machinery usage. As a result, there is a need for a detailed framework that considers a comprehensive set of concerns, throughout all lifecycle stages of a building. In the context of BIM-based lifecycle analysis tools with earthquake considerations, only the one study by Alirezaei et al. (2016) integrates BIM. They employ the program Excel as an intermediary to exchange information between a BIM and a structural analysis tool, unlike the integrated approach developed in this dissertation.  In environmental lifecycle analysis of buildings, there is a need to support decision-making from a cost perspective. Often, the results of environmental assessments are reported in unfamiliar units, making it difficult to interpret and compare alternatives. Some authors use a so-called “environmental performance score” to aide in the comparison of alternatives  42 (Gencturk et al., 2016; Hossain & Gencturk, 2016). However, without widespread adoption, such grading schemes can be ambiguous to an unacquainted decision maker. Using a more common monetary cost metric, the studies by Arroyo et al. (2015) and Wei et al. (2016) employ carbon taxes to translate carbon dioxide emissions into a cost. Nevertheless, there is still a need for models to translate a broad range of lifecycle concerns into costs.   Several students in the research group of Professor Haukaas have included environmental impacts in their consideration of structures. Employing Rt, Castrejón (2010) outlined the environmental impacts that should be included in simplified and detailed building models. Gill quantified some of those costs (Gill, 2017; Haukaas, Gill, & Gavrilovic, 2017) and Chui (2018) conducted parametric studies of a relatively simple building model. The present work extends that research with improvements in the modelling of buildings and costs (Gavrilovic & Haukaas, 2017; Haukaas & Gavrilovic, 2017).  3.2 Overview of Costs The comprehensive inclusion of costs, ranging from construction and worker transportation to earthquake damage and demolition, poses a formidable implementation challenge. Figure 3.1 provides an overview of the models and classes created in this research, and their arrangement within the model framework. The arrows show the flow of responses between models. Starting in the upper left corner of Figure 3.1, the hazard models produce a ground motion intensity that is input to a structural analysis model. The structural analysis response feeds into a damage model, which outputs into the repair impact model. The repair impact model is part of a suite of building impact models, each corresponding to a lifecycle phase; shown in the dashed box in the lower left corner of Figure 3.1. As shown, the building impact models provide direct costs, $, water usage, W, and time required to complete the phases, t,  43 together with vectors of energy usage, Q, and emissions, E. The energy vector Q stores the Joules of energy used for each energy source, e.g., diesel, electricity, and natural gas. Similarly, the emissions vector E stores the quantities of the emissions that are produced, such as kg/CO2 and kg/NOx. As shown by a diamond symbol, the building impact models contain the “RBIM” class, which in turn contains the components. The RBIM class contains building-level information, such as number of storeys, location, and occupancy, that is imported from a BIM. The models at the bottom of Figure 3.1 estimate the cost of emissions, downtime, and human injuries and casualties. For instance, energy usage results in direct costs and also emissions, which in turn is translated into cost. All costs are summed up in the scenario model, which evaluates the upstream models at specific points in time, such as the occurrence of an earthquake. Within the scenario model, costs that occur in the future, i.e., after a building is constructed, are discounted to present value. This is accepted practice for direct costs, but a matter of contention for some indirect costs, such as costs of damage to the environment and human health (Finnveden, 1997). This study uses a discount rate of 3% for all costs. Costs related to the environment and human health are pre-discounted in the literature; the cost values corresponding to a 3% discount rate are used in this study for consistency (Bijleveld et al., 2018a, 2018b; Shindell, 2015). 44  Figure 3.1 Models and classes to calculate total lifecycle cost RCostOfEmissionsModelRManufacturingImpactModelRConstructionImpactModelRRepairImpactModelROperationImpactModelRDemolitionImpactModelREmissionsFromEnergyModelRCostOfEnergyModelRDowntimeCostModelRCostOfWaterModelREnergyFromWaterModel$, t, Q, E$, t, Q, E,W$$EQ$$$$, t, Q, E$$, t, Q, ERAtkinsonBoore2003IntensityModelRBooreAtkinson2008IntensityModelRPoissonPointProcessOccurrenceModelRLognormalOccurrenceModelRBoundedExponentialMagnitudeModelRPolygonalAreaSourceModelRMultiPointLineSourceModelRQuadrilateralAreaSourceModeltotoLLLM iiRBuildingDamageModelRStructuralAnalysisModelRComponentRBIMRFiniteElementMeshRHumanImpactModeldh$ 45 Table 3.1 provides an overview of the cost models implemented in the classes in Figure 3.1. The numbers inside the cells of Table 3.1 refer to equation numbers in the subsequent sections, which are ordered in the same manner as the rows of the table. The upper part of Table 3.1 lists models for energy, water, and emissions, whose outputs are inputs to the direct and indirect cost models at the bottom of the table. Assessing the impacts of emissions is an important aspect of this study.  Table 3.1 Cost matrix (numbers in the cells refer to equation numbers in the subsequent sections)  Manufacturing Construction Operations Damage and repair Demolition Energy Consumption Material transport to site 6     Material transport to landfill     6 Worker transport to site  7, 8   7, 8 Heavy machinery use  7, 9   7, 9 Building operations   10   Water treatment and delivery   14   Water Consumption Household usage   15   Emissions Material production 16     Energy usage 17 17 17  17 Direct Costs Materials 18     Labour  18   18 Construction equipment  18   18 Water    19   Energy 20 20 20  20 Landfill disposal and recycling     21 HAZUS earthquake repairs    22  Indirect Costs Emissions  23, 24 24 24  24 Downtime    25  Earthquake casualties    30   46 Figure 3.1 shows that several models provide emissions information, E, to the RCostOfEmissionsModel. In this study the cost of emissions has two contributions: 1) The cost of environmental impacts, such as deforestation and climate change; and 2) The cost of damage to human health. Emissions include carbon dioxide, methane, sulphur dioxide, etc. For the material manufacturing stage, i.e., before the construction starts, the cost of environmental impacts is calculated according to Bijleveld et al. (2018a). However, it is assumed that the cost of damage to human health is not included in those cost numbers. For that reason, emissions are calculated for the manufacturing phase, and also for the remaining life of the building. The cost of damage to human health is calculated from those emissions (Shindell, 2015). Also, apart from material manufacturing, these emissions are used to calculate the environmental costs of other activities, e.g., operational energy usage, and worker and material transport (Bijleveld et al., 2018b).  3.3 Energy Consumption In this study, the energy usage is calculated for material transport, worker transport, construction machinery use, building heating and cooling, electricity in building operations, and for water treatment and delivery. The energy used for material transport, QMT, is (Gill, 2017)   (6) where M=number of materials (concrete, steel, wood), dm=distance between the building and manufacturing plant or landfill for material m in km, qm=mass of material m in kg, =energy intensity for transport of material m in J/kg/km, that depends on the transportation mode, i.e., heavy-, medium-, and light-duty trucks. It is assumed that all modes use diesel QMT = dm ⋅qm ⋅ imMTm=1M∑imMT 47 and that steel is transported with heavy-duty trucks, wood with light-duty trucks, and concrete with medium-duty trucks.   The energy consumed for worker transport to site and for heavy machinery usage depends on the number of labour-hours expended during construction, demolition, etc. The total labour-hours, tCSI, required to complete K tasks is calculated in this dissertation by multiplying the labour-hours per task with the number tasks:   (7) where CSI stands for MasterFormat codes from the Construction Specifications Institute (CSI, 2018), which are unique numbers used to identify products and tasks within the construction industry, K=total number of labour tasks, each corresponding to a CSI code, =labour-hours required for a crew to complete one unit of task k, and =number of units of task k. The labour-hours and crew type are provided by RSMeans, as shown in Table 3.2. Crews can be reused for multiple tasks, but the labour-hours are specific to each CSI task. To address the uncertainty in the calculation of the total labour-hours for a project, the labour-hours needed to complete a task are imported into Rts as Lognormal random variables. The mean values of the random variables are the labour-hours given by RSMeans and a 30% coefficient of variation is assumed. Table 3.2 RSMeans data for calculating labour-hours ( ), and crew requirements CSI Code Description Unit Crew Labour-hours 024116130050 Building demolition, large urban projects, concrete, includes 20-mile haul, excludes foundation demolition, dump fees C.F. B8 0.004 031113255000 C.I.P. concrete forms, column, square, plywood, 8" x 8", 1 use, includes erecting, bracing, stripping and cleaning SFCA C1 0.194 032111600200 Reinforcing steel, in place, columns, #3 to #7, A615, grade 60, incl labor for accessories, excl material for accessories Ton 4 Rodm 21.333 tCSI = lkCSI ⋅NkCSIk=1K∑lkCSI NkCSIlkCSI 48 033113700400 Structural concrete, placing, column, square or round, pumped, 12" thick, includes leveling (strike off) & consolidation, excludes material C.Y. C20 1.067 033513300250 Concrete finishing, specified Random Access Floors ACI Classes 1, 2, 3 & 4, for Composite Overall Floor Flatness & Levelness to FF35/FL25, bull float, machine float & steel trowel (walk-behind), excl placing, striking off & consolidating S.F. C10C 0.014 033529600050 Concrete finishing, walls, burlap rub with grout, includes breaking ties and patching voids S.F. 1 Cefi 0.018 033913500100 Curing, burlap, 10 oz., 4 uses assumed C.S.F. 2 Clab 0.291 The energy used for worker transport, QWT, is (Gill, 2017)   (8) where dWT=average distance of worker travel, including both to and from the site, in km, NWT=number of workers, NWS=number of work-shifts, K=number of worker transportation modes (diesel bus, Skytrain, automobile), fk=fraction of workers transported via the mode k, with , and =worker transport energy intensity for mode k in J/passenger/km. The number of work-shifts, NWS, is calculated by dividing the labour-hours, tCSI, from Eq. (7), by the number of hours worked in a shift, typically 8.  The energy used by heavy machinery, QHM, in construction and demolition is (Gill, 2017)   (9) where =ratio of heavy machinery use hours to labour-hours, as determined by the building construction type, e.g., concrete high-rise and steel low-rise, tCSI=number of labour-hours for the entire construction or demolition phase, from Eq. (7), and iHM=energy intensity demand for heavy machinery use in J/hr. Parameter values for Eq. (6), Eq. (8), and Eq. (9) are given in Table 3.3. QWT = dWT ⋅NWT ⋅NWS ⋅ fk ⋅ ikWTk=1K∑fk = 1∑ ikWTQHM =ηHM ⋅ tCSI ⋅ iHMηHM 49 Table 3.3 Energy use parameters for material and worker transport and machinery use Energy Intensity for Transporting Materials ( ) Material Transportation Mode Unit Value Source Heavy-duty trucks J/kg/km 2200 (Natural Resources Canada, 2019) Medium-duty trucks J/kg/km 6110 Light-duty trucks J/kg/km 7040 Energy Intensity for Transporting Workers ( ) Worker Transportation Mode k Unit Value Source Diesel bus J/passenger/km 920,000 (Poudenx & Merida, 2007) Skytrain J/passenger/km 390,000 Automobile J/passenger/km 2,730,000 Fraction of Workers Transported via Transportation Mode k (fk) Worker Transportation Mode k Value Source Diesel bus 0.2 (Gill, 2017) Skytrain 0.3 Automobile 0.5 Energy Intensity for Heavy Machinery use (iHM) Unit Value Source MJ/worker-hr 268 (Gill, 2017) Ratio of Heavy Machinery use to Labour-hours ( ) Building Type  Value Source High-rise wood 0.1 (Gill, 2017) steel 0.3 concrete 0.3 Low-rise wood 0.05 steel 0.1 concrete 0.1  The energy used for heating and cooling, QHC, in building operations is calculated in this dissertation as    (10) where hHC=heating and cooling efficiency ratio, QT=rate of energy loss due to transmission, QV=rate of energy loss due to ventilation, QI=rate of energy loss due to infiltration, and imMTikWTηHMQHC = 1ηHC⋅ QT +QV +QI( ) ⋅ tH 50 tH=time that the building is operational in hours. The rate of energy loss due to transmission, QT, in J/hr, is typically calculated with (ASHRAE, 2009)   (11) where 3600=the number of seconds in an hour, R=thermal resistance of a component in m2×°C/Watts, AEXT=exterior area of the component exposed to the environment in m2, and D=difference between the interior and exterior temperature of a building in °C. The rate of energy loss due to ventilation, QV, and infiltration, QI, in J/hr, is given by the “sensible heat equation” (ASHRAE, 2009)   (12) where cp=specific heat capacity of air in J/kg/°C, r=density of air in kg/m3, V=volume of the building in m3, D=difference between the interior and exterior temperature of a building in °C, and ACHVI=number of air changes per hour from ventilation and infiltration combined.  The electrical energy consumed in building operations, QEO, in Joules, is (Frank & Sen, 2011)    (13) where 3.6×106=kWh to Joules conversion factor, ACOM=commercial floor area in ft2, lCOM=average rate of commercial electricity usage in kW/ft2, 8760=number of hours in a year, NRES=number of residential households in the building, lRES=average rate of residential electricity usage in kWh/household/year, and tH=time in hours that the building is QT = 3600R AEXT ⋅ ΔQV +QI = cp ⋅ρ ⋅V ⋅ Δ ⋅ACH VIQEO = 3.6 ⋅106 ⋅ ACOM ⋅λCOM + 18760 NRES ⋅λRES⎛⎝⎜⎞⎠⎟ ⋅ tH 51 operational. The energy use parameters for Eq. (11), Eq. (12), and Eq. (13) are shown in Table 3.4. Table 3.4 Energy use parameters for building operations Parameter Unit Value Source Exterior temperature °C JAN 4.8 (The Weather Network, 2019) FEB 5.9 MAR 7.6 APR 10.0 MAY 13.2 JUN 15.9 JUL 18.1 AUG 18.3 SEP 15.4 OCT 11.1 NOV 7.1 DEC 4.8 Interior temperature °C 23 - ACHVI air change/hr LN~(6.0,0.3) (Engineering ToolBox, 2005a) cp (0°C) J/kg/°C 1006 (Engineering ToolBox, 2005b) r (0°C) kg /m3 1.276 hHC - LN~(0.85,0.2) (US Department of Energy, 2019) lCOM kW/ft2 0.0017 (Frank & Sen, 2011) lRES kWh/year/household 11135 (World Energy Council, 2016) The electrical energy consumed for water treatment and delivery, QWD, in Joules, is calculated in this dissertation by multiplying the quantity of water delivered with the electricity required for water treatment and delivery:   (14) where 3.6×106 is again equal to the kWh to Joules conversion factor, qWD=volume of water delivered in m3, and PWD=electricity required to treat and deliver a cubic meter of water; taken as 0.123 kWh/m3 (Metro Vancouver, 2014). QWD = 3.6 ⋅106 ⋅qWD ⋅PWD 52 3.4 Water Consumption The water used in building operations, qWD, in m3, is (Dziegielewski, 2000)    (15) where ACOM was defined above as the commercial floor area in m2, aCOM=average rate of commercial water usage in m3/m2/day, NRES was defined above as the number of residential households, NPH=average number of people per household, aRES=average rate of residential water usage in m3/person/day, and tD=time in days that the building is operational. Parameter values for Eq. (15) are given in Table 3.5. Table 3.5 Water consumption parameters Parameter Unit Value Source Commercial water consumption (aCOM) m3/m2/day 0.0029 (Dziegielewski, 2000) Number of people per household (NPH) people/household 2.5 (Statistics Canada, 2016) Residential water consumption (aRES) m3/person/day 0.438 (Metro Vancouver, 2018) Direct cost of water (CWD) $/2.831685m3 2.849 October 1 - May 31 3.571 June 1 – September 30 (Metro Vancouver, 2014) 3.5 Emissions The calculation of emissions from material manufacturing requires “tools” and “databases.” Lifecycle assessment tools receive as inputs energy, raw materials, etc., from lifecycle inventory databases, and output the total emissions from the material manufacturing process. The implementations carried out in this research employ the OpenLCA tool (Ciroth, 2007) to qWD = (ACOM ⋅α COM + N RES ⋅N PH ⋅α RES ) ⋅ tD 53 calculate the emissions. These calculations are based on information provided by the ecoinvent database (Wernet et al., 2016). The emissions, E, from material production, in kg, are calculated in this dissertation by multiplying the emissions produced per unit of material manufactured with the quantity of material:         n=1, 2, 3, …, N (16) where N=number of emission types (CO2, N2O, CH4, etc.), =emission n produced in the manufacture of material m, in kg, and qm=the quantity of material in m3 or kg. Values for are provided by OpenLCA for different materials and shown in Table 3.6.  Table 3.6 Emissions ( ) from OpenLCA for wood, steel, and concrete Emission (n) Unit Material (m) Wood [/m3] Steel [/kg] Concrete [/m3] Carbon dioxide (CO2) kg 195.117419 1.11564410 291.036695 Methane (CH4) kg 0.3968076 0.0021241 0.31369120 Nitrous oxide (N2O) kg 0.95313927 6.2486E-05 0.0022870 Hydrofluorocarbon (HFC-134a) kg 2.38E-07 1.7177E-09 1.2857E-07 Black carbon (BC) kg 0.17341382 0.00265465 0.09377643 Sulphur dioxide (SO2) kg 0.26247101 0.0138968 0.38227800 Carbon monoxide (CO) kg 0.54238684 0.00410289 0.34018281 Organic carbon (OC) kg 9.7834E-05 7.1562E-09 2.199E-07 Nitrogen oxides (NOx) kg 0.95313927 0.00411067 0.59027571 Ammonia (NH3) kg 0.00912766 0.00033543 0.01129424 Similarly, the emissions, E, generated from energy usage are calculated in this dissertation by multiplying the quantity of energy used with a conversion factor:       n=1, 2, 3, …, N (17) where S=number of energy sources, e.g., diesel, electricity, and natural gas, =energy to En = γ m,n ⋅qmm=1M∑γ m,nγ m,nγ m,nEn = fn,sCM ⋅qss=1S∑fn,sCM 54 emission conversion factor for emission n and energy source s, in kg/L for fuel or kg/GJ for electricity, that depends on the energy consumption mode, e.g., light-duty trucks, construction equipment, and building operations, and qs=quantity of energy source s in L for fuel or GJ for electricity. The values for  are given Table 3.7 for several energy sources, emission types, and consumption modes (British Columbia Ministry of Environment, 2014).  Table 3.7 Emission conversion factors ( ) by consumption mode and energy source  Consumption Mode  Energy Source s Unit Emission n CO2 CH4 N2O Light-duty vehicles, trucks, SUVs, and minivans Gasoline kg/L 2.175 0.00024 0.00053 Diesel kg/L 2.556 0.000060 0.00022 Propane kg/L 1.507 0.00064 0.000028 Natural Gas kg/L 2.723 0.013 0.000086 Medium-duty trucksa Gasoline kg/L 2.175 0.000154 0.00037 Diesel kg/L 2.556 0.000085 0.000186 Natural Gas kg/L 2.723 0.013 0.000086 Heavy-duty trucks Gasoline kg/L 2.175 0.000068 0.00020 Diesel kg/L 2.556 0.00011 0.000151 Natural Gas kg/L 2.723 0.013 0.000086 Equipment and off-road vehicles Gasoline kg/L 2.175 0.0027 0.00005 Diesel kg/L 2.556 0.00015 0.0011 Natural Gas kg/L 2.723 0.013 0.000086 Building Operations Natural Gas kg/GJ 49.46 0.0010 0.0009 Electricity kg/GJ 2.8 CO2e avalues are the averages of the light-duty and heavy-duty truck consumption modes 3.6 Direct Costs The cost of materials, labour, and equipment, cCSI, is calculated in this dissertation by multiplying the unit cost of an item with the number of items: fn,sCMfn,sCM 55   (18) where it was defined earlier that CSI stands for MasterFormat CSI codes, K=number of CSI items, =cost of one unit of item k from the RSMeans database, and =number of units of item k. Table 3.8 gives examples of several items along with their CSI codes, a detailed description, and associated costs. A full list of the CSI codes associated with the construction of the case study building is given in Appendix B. Depending on the type of item, it may have material, labour, and equipment costs. Uncertainty is addressed in the calculation of the material, labour, and equipment costs by importing the costs into Rts as Lognormal random variables. The mean of each random variable is the cost value provided by RSMeans, while the coefficient of variation is assumed to be 30%. Table 3.8 RSMeans data for calculating material, labour, and equipment costs ( ) CSI Code Description Unit $ CAD2019 (Vancouver) Material Labour Equipment 024116130050 Building demolition, large urban projects, concrete, includes 20-mile haul, excludes foundation demolition, dump fees C.F. - 0.17 0.27 024119161000 Selective demolition, cutout, concrete, elevated slab, bar reinforced, under 6 C.F., excludes loading and disposal C.F. - 35.97 7.4 031113255000 C.I.P. concrete forms, column, square, plywood, 8" x 8", 1 use, includes erecting, bracing, stripping and cleaning SFCA 3.34 6.17 - 032111600200 Reinforcing steel, in place, columns, #3 to #7, A615, grade 60, incl labor for accessories, excl material for accessories Ton 1255.63 807.91 - 033113350150 Structural concrete, ready mix, heavyweight, 3000 psi, includes local aggregate, sand, Portland cement (Type I) and water, delivered, excludes all additives and treatments C.Y. 137.52 - - 033113700400 Structural concrete, placing, column, square or round, pumped, 12" thick, includes leveling (strike off) & consolidation, excludes material C.Y. - 32.31 21.27 033513300200 Concrete finishing, fresh concrete flatwork, floors, basic finishing for unspecified flatwork, bull float, manual float & manual steel trowel, excl placing, striking off & consolidating S.F. - 0.61 - 033513300250 Concrete finishing, specified Random Access Floors ACI Classes 1, 2, 3 & 4, for Composite Overall Floor Flatness & Levelness to FF35/FL25, S.F. - 0.45 0.03 cCSI = CkCSI ⋅NkCSIk=1K∑CkCSI NkCSICkCSI 56 bull float, machine float & steel trowel (walk-behind), excl placing, striking off & consolidating 033529600050 Concrete finishing, walls, burlap rub with grout, includes breaking ties and patching voids S.F. 0.04 0.61 - 033529600600 Concrete finishing, walls, float finish, 1/16" thick S.F. 0.43 0.91 - 033713300020 Gunite, dry mix, applied in layers, 1" thick, excludes reinforcing mesh S.F. 0.44 0.88 0.27 033713300900 Gunite, preparation of old walls, excludes scaffolding, good condition S.F. - 0.78 - 033913500100 Curing, burlap, 10 oz., 4 uses assumed C.S.F. 30.5 8.17 - The direct cost of water, cWD is calculated here by multiplying the unit cost of water with the quantity of water:   (19) where CWD=cost of water in $/m3, and qWD=quantity of water in m3. The cost of water is given in Table 3.5 while the quantity is given by Eq. (15). The cost of energy, cQ, is (Haukaas et al., 2017)    (20) where =cost of energy source s, in $/L for fuel or $/kWh for electricity, =energy density conversion factor of energy source s, in J/L for fuel or J/kWh for electricity, and qs=quantity of energy source s, in L for fuel or kWh for electricity. Parameter values for Eq. (20) are listed in Table 3.9. Table 3.9 Energy cost conversions and density factors Cost Conversion Factors ( ) Energy Source Unit $ CAD2019 Source Natural gas building operations GJ 6.662 (Fortis BC, 2018) Electricity kWh 0.0829 < 1350 kWh 0.1243 > 1350 kWh (BC Hydro, 2018) cWD = CWD ⋅qWD cQ = CsQ ⋅ρsQs=1S∑ ⋅qsCsQ ρsQCsQ 57 Gasoline1 L 1.23 (GlobalPetrolPrices.com, 2019b) Diesel1 L 1.20 (GlobalPetrolPrices.com, 2019a) Liquid propane gas1 L 0.90 (GlobalPetrolPrices.com, 2019c) Energy Density Conversion Factors ( ) Energy Source Unit Value Diesel J / L 35800000 (US Department of Energy, 2017) Fuel oil J / L 34800000 Gasoline J / L 34200000 Liquid propane gas J / L 26000000 Natural gas J / L 37300 Electricity J / kWh 3600000 1 Canada wide average for the period 10-12-2018 to 18-3-2019 The cost of landfill disposal and recycling, cDR, is calculated in this dissertation by multiplying the cost of disposal or recycling with the quantity of material:   (21) where =cost of disposal or recycling for material m in $/tonne, and qm=quantity of material m in tonnes. The cost of landfill disposal is 70 $/tonne for wood and 90 $/tonne for other waste. The cost of recycling concrete is 32 $/tonne (Ecowaste, 2018), while the revenue from recycling steel is 110 $/tonne (Metro Vancouver, 2008). 3.7 HAZUS Earthquake Costs Probabilistic earthquake intensity models with ground motions as output, covering all possibilities during the building’s life, are still unavailable in state-of-the-art earthquake engineering. To address the cost of future earthquakes for the considered building, the HAZUS (FEMA-NIBS, 2003) approach is adopted. Earthquake hazard models output ground motion intensities, which are input to a building response model. The building response model provides drift values, which are used by the building damage model to calculate a ρsQcDR = CmDR ⋅qmm=1M∑CmDR 58 damage ratio. The repair cost of a building, cR, is calculated by multiplying the replacement cost of a building with its damage ratio:   (22) where CBLD=replacement cost of a building, and hB=building damage ratio that depends on the building type (C2M, S4M, W2, etc.). Full details of the hazard, building response, and damage models are described in Mahsuli and Haukaas (2013a; b). The regional seismic hazards considered for this building are summarized in Table 3.10 (Adams & Halchuk, 2003; Atwater & Hemphill-Haley, 1997). To investigate the effect of different material options on the total lifecycle cost of the considered building, the C2M Concrete, S4M Steel, and W2 Wood building types are examined. Table 3.10 Earthquake occurrence parameters  Earthquake Source Recurrence Relationship Return Period (years) CASR Poisson Point Process 5.34645 GSP Poisson Point Process 10.77853 JDFF Poisson Point Process 127.3269 JDFN Poisson Point Process 288.5004 BRO Poisson Point Process 0.485413 NOFR Poisson Point Process 9.7901 CST Poisson Point Process 6.904265 Subduction interface (full rupture) Lognormal Distribution LN~(590,105) 3.8 Indirect Cost of Emissions The indirect cost of emissions during the material manufacturing phase is addressed in this dissertation by using the ReCiPe2016 framework. For that reason, the cost of these emissions is considered in a different manner compared with the other emissions, addressed below. Utilizing the impact categories provided by ReCiPe2016, the cost, cML, is formulated as (Huijbregts et al., 2017): cR = CBLD ⋅ηB 59   (23) where K=number of impacts, e.g. climate change, and ozone depletion, =cost of a unit of an impact k in $/unit of impact, =conversion factor for a unit of impact k, per unit of material m, and qm=quantity of material m. Values for are given in Table 3.11 while values for  are listed in Table 3.12. Table 3.11 Cost of ReCiPe2016 impacts ( ) (Bijleveld et al., 2018a)  Impact Categories €2015 Agricultural land occupation 0.0845 Climate change 0.057 Freshwater ecotoxicity 0.0361 Freshwater eutrophication 1.86 Human toxicity 0.0991 Ionising radiation 0.0461  Marine ecotoxicity 0.00739 Marine eutrophication 3.11 Ozone depletion 30.4 Particulate matter formation 39.2 Photochemical oxidant 1.15 Terrestrial acidification 4.97 Terrestrial ecotoxicity 8.69 Urban land occupation 0.0845 Table 3.12 ReCiPe2016 impacts from OpenLCA for wood, steel, and concrete ( )  Impact Categories Unit Material (m) Wood [/m3] Steel [/kg] Concrete [/m3] Agricultural land occupation m2a 11813.3963 0.05156724 3.94886734 Climate change kg CO2e 133.910036 1.16766681 294.117880 Freshwater ecotoxicity kg 1.4-DBeq 0.95433475 0.23798990 0.92590455 Freshwater eutrophication kg Peq 0.01685197 0.00609882 0.032666 Human toxicity kg 1.4-DBeq 30.2057801 10.3748921 41.5635350 Ionising radiation kg U235eq 8.18794162 0.05167960 6.76122276 Marine ecotoxicity kg 1.4-DBeq 0.95043344 0.21889747 0.93714843 Marine eutrophication kg Neq 0.07337315 0.00065511 0.03180353 cML = CkMLk=1K∑m=1M∑ ⋅ !γ k ,m ⋅qmCkML!γ k ,mCkML!γ k ,mCkML!γ k ,m 60 Ozone depletion kg CFC-11eq 1.7889E-05 1.1546E-07 1.1736E-05 Particulate matter formation PM10 eq 0.4905943 0.00834546 0.3547566 Photochemical oxidant kg NMVOC 1.1978143 0.00620518 0.71276995 Terrestrial acidification kg SO2 eq 0.8185951 0.01702058 0.74050638 Terrestrial ecotoxicity kg 1.4-DBeq 0.02002139 0.00029095 0.01308382 Urban land occupation m2a 625.140551 0.02991476 3.09575297 The cost of environmental and human health impacts from emissions, cE, is calculated in this dissertation by multiplying the cost of an emission with the quantity of the emission:   (24) where =cost of impacts of emission n in $/kg, and En=quantity of emission n in kg, calculated from Eq. (16) and Eq. (17). Table 3.13 provides the human health costs of emissions while Table 3.14 provides the environmental costs. To address uncertainty in the calculation of emissions costs, the costs are imported into Rts as Lognormal random variables. The mean of the random variables are the cost values provided in Tables 3.13 and 3.14, while the coefficient of variation is assumed to be 20%. Table 3.13 Human health costs of emissions ( ) (Shindell, 2015) Emission USD2007 /ton  Carbon dioxide (CO2) 84 Methane (CH4) 4,600 Nitrous oxide (N2O) 37,000 Hydrofluorocarbon (HFC-134a) 160,000 Black carbon (BC) 270,000 Sulphur dioxide (SO2) 42,000 Carbon monoxide (CO) 630 Organic carbon (OC) 68,000 Nitrogen oxides (NOx) 67,000 Ammonia (NH3) 25,000  cE = CnE ⋅Enn=1N∑CnECnE 61 Table 3.14 Environmental costs of emissions ( ) (Bijleveld et al., 2018b)  Emission €2015/kg (3% discounting) Lower Central Upper Carbon dioxide (CO2) 0.0218 0.0566 0.0944 Methane (CH4) 0.673 1.74 2.90 Nitrous oxide (N2O) 5.78 1.50 2.50 Sulphur dioxide (SO2) 8.30 11.5 17.9 Carbon monoxide (CO) 0.0383 0.0526 0.0918 Nitrogen oxides (NOx) 9.97 14.8 22.1 Ammonia (NH3) 10.0 17.5 25.2 3.9 Indirect Cost of Downtime The cost of downtime, cDT, is calculated in the current work by multiplying the commercial rental income with the commercial floor area:   (25) where CDT=commercial rental income in $/ft2/yr, ACOM=commercial floor area in ft2, and tYR=time in years that the building is down. CDT is taken as 63.10 $/ft2/yr (CBRE, 2018).  3.10 Indirect Cost of Injuries and Deaths Injuries and deaths are directly related to the severity of building damage. In this dissertation, the FEMA (2013) methodology is used to translate building damage into casualties. The number of non-fatal injuries, NINJ, is calculated by multiplying the number of building occupants with the probability of being in a casualty severity level:    (26) where f OC=building occupancy factor, i.e., the fraction of occupants currently in the building at the time of the hazard, NOC=total number of building occupants, CSLm=casualty severity CnEcDT = CDT ⋅ACOM ⋅ tYRN INJ = f OC ⋅NOC ⋅ P CSL1( )+ P CSL2( )+ 0.25 ⋅P CSL3( )⎡⎣ ⎤⎦ 62 level for m=1,...,4 levels, and P(CSLm)=probability of being in a casualty severity level m. Similarly, the number of fatalities, NFTL, is    (27) It is assumed that 25% of the occupants in casualty severity level 3 sustain non-fatal injuries while the remaining 75% experience fatal injuries. The probability of being in a casualty severity level, P(CSLm), is (FEMA, 2013)       m=1,…,4 (28) where DS=building damage state for ds=1...4 damage states, P(CSLm|DS=ds)=probability of an indoor casualty of severity level m, given a damage state ds, and P(DS=ds)=probability of damage state ds. The probability of being in or exceeding a particular damage state DS, conditional on the peak building drift ratio, is defined as (FEMA, 2013):   (29) where =the standard-normal cumulative distribution function, =dispersion, i.e., the standard deviation of the underlying normal random variable, ln=the natural logarithm, d =peak building drift ratio, and =median drift value at the threshold of damage state DS. Parameter values for Eq. (28) and (29) are given in Table 3.15.  N FTL = f OC ⋅NOC ⋅ 0.75 ⋅P CSL3( )+ P CSL4( )⎡⎣ ⎤⎦P(CSLm ) = P(CSLm DS = ds) ⋅P(ds=14∑ DS = ds)P(DS ≥ ds δ ) = Φ 1βDSln δθDS⎛⎝⎜⎞⎠⎟⎡⎣⎢⎤⎦⎥Φ βDSθDS 63 Table 3.15 Indoor casualty probabilities and fragility curve parameters (FEMA, 2013)  Building Damage State - DS DS=1 (Slight) DS=2 (Moderate) DS=3 (Extensive) DS=4 (Complete) Indoor Casualty Severity Level m Indoor Casualty Probabilities (%) (Tables 13.3-13.6; FEMA, 2013) 1  0.05 0.25 (0.20 W2) 1.00 5.00 2  0.00 0.03 (0.25 W2) 0.10 1.00 3 0.00 0.00 0.001 0.01 4  0.00 0.00 0.001 0.01 Fragility Curve Parameters HAZUS Building Type Fragility Curve Parameters (Table 5.9a; FEMA, 2013) Median  C2M 0.0027 0.0067 0.02 0.0533 Dispersion  0.74 0.77 0.68 0.77 Median  S4M 0.0027 0.0053 0.016 0.0467 Dispersion  0.77 0.72 0.7 0.89 Median  W2 0.004 0.012 0.04 0.1 Dispersion  0.81 0.88 0.9 0.83 The total cost of casualties, cCAS, is calculated by adding the cost of injuries to the cost of fatalities:   (30) where CINJ=cost of a non-fatal injury, NINJ=number of non-fatal injuries, given by Eq. (26), CFTL=cost of a fatality, and NFTL=number of fatalities, given by Eq. (27). For this study, the cost of a fatality is $8,100,000 CAD2019 (Miller, 2000) while the cost of a nonfatal injury, i.e., fall, cut, struck, burn, is $10,015 CAD2019 (Finkelstein, Corso, & Miller, 2006).  3.11 Resulting Lifecycle Cost Curves For the building considered in study, three design options are analysed: 1) a wood option with glue-laminated columns and cross-laminated timber floor slabs, 2) a steel option with wide-flange columns and composite floor slabs consisting of steel decking and lightweight cCAS = C INJ ⋅N INJ +CFTL ⋅N FTL 64 concrete topping, and 3) a concrete option with reinforced concrete columns and slabs. The left-hand side of Figure 3.2 shows a rendering of the BIM that represents the building analysed in this study. The floor plan is shown on the right-hand side of Figure 3.2; all material options have a reinforced concrete shear wall in the centre that is intended to carry lateral load on the building, and to serve as an elevator shaft. The total building value according to the RSMeans Square Foot Estimator is $11,750,000 (RSMeans, 2019). Additional building information, height, square footage, etc., is provided in Section 1.6.  Figure 3.2 Realistic rendering of the considered building (left) and its floor plan (right) Table 3.16 provides dimensions and characteristics of the shear walls, slabs, and columns. The members were sized so that similar building drift ratios are observed with all three options.  Table 3.16 Shear wall, slab, and column characteristics  Shear Walls Wall thickness  0.2 m Longitudinal reinforcement spacing 0.2 m Longitudinal reinforcement type 20M Transverse reinforcement spacing 0.15 m Transverse reinforcement type 15M Concrete strength C40 Floors and Roof Slabs GSPublisherEngine 0.50.100.100 19 x 0'-6 5/8" = 10'-6"1 2 3 4 5 6 7 8 910111213141516171819 19 x 0'-6 5/8" = 10'-6"1 2 3 4 5 6 7 8 91011121314151617181936 m30 m5.2 m4 m 65 Reinforced Concrete Slabs Composite Steel Decking CLT Panels  Slab thickness 0.2 m Steel decking gauge 18 CLT panel thickness 0.30 m Longitudinal reinforcement spacing 0.2 m Longitudinal reinforcement type 15M Steel decking depth 75 mm Number of layers 5 Transverse reinforcement spacing 0.2 m Transverse reinforcement type 15M Lightweight concrete topping thickness 75 mm Type E1 Concrete strength C30 Columns Rectangular, Reinforced Concrete Steel Wide Flange Rectangular, Glulam Width 0.2 Designation W310x129 Width 0.3 m Depth 0.3 Number of longitudinal reinforcement bars along width 4 Web thickness 13.1 mm Number of longitudinal reinforcement bars along depth 6 Depth of section 318 mm Longitudinal reinforcement type 15M Flange width 308 mm Depth 0.35 m Transverse reinforcement spacing 0.2 m Transverse reinforcement type 10M Flange thickness 20.6 mm Concrete strength C30 Figure 3.3 shows the relative frequency diagrams of the total lifecycle cost for the wood, steel, and concrete material options. The wood option has the lowest mean cost followed by steel. The concrete option results in the largest mean cost, which is about 7%  66 greater than wood. Monte Carlo sampling was used to create the diagrams with 100,000 samples for each material option.   Figure 3.3 Relative frequency diagrams for the total lifecycle cost  The grey lines in Figure 3.4 show the accumulation of cost over time for many building lifetime scenarios, i.e., for many of the 100,000 samples. Material manufacturing and construction costs are responsible for the initial surge in cost. The subsequent steady increase is from operational costs, while the sudden cost increases at different points in time are caused by earthquakes. Operational costs accumulate nonlinearly as a result of discounting; a cost that occurs late in the building’s life contributes less to the total cost than a cost that occurs earlier. The conceptual probability distributions sketched in Figure 3.4 are included to emphasize that the total cost is uncertain; the right-most distribution is representative of those in Figure 3.3. A building lifespan of 50 years was used for this study. 6,000,000 7,000,000 8,000,000 9,000,000 10,000,000 11,000,000Relative FrequencyCost [$]Relative Frequency Diagrams of the Total Lifecycle CostConcreteSteelWood$8,001,960$8,102,730$8,587,360 67  Figure 3.4 Building lifetime scenario Figure 3.5 provides a breakdown of the total cost according to the lifecycle phases and Figure 3.6 breaks down the costs within each phase. Note that the costs in Figure 3.3 are discounted, while the costs presented in Figures 3.5  and 3.6  are not. This is because Figures 3.5  and 3.6  provide breakdowns of individual costs, and discounting is neglected to allow a one-to-one comparison of costs. It is seen in Figure 3.5 that about 70% of the total lifecycle cost occurs in the operations phase. Figure 3.6 shows that the greatest contributors to operational costs are the direct cost of energy and the emissions arising from its usage; specifically, carbon dioxide (CO2) emissions. This study assumes natural gas heating, which is common in the region. Although the direct cost of electricity is higher than natural gas, electric heating considerably reduces the total operations cost by about 65%. This is because the carbon dioxide equivalent (CO2e) from local electricity production is approximately 5% of the CO2 emitted from natural gas (Table 3.7). Hence, electric heating would reduce the Total Cost [$]Time [years]Construction CostDamage Repair CostDemolition Cost 68 overall cost to society, even though it results in increased costs for the developer, and slightly higher operational costs for the occupants.  Figure 3.5 Lifecycle costs by phase  2,058,088 1,695,603 2,030,878768,243558,765 352,90210,480,67210,480,682 10,480,672260,879249,803 210,7141,097,6711,061,838 1,022,69802,500,0005,000,0007,500,00010,000,00012,500,00015,000,00017,500,000Concrete Wood SteelCost [$]Comparison of Total Lifecycle Costs Manufacturing Construction Operations Damage and Repair Demolition 69  Figure 3.6 Lifecycle cost breakdown by phase Shown in Figure 3.5, the manufacturing phase is the next largest contributor to the total cost due to the cost of emissions from material production and the direct cost of materials. The greatest costs stem from human health impacts, specifically human toxicity and black carbon emissions. Closer examination of Figure 3.6 shows that these emissions are more prevalent in steel manufacturing. As a result, the steel option results in the greatest manufacturing emissions cost. The wood option has the lowest cost of emissions, about 30% less than steel and concrete. Concrete is the biggest driver of climate change due to the significant amount of CO2 emitted during its production. Using electric arc furnaces in steel production and carbon capture technologies in concrete production will impact these results.  In the construction phase, it is observed in Figure 3.5 that the steel option has the lowest cost while the concrete option has the highest. The concrete option requires more 02,000,0004,000,0006,000,000EmissionsMaterialsEnergyEmissionsLabourEquipmentEnergyEmissionsWaterEarthquake DamageCasualtiesEnergyEmissionsDisposalLabourEquipmentManufact. Construction Operations Damageand Repair Demolition1,079,517978,571581,7344,789,2505,333,091235,70725,1721,163,401867,477260,6344,789,250 5,333,091197,29113,423724,486 971,117471,3914,789,250 5,333,101358,331248,2001,603 86,677 386,706 553,354Cost [$]Lifecycle Costs BreakdownConcrete Steel Wood 70 labour hours than steel and wood combined. It also accounts for the most material by mass. As a result, the construction energy and emissions costs of concrete are about twice that of wood and steel, though these costs are comparatively small, as seen in Figure 3.6. Combining the costs of material, labour, and equipment in Figure 3.6 makes steel the most economical option from a developer’s perspective. However, including the cost of emissions makes wood the better option for society.  Figure 3.5 shows that the earthquake-related costs account for about 4% of the total lifecycle cost. Although the mean costs are low, when large earthquakes occur, the worst-case casualty and repair costs can exceed the value of the building. Overall, steel has the lowest repair cost. Wood is the most economical to repair when damage occurs; however, wood gets damaged more often, which results in a higher mean repair cost. Occupants of the concrete structure suffer the greatest number of casualties, while those in the wood structure suffer the least. In the worst-case scenario, out of the 100 building occupants there are 0.3 deaths and 5.6 injuries for the wood option, 0.7 deaths and 8.2 injuries for the steel option, and 1.3 deaths and 10.8 injuries for the concrete option.  The remaining paragraphs in this section provide a detailed comparison of the results for the concrete, wood, and steel materials options for the case study building. Table 3.17 provides a side-by-side comparison of key cost values for each material. These costs are provided again in Figures 3.7 to 3.10, according to the manufacturing, construction, operations, and demolition phases of the building. The bottom part of Table 3.17 shows the total values for the building lifecycle phases (Figure 3.5) and their impacts, i.e., energy, and emissions.   71 Table 3.17 Detailed lifecycle analysis results  Costs [$]  Material Concrete Wood Steel Energy from construction 56,936 10,395 21,414 Energy from operations 4,789,250 4,789,250 4,789,250 Energy from demolition 32,622 25,846 24,645 Emissions from manufacturing 1,079,517 724,486 1,163,401 Human health impacts from manufacturing emissions 605,322 519,216 614,619 Environmental impacts from manufacturing emissions 474,195 205,270 548,782 Emissions from construction 82,796 13,442 17,679 Emissions from operations 5,333,091 5,333,101 5,333,091 Emissions from demolition 11,929 9,254 8,740 Water consumption in operations 358,331 358,331 358,331 Construction labour time in days 1,955 405 466 Equipment 46,777 63,536 53,175 Materials 978,571 971,117 867,477 Labour 581,734 471,391 260,634 Repair of earthquake damage 235,707 248,200 197,291 Earthquake casualties 25,172 1,603 13,423 Total Costs [$] Manufacturing 2,058,088 1,695,603 2,030,878 Construction 768,243 558,765 352,902 Operations 10,480,672 10,480,682 10,480,672 Demolition 1,097,671 1,061,838 1,022,698 Sum of materials, equipment, and labour for  manufacturing and construction  1,607,082 1,506,044 1,181,286 Earthquake 260,879 249,803 210,714 Emissions 7,586,850 6,804,769 7,686,312 Energy 4,878,808 4,825,492 4,835,309 Mean cost (discounted) 8,587,360 8,001,960 8,102,730 Mean cost (undiscounted) 14,640,381 14,045,087 14,084,440  72  Figure 3.7 Breakdown of costs for manufacturing phase Figure 3.7 shows the breakdown of costs for the material manufacturing phase. As seen in Figure 3.7, the cost of emissions for concrete and steel is greater than the individual cost of the materials. Of the three, wood has the lowest cost of emissions, and the lowest manufacturing cost overall. If the cost of operational emissions is excluded, the cost of manufacturing emissions would be the largest contributor to the total lifecycle cost.  1,079,517724,4861,163,401978,571971,117867,4770500,0001,000,0001,500,0002,000,0002,500,000Concrete Wood SteelCost [$]Manufacturing PhaseEmissions Materials 73  Figure 3.8 Breakdown of costs for construction phase As observed in Figure 3.8, labour is the greatest contributor to the cost of construction for all three material options. It is also seen in the figure that the labour and energy costs of concrete are much higher than the other two materials. Concrete construction is more labour intensive because of formwork installation, concrete placing and finishing, stripping of the forms, etc. The wood and steel members are prefabricated which results in less installation labour. The concrete structure requires more material by volume, and concrete is also heavy. Thus, more energy is used in material transport.  56,936 10,395 21,41482,79613,442 17,679581,734471,391260,63446,77763,53653,1750100,000200,000300,000400,000500,000600,000700,000800,000900,000Concrete Wood SteelCost [$]Construction PhaseEnergy Emissions Labour Equipment 74  Figure 3.9 Breakdown of costs for operations phase Figure 3.9 provides the cost breakdown for the operations phase. It is seen in the figure that water contributes the least to the operational costs. Energy and emissions costs are the largest contributors, and the cost of emissions from energy usage is greater than the cost of energy. Note that the costs are similar for all three material options because the structural system has a very small impact on the energy performance of the building. The material composition of the exterior walls and the area of windows plays a larger role.  4,789,250 4,789,250 4,789,2505,333,091 5,333,101 5,333,091$358,331$358,331 $358,33102,000,0004,000,0006,000,0008,000,00010,000,00012,000,000Concrete Wood SteelCost [$]Operations PhaseEnergy Emissions Water 75  Figure 3.10 Breakdown of costs for demolition phase The breakdown of costs for the demolition phase is given in Figure 3.10. Unsurprisingly, the largest costs are from equipment, followed by labour and disposal. The cost of energy and emissions is relatively low, and roughly the same across all material options.   32,622 25,846 24,64511,929 9,254 8,740113,064 86,677 49,253386,707386,706386,706553,349553,354553,3540200,000400,000600,000800,0001,000,0001,200,000Concrete Wood SteelCost [$]Demolition PhaseEnergy Emissions Disposal Labour Equipment 76  Figure 3.11 Cost of emissions and environmental impacts for concrete material A detailed breakdown of the emissions and impact costs is provided in Figure 3.11 for concrete. It is seen in Figure 3.11 that the largest contributor to the cost of emissions for concrete is human toxicity, followed by black carbon particulate matter and sulfur dioxide emissions. Of all the costs in Figure 3.11, $654,200 is from damage to human health, while $488,314 is attributable to environmental damage. Concrete has the highest human health costs of the three. Also, in general the human health costs outweigh the environmental costs; a trend that is valid for all three materials.    0 50,000100,000150,000200,000250,000300,000Ammonia EmissionsBlack Carbon PM EmissionsCarbon Dioxide EmissionsCarbon Monoxide EmissionsHFC134a EmissionsMethane EmissionsNitrogen Oxides EmissionsNitrous Oxide EmissionsClimate ChangeFreshwater EcotoxicityFreshwater EutrophicationHuman ToxicityIonising RadiationMarine EcotoxicityMarine EutrophicationOzone DepletionParticulate Matter FormationPhotochemical OxidantTerrestrial AcidificationTerrestrial EcotoxicityUrbanLand OccupationOrganic Carbon EmissionsSulfur Dioxide EmissionsCost [$]Costs of Emissions and Impacts for Manufacturing and Construction Phases 77  Figure 3.12 Cost of emissions and environmental impacts for steel material  Figure 3.12 illustrates the emissions costs for the steel material option. Of these costs  $622,432 is from human health impacts, while $551,012 is from environmental impacts. Similar to concrete, the highest costs in the figure are from human toxicity, black carbon particulate matter, and sulfur dioxide. However, these costs are higher for the steel than they are for concrete; the steel human toxicity cost is highest emission cost for all three materials.  0 50,000100,000150,000200,000250,000300,000350,000400,000Ammonia EmissionsBlack Carbon PM EmissionsCarbon Dioxide EmissionsCarbon Monoxide EmissionsHFC134a EmissionsMethane EmissionsNitrogen Oxides EmissionsNitrous Oxide EmissionsClimate ChangeFreshwater EcotoxicityFreshwater EutrophicationHuman ToxicityIonising RadiationMarine EcotoxicityMarine EutrophicationOzone DepletionParticulate Matter FormationPhotochemical OxidantTerrestrial AcidificationTerrestrial EcotoxicityUrbanLand OccupationOrganic Carbon EmissionsSulfur Dioxide EmissionsCost [$]Costs of Emissions and Impacts for Manufacturing and Construction Phases 78  Figure 3.13 Cost of emissions and environmental impacts for wood material A detailed breakdown of the emissions costs is provided in Figure 3.13 for the wood material option. It is seen in the figure that the largest contributor is the cost of nitrogen oxides emissions, followed by black carbon particulate matter and particulate matter formation. Overall, wood has the lowest environmental costs of $207,500, and the lowest human health costs of $526,934. 3.12 Conclusions  A comprehensive collection of probabilistic models for calculating the total lifecycle cost of a building is presented. Several models are developed to quantify the impacts of manufacturing, construction, operations, demolition, and earthquake damage. These models rely on detailed and information-rich building models created from BIM. The building model 0 50,000100,000150,000200,000250,000Ammonia EmissionsBlack Carbon PM EmissionsCarbon Dioxide EmissionsCarbon Monoxide EmissionsHFC134a EmissionsMethane EmissionsNitrogen Oxides EmissionsNitrous Oxide EmissionsClimate ChangeFreshwater EcotoxicityFreshwater EutrophicationHuman ToxicityIonising RadiationMarine EcotoxicityMarine EutrophicationOzone DepletionParticulate Matter FormationPhotochemical OxidantTerrestrial AcidificationTerrestrial EcotoxicityUrbanLand OccupationOrganic Carbon EmissionsSulfur Dioxide EmissionsCost [$]Costs of Emissions and Impacts for Manufacturing and Construction Phases 79 contains components, which contain finite elements and other information required for lifecycle analysis.   New cost models are implemented to convert lifecycle concerns into costs. These costs include direct costs, such as materials and labour, and indirect costs, such as the cost of environmental impacts and damage to human health. Translating lifecycle concerns into cost complements the performance-based earthquake engineering and reliability-based design optimization approaches. An analysis is conducted for a specific building located in Vancouver, Canada. The relative frequency diagrams for the total lifecycle cost of concrete, wood, and steel options are presented and compared. Although not implemented here, additional models can be easily added to include the impacts of maintenance and structural retrofits.   80 Chapter 4: Visual Damage 4.1 Introduction A contribution in this chapter is the development and implementation of a seismic loss methodology that provides enriched estimates of the cost, duration, labour, and equipment requirements of repair. The specific objectives completed in this chapter are: 1) Develop  detailed visual damage models for structures subjected to earthquake ground motions; 2) Describe a collection of repair actions for different types and extents of visual damage; 3) Obtain enriched estimates of the cost and duration of repairs; and 4) Conduct a detailed seismic loss analysis on an entire building to show how the ground shaking duration, and the damage accumulated during the initial shaking, influences subsequent repairs.  Because an aim in this research is to contribute new models and insights to the ongoing advancement of performance-based earthquake engineering, a brief review of that field is provided here. Since the 1990s, structural engineers have attempted to predict the cost of damage, exemplified by the work in the Pacific Earthquake Engineering Research Center (Cornell & Krawinkler, 2000). The long-term vision in this work is to develop detailed computer simulation models for the holistic performance of structures, including more complete damage and cost estimates.   The emphasis in this research is on reinforced concrete slabs, rectangular columns, and shear walls. Non-structural components, such as windows, partition walls, and utilities could be addressed in a similar manner, but are not considered here. Collateral repair work, e.g., finishing removal, utility relocation, and re-installation is also considered outside the scope of this work.  81  Early research on damage prediction focused on damage indices. The influential Park and Ang damage index (1985) was developed for reinforced concrete components and a review of such indices is provided by Williams and Sexsmith (1995). Unfortunately, the association of specific types of visual damage with values of a damage index is often subjective and impractical for specifying repair actions. More recently, fragility functions have prevailed as an alternative to damage indices. The fragility-based approach uses discrete damage states of increasing severity to represent damage. Fragility functions provide the probability of a component being in a damage state, given an engineering demand parameter, such as inter-storey drift (Porter, Kiremidjian, & LeGrue, 2001). One methodology that adopts fragility functions for damage is FEMA P-58, seismic performance assessment of buildings (FEMA, 2018; Moehle & Deierlein, 2004; Yang et al., 2009). A computer program named PACT, which implements that methodology (FEMA, 2019), is employed in this research to compare cost estimates.   Fragility functions are conceptually appealing, and they represent a straightforward approach for modelling uncertainty. However, the type of damage attributed to a damage state is often subjective (Gencturk et al., 2016). Several types of damage are sometimes lumped into one damage state. Moreover, fragility functions do not provide detailed repair quantities or the specific location of the damage. This may impede efforts to compare alternative repair actions, potentially resulting in inaccurate cost estimates. At the cost of more comprehensive modelling, that problem is mitigated in the current work by means of detailed visual damage predictions using responses, primarily strains, from finite element analyses. The visual damage is employed to select repair actions, which in turn provide detailed estimates of cost, duration, crew, and equipment associated with the repairs.   82 4.2 Methodology The methodology presented in this research assumes that a finite element model is available for the building or the component. With that starting point the methodology consists of three steps: 1) Prediction of visual damage based on the finite element responses; 2) Selection of repair actions based on the visual damage; and 3) Prediction of cost and duration of repairs, as well as equipment and labour needs, based on the list of repair actions. The repair actions utilize the MasterFormat CSI codes (CSI, 2018) for material, labour, and equipment. The CSI codes are used in conjunction with the RSMeans database (RSMeans, 2019) to calculate the repair requirements. To link the finite element responses to the visual damage, a new component discretization scheme, called a damage mesh, is implemented. The damage mesh records the types, quantities, and the location of damage during earthquakes.  To facilitate the type of analysis presented here, a component discretization scheme is developed that uses several mesh types to estimate and visualize damage. Presented in Figure 4.1, a finite element mesh, damage mesh, and visualization mesh work together to display and record the properties of visual damage over time. Shown on the left-hand side of the figure, the finite element mesh provides the responses, i.e., stresses, strains, and deformations, from a structural analysis. As shown in the figure, the finite element mesh can vary depending on the analysis type, i.e., linear elastic or nonlinear, and also on the component geometry. Irrespective of the finite element mesh configuration, components are implemented to provide finite element responses anywhere within the component.  In the middle of Figure 4.1, the damage mesh links the finite element mesh with the visualization mesh, i.e., the mesh of the visible surface of a solid. Damage can be localized, or it can occur simultaneously across different surfaces of a component. For this reason, the  83 damage mesh created in this research partitions a component into damage regions according to sectors and segments. These regions are highlighted in the damage mesh that is shown in the middle of Figure 4.1. Each damage region requires one or more surfaces on which visual damage may occur. It is convenient to first partition the component cross-section into sectors. These sectors should define areas where the stresses and strains are expected to influence the damage at the adjoining surfaces. Examples of cross-section partitioning schemes are shown along the bottom of Figure 4.1. One such scheme used here is centroidal Voronoi tessellation (Du, Faber, & Gunzburger, 1999). In centroidal Voronoi tessellation, several points are specified over a cross-section. An algorithm then partitions the areas surrounding the points into sectors, so that each point becomes the centroid of the sector. When specifying these points, care should be taken to include areas of the cross-section that behave differently under loading, e.g., confined core concrete vs. cover concrete, and composite sections. The thickness of a cross-section is another important consideration, as damage in a thin section is likely to penetrate throughout its thickness.   84  Figure 4.1 Visual damage mesh discretization  A visualization mesh, shown in the right-hand side of Figure 4.1, contains the ingredients necessary to visualize damage on a computer. It is seen in the figure that the visualization mesh contains a damage surface, which in turn contains faces, edges, and vertices. A face represents part of a surface area, a vertex a point on a surface, and an edge a line that spans between two vertices. The faces, edges, and vertices serve two purposes: The faces are used to visualize damage on the surface, and the vertices and edges describe the deformed shape of the surface. To render visual damage on a computer, the damage mesh supplies the type of visual damage to a face. Next, the shape of the damage surface, i.e., coordinates of the vertices and edges, is provided by the finite element mesh, via the damage mesh. The damage mesh connects finite element nodes and vertices with rigid-links, or through interpolations such as splines. When deformations occur in the finite elements, these changes are picked up by the vertices and the shape of the rendered solid deforms accordingly.   85 4.3 Visual Damage  Visual damage is a vital concept in this work because it is what an estimator observes when preparing repair orders. The first step in implementing a visual damage model is defining the types of damage that can occur to a component. As the focus here is on reinforced concrete components, the damage types considered in this research are cracking, spalling, cover delamination, core crushing, reinforcement buckling, and reinforcement fracture. Cracking and reinforcement fracture occur under tension and the rest occur in compression.   The finite elements provide strains in the concrete cover, the core, and in the reinforcement. Strains are used because they are non-dimensional, unitless, and readily available in finite element analysis. A nonlinear finite element modelling approach is employed to capture the reduction in material strength and stiffness that occurs with extensive damage. Fiber-discretized, displacement-based elements (Scott, Fenves, McKenna, & Filippou, 2008) are used for the column components, and “MITC4” four-node shell elements (Bathe & Dvorkin, 1984) are used for the shear walls and floor slabs. The shear walls are modelled with nonlinear layered shell elements (Xiao Lu, Lu, Guan, & Ye, 2013), using the “plastic damage concrete plane stress” material model for the concrete layers and the “plate rebar” material model for the reinforcement layers. The Concrete02 and Steel02 material models in OpenSees are used in the fiber-discretized column elements. The right side of Figure 4.2 shows a quadrilateral reinforced concrete cross-section discretized with fibres. The brown circles within the cross-section represent steel fibres and the grey circles concrete fibres. Each bar of reinforcement is modelled as a discrete fibre. The concrete fibres consist of core fibres, shown in the middle of the cross-section, and cover fibres. Each fibre represents a discrete area of the cross-section, and it contains a location  86 within the cross-section (y, z coordinates) and a uniaxial material model. The material model governs the stress-strain relationship of the fibre. As seen in Figure 4.2, the individual fibres are queried to provide the stress and strain values at different points within the cross-section.   Figure 4.2 Fibre section forces, stresses, and strains  OpenSees employs many types of material models, from simple linear elastic materials, to inelastic materials that incorporate degradation effects over many loading cycles. Figure 4.3 shows stress-strain envelope of the OpenSees “Concrete02” material model (Yassin, 1994), used for the concrete fibres. The Concrete02 model approximates the tensile behaviour of concrete with linear tension softening and exhibits hysteretic behaviour.  yzxyzNxMyMzε steel ,σ steelεcover ,σ coverεcore ,σ coreF =NxxMzzM yy⎧⎨⎪⎪⎩⎪⎪⎫⎬⎪⎪⎭⎪⎪ 87  Figure 4.3 Concrete material model stress-strain backbone The Giuffré-Menegotto-Pinto steel material model, or “Steel02” in OpenSees (Filippou, Bertero, & Popov, 1983), is used to model the reinforcement fibres. Shown in Figure 4.4, the Steel02 model behaves symmetrically in compression and tension. It also incorporates hysteretic behaviour with isotropic strain hardening.  Figure 4.4 Steel material model stress-strain backbone Stress [MPa]Strain [mm/mm]Concrete Material ModelEtsEcλ·Ecf’cf’cuftεcu εcStress [MPa]Strain [mm/mm]Steel Material ModelfyEsb·EsR0,cR1,cR2 88 The various symbols shown in Figures 4.3 and 4.4, Ec, Ets, fy, etc., correspond to the material model parameters. Table 4.1 provides the descriptions of these parameters and the values used in the analyses. In Rts, material model parameters are stored in the material knowledge classes, e.g., RSteelMaterialKnowledge. Within these material knowledge classes, many material parameters are implemented as Lognormal random variables, as illustrated in Table 4.2. Table 4.1 Material model parameters Material Parameter Description Value Figure ft Concrete tensile strength  4.3 f’cu Ultimate concrete compression strength  Ec Concrete modulus of elasticity under compression  Ets Tension softening stiffness  l Ratio between unloading slope and initial slope 0.1 ecu Concrete strain at ultimate compressive strength 0.005 b Steel strain-hardening ratio 0.02 4.4 R0 Steel parameters that control the transition from the elastic to plastic branch 18 cR1 Steel parameters that control the transition from the elastic to plastic branch 0.925 cR2 Steel parameters that control the transition from the elastic to plastic branch 0.15 Table 4.2 Lognormal material model random variables Material Parameter Description Mean Value Coefficient of Variation Figure f’c 28-day concrete compressive strength 40 MPa (shear wall) 30 MPa (slab) 0.15 4.3 0.1⋅ fc'0.2 ⋅ fc'3300 ⋅ fc' + 6900Ec ⋅ ft2 ⋅ fc' 89 35 MPa (column) ec Concrete strain at f’c 0.002 0.05 rc Concrete mass density 2450 kg/m3 0.05 - nc Concrete Poission’s ratio 0.15 0.05 fy Steel yield stress 400 MPa 0.2 4.4 Es Steel modulus of elasticity 200 GPa 0.15 ns Steel Poission’s ratio 0.3 0.03 - rs Steel mass density 7900 kg/m3 0.05 Figure 4.5 illustrates the modelling of a reinforced concrete shear wall using multi-layer shell elements. Multi-layer shell elements have the advantage in that they are capable of simulating coupled bending-shear and coupled in-plane/out-of-plane bending behaviour of shear walls (Xinzheng Lu, Xie, Guan, Huang, & Lu, 2015). Older modelling techniques fail to account for the interaction between shear and bending which can affect structural behaviour. On the left of the figure, a layered shell cross-section contains multiple material layers with different properties. Each layer has a thickness, orientation, i.e., the direction of dominant material behaviour, and a material model. OpenSees multi-dimensional material (NDMaterial) models are used for the concrete and reinforcement layers. The core concrete layers are modelled with the “plastic damage concrete plane stress” material while the cover concrete is modelled with the “elastic isotropic plane stress” material. In contrast to the frame elements described above, the reinforcement bars are not modelled as individual fibres. Rather, the reinforcement layers are “smeared” into thin plates and modelled with the “plate rebar” material.  90  Figure 4.5 Multi-layer shell shear wall elements The graphic on the right of Figure 4.5 shows a shear wall discretized into many “MITC” four-node shell elements with membrane and drilling responses. The stress and strain responses provided at the midplane of this element are shown in the two leftmost graphics of Figure 4.6. These stress and strain responses are average values, calculated at four different points on the element, i.e., average of four integration points. The right side of Figure 4.6 illustrates how the axial in-plane strains are combined with the midplane rotations to get strains along the thickness of the shell. The visual damage models require strain values at different locations along the shell thickness, e.g., strains at the reinforcement and cover concrete.  Figure 4.6 Strain at the surface of shell element yzxε yyε xxMid-surface strainsσ =σ xxσ yyτ xyσ xxσ yyτ xyτ xzτ yz⎧⎨⎪⎪⎪⎪⎪⎪⎩⎪⎪⎪⎪⎪⎪⎫⎬⎪⎪⎪⎪⎪⎪⎭⎪⎪⎪⎪⎪⎪σ yyσ xxτ xyτ xyτ yzτ xzStressesIn-plane axial and shearOut-of-planeshearh2ε yyyh2ε xxx++==Top and bottom surface strainsBendingθ yyh2θ xxh2θ xxθ xxθ yyθ yyθ xyε =ε xxε yyγ xyθ xxθ yyθ xyγ xzγ yz⎧⎨⎪⎪⎪⎪⎪⎪⎩⎪⎪⎪⎪⎪⎪⎫⎬⎪⎪⎪⎪⎪⎪⎭⎪⎪⎪⎪⎪⎪ε ytopε xtopε xbottomε ybottom 91 As seen in the figure, the strains at the top and bottom surfaces in the y-direction, , are a combination of in-plane strains and strains interpolated from rotations:   (31) where eyy=in-plane, or “axial” strains in the y-direction, qxx=rotation around the x-axis, and h=element thickness. It is assumed here that the rotations are relatively small and the element is thin, i.e., a shell element. The rotation direction around any axis is given in accordance with the “righthand rule.” In this case, where rotations occur along the x-axis, the y-direction strain at the top surface, , is calculated by subtracting the rightmost term in Eq. (31) from the leftmost. Conversely, the strain at the bottom, , is calculated by adding the rightmost term to the left. Repeating the procedure in the x-direction, the strains are given with   (32) where exx=in-plane strains in the x-direction, qyy=rotation around the y-axis, and h was given above as the element thickness. Along the x-direction, the strain at the top, , is calculated by adding the rightmost term to the left in Eq. (32). The rightmost term is subtracted from the left for the bottom strain, .  4.3.1 Cracking Cracks are a normal occurrence in concrete structures. They occur during the drying process, from exposure to freeze-thaw cycles, and from detrimental chemical activity within the aggregate-cement paste interface. It is cracking from mechanical stresses, such as loading ε ytop,bottomε ytop,bottom = ε yy ∓θ xxh2ε ytopε ybottomε xtop,bottom = ε xx ±θ yyh2ε xtopε xbottom 92 from earthquakes, that is the focus here. Due to the heterogenous nature of concrete, the properties of individual cracks are inherently difficult to predict. As a result, the focal point of many equations in the literature is on estimating average crack properties, i.e., the average of many cracks distributed over a surface area. Cracking is a special case where strain is used to calculate a crack width. The crack properties considered here are the crack length, width, depth, spacing, and orientation. The top of Figure 4.7 shows the crack spacing, Sm, and length of crack, lCR, on the surface of a reinforced concrete component. The bottom part of the figure provides a cross-section of a crack that shows crack width at the surface, i.e., the maximum crack width, wMAX, and the average crack width, wAVG. In reinforced concrete components, the crack depth, dCR, is assumed to be equal to the concrete cover thickness.  Figure 4.7 Crack dimensions for repair quantities The cracking of concrete occurs under tension, or when (Collins & Mitchell, 1987)   (33) lCRdCRwAVGSmwMAXftc ≥ 0.33 fc' 93 where ftc=tensile stress in the extreme tension fiber, in MPa, and f’c=28-day compressive cylinder strength of concrete, in MPa. The righthand term in Eq. (33) is also known as the concrete cracking stress, or fcr. Cracking is a concern when    (34) where =crack width at the surface, and =crack width limit at which structural integrity and durability become a concern. The recommended crack width limit used here is (Table 7.6-1; Fédération internationale du béton, 2013)   (35)  The modified compression field theory (Vecchio & Collins, 1986) provides the crack width, spacing, and orientation for reinforced concrete shell elements such as slabs and walls. The modified compression field theory is applicable in situations where the element load is primarily carried by in-plane shear and axial stresses, e.g., membrane stresses in shell elements. The right side of Figure 4.8 provides a schematic of a reinforced concrete shell element with longitudinal and transverse reinforcement that is aligned with the x- and y-directions, respectively.   Figure 4.8 Crack parameters from finite element responses wMAX ≥ wLIMwMAX wLIMwLIM =0.3 mm for indoor environments0.2 mm when exposed to harsh environments⎧⎨⎪⎩⎪γεε1ε2 θε yxyε xγ xy2ε xε yε2Sθθε1smxxysmy 94 The average surface crack width, , in mm, is calculated with (Vecchio & Collins, 1986)    (36) where Sq=average crack spacing along q, in mm, q=crack orientation, and ϵ1=the principal tensile strain. The average crack spacing, Sq, is a function of the reinforcement spacing and the crack orientation:    (37) where Smx and Smy is the reinforcement spacing along the x and y directions, respectively, and q was defined previously as the crack orientation. The Mohr’s circle of strain, shown on the left-hand side of Figure 4.8, is used to derive the equations for the principal tensile strain, ϵ1, and principal compressive strain, ϵ2, from    (38) and the principal angle from   (39) where ex=in-plane strain along the x direction, ey=in-plane strain along the y direction, and gxy=shear strain in the xy plane. It turns out that the crack orientation, q, coincides with the principal angle. As shown in the middle sketch of Figure 4.8, the crack orientation is equal to wMAXwMAX = Sθ ⋅ε1Sθ =1sinθSmx+ cosθSmy⎛⎝⎜⎞⎠⎟ε1,2 =ε x + ε y2±ε x − ε y2⎛⎝⎜⎞⎠⎟2+γ xy2⎛⎝⎜⎞⎠⎟2θ = 12tan−1γ xyε x − ε y⎛⎝⎜⎞⎠⎟ 95 the angle between the reinforcement along the x-direction and the principal compressive strain ϵ2.  For flexural dominated components, such as beams and columns, a different approach is taken to calculate the crack widths and spacing. The mean crack width at the surface, , in mm, is calculated with (Leonhardt, 1988)   (40) where =average tensile strain in the member, and S=mean crack spacing, in mm, calculated with (CEB-FIP, 1978)   (41) where c=concrete cover thickness, in mm, Sm=reinforcement spacing (maximum 15×db), in mm, k1=coefficient to account for bond properties of reinforcement bars, taken as 0.4 for deformed bars, k2=coefficient to account for strain gradient in the reinforcement embedment zone, db=reinforcement bar diameter in mm, and ref=ratio of area of steel bonded to concrete, to the area of the effective embedment zone. The strain gradient coefficient, k2, is calculated with    (42) where ϵ1 and ϵ2 are the largest and smallest tensile strains in the reinforcement embedment zone. The ratio of area of steel bonded to concrete, to the area of the effective embedment zone, ref, is determined by wMAXwMAX = εtc ⋅SεtcS = 2 ⋅ c +sm10⎛⎝⎜⎞⎠⎟+ k1 ⋅ k2dbρefk2 =0.25⋅ ε1 + ε2( )2 ⋅ε1 96   (43) where Ab=area of the reinforcement, in mm2, and Acef=area of the embedment zone, in mm2, estimated as follows   (44) where db was defined earlier as the diameter of a reinforcement bar in mm.  The average crack width, , is here assumed to be half of the crack width on the surface:   (45) where  was defined previously to be the crack width at the surface. The volume of a crack, vCR, im m3, is calculated by multiplying the average crack width with the crack depth and length:   (46) where =average crack width, in m, dCR=crack depth, in m, and lCR=length of the crack, in m. Several cracks may occur over a surface area. The sum of crack volumes over the component gives the total crack repair volume:   (47) where K=total number of damage regions within a component, =volume of an average crack in damage region k, and =the number of cracks in damage region k, determined by ρef =AbAcefAcef = 225⋅db2wAVGwAVG = 0.5⋅wMAXwMAXvCR = wAVG ⋅dCR ⋅ lCRwAVGQCR = vkCR ⋅NkCRk=1K∑vkCRNkCR 97   (48) where la=dimension of damage region surface perpendicular to the direction of cracking, in mm, and S=crack spacing, in mm, given by Eq. (41).  4.3.2 Cover Spalling Concrete spalling results from compressive strains in the cover concrete and from the micro-buckling of the embedded reinforcement (Suda & Masukawa, 2000). Spalling occurs in compression when    (49) where =maximum compressive strain in the concrete cover, and =strain limit at which spalling occurs. The spalling strain limit is assumed to be a lognormal random variable with a mean of -0.0066 and a coefficient of variation of 0.33 (Lehman, Moehle, Mahin, Calderone, & Henry, 2004). Note that ATC-32 (Nutt, 1996) recommends a spalling limit of -0.004. The spalling repair quantity, QSP, in m3, is calculated by multiplying the surface area of repair with the depth of repair:   (50) where ASP=area of spalling, in m2, and dSP=depth of spalling, in m. As shown in Figure 4.9, the spalling repair depth is the sum of the cover thickness and reinforcement bar diameter:   (51) where h=concrete cover thickness, in m, and db=the greater diameter of the longitudinal or transverse reinforcement, in m. The spalled area, ASP, is equal to NkCR = la / SεCOVER ≤ εLIMITSPεCOVER εLIMITSPQSP = ASP ⋅dSPdSP = h+ db 98   (52) where A=surface area of a damage region, in m2, and r=ratio of the spalled area to the total surface area. It is assumed that spalling is a progressive form of damage. At its onset, a small ratio of an area will have spalled. As strains increase, the spalled area increases in size until the entire surface area has ultimately spalled off.  This damage progression is modelled with a spalling damage ratio   (53) where =the minimum spalling ratio (assumed to be 0.25), =strain limit at which cover loss occurs, =strain limit at which spalling occurs, and =compressive strain in the concrete cover, where .  Figure 4.9 Spalling repair quantities  ASP = A ⋅rr =1− rMINεLIMITCL − εLIMITSP⎛⎝⎜⎞⎠⎟⋅ εCOVER − εLIMITSP( )+ rMINrMIN εLIMITCLεLIMITSP εCOVERεLIMITSP ≤ εCOVER ≤ εLIMITCLdSPhdb 99 4.3.3 Cover Delamination The cover and core concrete, i.e., unconfined and confined concrete, are known to behave differently under loading. Compared to the unconfined cover concrete, the confined core region can sustain greater ultimate stresses and strains (Mander, Priestley, & Park, 1988).  As strains at the cover-core interface exceed the cover strain capacity, the cover concrete delaminates over large areas—as shown in the leftmost sketch of Figure 4.10. The delamination of concrete cover, or cover loss, occurs when    (54) where =compressive strain in the core, and was defined above as the strain limit at which cover delamination occurs. The cover delamination strain limit is assumed to be a lognormal random variable with a mean of -0.011 and a coefficient of variation of 0.22 (Lehman et al., 2004).  Figure 4.10 Cover loss repair quantities  εCORE ≤ εLIMITCLεCORE εLIMITCLhd 2·dbdb + 0.0125 100 The repair quantity for concrete cover loss, QCL, in m3, is given by   (55) where aCL=surface area of cover lost, in m2, and dCL=the repair depth in m. It is assumed that when cover delamination occurs, the cover is lost over the surface area of a damage region. As shown in the right-most graphic of Figure 4.10, the repair depth is calculated with   (56) where h=concrete cover thickness, in m, and db=the greater diameter of the longitudinal or transverse reinforcement in m. A depth of 0.0125 m is added to allow space for the repair material to penetrate behind the reinforcement layers.  4.3.4 Core Crushing, Reinforcement Fracture, and Reinforcement Buckling When reinforcement buckles, fractures, or when confined core crushing occurs, the component is deemed irreparable. Core crushing occurs when the compressive strain in the core exceeds the core crushing strain limit:   (57) where =maximum strain in the core, and =ultimate strain at which core crushing occurs. Reinforcement buckling occurs under compression when    (58) where =strain in the reinforcement, and =buckling strain of reinforcement. In tension, reinforcement fractures when   (59) QCL = aCL ⋅dCLdCL = h+ 3⋅db + 0.0125εCORE ≤ εLIMITCRUSHεCORE εLIMITCRUSHεREINF ≤ εLIMITBUCKLEεREINF εLIMITBUCKLEεREINF ≥ εLIMITFRACT 101 where =strain in the reinforcement, and =fracture strain of reinforcement. The strain limits for Eq. 57-59 are given in Table 4.3 below. As before, the strain limits are created as lognormal random variables with the mean and coefficient of variation given in the table.  Table 4.3 Visual damage strain limits Damage Type Mean Value Coefficient of Variation Strain Location Reference Core crushing -0.019 0.36 Core Lehman et al. (2004) Reinforcement buckling -0.038 0.30 Reinforcement Reinforcement fracture 0.125 0.20 Reinforcement (C.-K. Wang & Salmon, 1979) Note that not all damage modes are captured in the modelling. For example, the brittle shear failure of columns is neglected as it is assumed that the columns are adequately detailed to prevent such a failure. Also, the punching shear failure mode of slabs is excluded.  4.4 Repair Actions  The relationship between visual damage and repair actions is illustrated in Figure 4.11, which depicts a shear wall with several types of damage. The top-most graphic in the figure shows cracking, spalling, and cover delamination. The arrows leading off of the damaged areas point to sets of CSI codes. Each set of codes denotes a repair action, and each numbered code is a material, labour, or equipment item. The graphic in the middle of Figure 4.11 shows the repair action for the replacement of the concrete cover. It will be shown later that replacing the concrete cover may be a better option than repairing a myriad of other damage. The final recourse is component replacement, highlighted at the bottom of Figure 4.11. Component replacement entails demolition of the damaged component and construction of a new one. As shown on the right side of the figure, the CSI codes are used with RSMeans to provide the εREINF εLIMITFRACT 102 cost of repairing minor cracks and spalling, CREPAIR, cost of cover replacement, CCOVER, and the cost of component replacement, CREPLACE. The calculation of these costs from the CSI codes is described in the subsequent section.  Figure 4.11 Repair actions and CSI codes  This research considers conventional concrete repair actions, such as those outlined in EN-1504 (Raupach & Büttner, 2014). Other repair techniques, such as structural 036423000000030130620150030130622200033113250340033529600600033113705620030505100050024119192000024119180300031113852400033113704950031113850150033529600050033913500100031505705040031505705250031505705600031505705550031505705650030505100060038116500820024119271040024119192000024119190118024119180300038216100700036305101535031113852400032111600700033113705100033529600050033913500100Shear wall replacementCover replacementCracking, spalling, and cover patch repairCCOVERCREPLACECREPAIR033113250340033529600600033113705620CrackingSpallingCover delaminationRSMeans$RSMeans$RSMeans $030130620150030130622200036423000000 103 strengthening, e.g., fiber wrapping, are not considered. The goal here is to return the component to its pre-damaged strength and functionality. For structural repair of cracking, only epoxy injection is considered. Damage that is shallow and over a small area, e.g., cover spalling, is repaired with hand-applied mortar. Concrete cover replacement becomes the preferred option with extensive damage. This entails chipping away the damaged areas and recasting the cover concrete, i.e., formwork is installed, and concrete is placed in the typical manner of new construction. In situations where recasting is not feasible, e.g., an overhead repair on a ceiling, then spray-on repairs are used.  For concrete components, repair actions generally contain the following steps (Grantham, 2011):  1. Selective demolition of damaged area, i.e., chipping away cracked concrete; 2. Removal, hauling, and disposal of demolition material; 3. Formwork installation, temporary bracing, and surface preparation, if required;  4. Repair material procurement and placement; and 5. Finishing and curing of the repair surface. The first step, selective demolition, encompasses demolition activities that are carefully executed using hand tools, with regard to surrounding components and finishes. This is followed by the removal and transport of demolition material to a landfill or recycling facility. Depending on the type of damage, the repair may require special surface treatments, such as sandblasting, bracing of adjacent components, or formwork for casting the repair material. Where repair material is set over existing material, the repair material and the underlying native material should have similar mechanical characteristics, to prevent premature repair failure. Here, the repair material concrete type, e.g., C15, C20, C25, is  104 matched so that it is of the same type as the original concrete used in the construction of the component. The final step involves finishing and curing of the repair material surface. There may be additional steps such as removing/replacing finishing or utility relocation around the repair area. This collateral work, i.e., not related to the repair of a structural component, is not included here. It is assumed here that cracks are repaired solely by epoxy injection. The expectation is that epoxy injection repairs return the component to its pre-damaged load carrying capacity. For components like walls and slabs, this type of repair assumes that there is access to the other side of the component. This is so that cracks that permeate through the thickness of the component can be sealed off to prevent escape of epoxy on the other side. Crack repair by chipping and filling is not considered here. Also not considered here is the coating over of cracked surfaces with a thick epoxy-based paint.  For relatively small and shallow damaged areas, such as when spalling starts to occur, hand-applied mortar is used for repair. This type of repair requires preparing the surface through chipping and sandblasting, followed by the application of repair mortar by hand. It is expected that the repair mortar is mixed on-site in the vicinity of the repair. Concrete cover replacement becomes the preferred option when damage occurs over a large area. Replacing the cover concrete entails chipping away and recasting the cover concrete on the entire face of the wall. Recasting means that formwork is installed, and the repair concrete is placed and cast in the typical manner of new construction. In the situations where recasting is not feasible, e.g., an overhead repair on a ceiling, then spray-on or “gunite” repairs are used. In spray-on repairs, the “dry-mix” repair material is included in the CSI code and it is priced per inch of thickness. It is assumed that no reinforcement mesh is  105 required because the component reinforcement serves this purpose. Also, after application, the spray-on concrete is finished to a high tolerance. To demonstrate the implementation of a repair action, consider the replacement of the reinforced concrete shear wall of Figure 4.11. Presented in Table 4.4, the major steps, e.g., formwork installation, and concrete placing, are given as boldface headings. The CSI items are enumerated under each activity along with their descriptions, units, and CSI codes. Several items depend on a certain parameter, e.g., the concrete formwork is determined by the wall height. The replacement repair action shares many of the same CSI codes as new construction. Notable differences are the shoring, demolition, disposal, and reinforcement dowel installation codes. Additional repair actions for the wall, column, and slab components are given in Appendix C. Table 4.4 Replacement repair action of reinforced concrete shear wall Condition CSI Code Unit Description Bracing and shoring Assume 8 frames 031505705040 EA Frame shoring system, frame, 12000# per leg, 2' wide x 6' high, steel, buy 031505705250 EA Frame shoring system, X-brace, 12000# per leg, steel, buy 031505705600 EA Frame shoring system, screw jack, 12000# per leg, steel, buy 031505705550 EA Frame shoring system, base plate, 12000# per leg, steel, buy 031505705650 EA Frame shoring system, U-head, 12000# per leg, 8" x 8", steel, buy Demolition Reinforcement ratio <= 0.01 030505100050 CY Selective concrete demolition, reinforcing less than 1% of cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping 0.01 < Reinforcement ratio <= 0.02 030505100060 CY Selective concrete demolition, reinforcing 1% - 2% of cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping Reinforcement ratio > 0.02 030505100070 CY Selective concrete demolition, reinforcing more than 2% cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping Assume entire length of wall 038116500820 LF Concrete sawing, concrete walls, rod reinforcing, per inch of depth  106 Assume entire length of wall 024119271040 LF Selective demolition, torch cutting, steel, reinforced concrete walls, 12"-16" thick, oxygen lance cutting Removal and disposal 0-50 ft hauling distance of material 024119192000 CY Selective demolition, rubbish handling, 0'-50' haul, load, haul, dump and return, hand carried, cost to be added to demolition cost  024119190118 EA Selective demolition, rubbish handling, regular chute, circular steel 4' length, 30" diameter, cost to be added to demolition cost Distance to disposal facility < 5 miles 024119180300 CY Selective demolition, disposal only, urban buildings with salvage value allowed, concrete frame, includes loading and 5 mile haul to dump Drilling and embedment of reinforcement dowels 1 dowel per 16 in of length, per side 038216100700 EA Concrete impact drilling, for anchors, up to 4" D, 1" dia, in concrete or brick walls and floors, includes bit cost, layout and set up time, excl anchor  036305101535 EA Chemical anchoring, for fastener 1" diam x 8" embedment, incl epoxy cartridge, excl layout, drilling & fastener Formwork (site-built from plywood) Wall height <= 8 ft 031113852000 SFCA C.I.P. concrete forms, wall, job built, plywood, to 8' high, 1 use, includes erecting, bracing, stripping and cleaning 8 ft. < Wall height <= 16 ft 031113852400 SFCA C.I.P. concrete forms, wall, job built, plywood, over 8' to 16' high, 1 use, includes erecting, bracing, stripping and cleaning Wall height > 16 ft 031113852700 SFCA C.I.P. concrete forms, wall, job built, plywood, over 16' high, 1 use, includes erecting, bracing, stripping and cleaning Box-out per each opening 031113850150 EA C.I.P. concrete forms, wall, box out for opening, to 16" thick, over 10 S.F. (use perimeter), includes erecting, bracing, stripping and cleaning Installation of reinforcement Reinforcement diameter <= 20M 032111600700 TON Reinforcing steel, in place, walls, #3 to #7, A615, grade 60, incl labor for accessories, excl material for accessories Reinforcement diameter > 20M 032111600750 TON Reinforcing steel, in place, walls, #8 to #18, A615, grade 60, incl labor for accessories, excl material for accessories Concrete placing (pumped) Wall thickness <= 8 in 033113704950 CY Structural concrete, placing, walls, pumped, 8" thick, includes leveling (strike off) & consolidation, excludes material 8 in. < Wall thickness <= 12 in 033113705100 CY Structural concrete, placing, walls, pumped, 12" thick, includes leveling (strike off) & consolidation, excludes material 12 in. < Wall thickness <= 15 in 033113705350 CY Structural concrete, placing, walls, pumped, 15" thick, includes leveling (strike off) & consolidation, excludes material Finishing and curing  107  033529600050 SF Concrete finishing, walls, burlap rub with grout, includes breaking ties and patching voids  033913500100 CSF Curing, burlap, 10 oz., 4 uses assumed There are situations where repair actions are overridden and replaced with more pragmatic solutions. Consider the approach for selecting repair actions presented in Figure 4.12. The first decision point at the top of the figure checks whether the component is repairable. Strains, e, in the core concrete and reinforcement are compared to the crushing, buckling, and fracture strain limits. The component is assumed irreparable and replaced if any of the inequalities are true. Replacement also occurs if the repair costs exceed 75% of the component replacement cost. Preference is given to new components as they have a longer service life and a lower risk of repair failure. Illustrated in the middle of Figure 4.12, the minimum of the cover replacement cost, CCOVER, and the cost of repairing miscellaneous damage, CREPAIR, is weighed against the component replacement cost, CREPLACE.    108  Figure 4.12 Repair action selection procedure  At the final decision point, given at the bottom of Figure 4.12, cover replacement takes precedence if its cost is less than the cost of miscellaneous repairs. Cover replacement is more straightforward than a myriad of smaller repairs and provides greater security against repair failure. Here the direct repair cost, i.e., cost of materials, labour, and equipment is used as a decision criterion for selecting repair actions. However, a comprehensive cost that includes the costs of energy use, emissions, downtime, etc., may lead to better repair actions with the lowest overall impact.   4.5 Repair Cost, Duration, and Labour Requirements  The RSMeans database provides cost values for the required materials, labour, and equipment. Table 4.5 highlights several items from RSMeans along with their CSI codes, YesYesNoReplace shear wallCracking, spalling, and cover patch repairNoReplace cover concreteCCOVER ≤CREPAIR0.75⋅CREPLACE ≤min CCOVER ,CREPAIR( )YesReplace shear wallNoεCORE ≤ εLIMITCRUSHεREINF ≤ εLIMITBUCKLEεREINF ≥ εLIMITFRACT 109 detailed description, and costs. The materials, labour, and equipment costs provided by RSMeans are “bare” costs. They do not include profit and overhead expenses that would normally be included in a repair estimate. As shown in the far-right columns of Table 4.5, RSMeans provides a bare total, and an all-in cost that includes profit and overhead. Using the all-in cost, the bare costs are marked up so that they are representative of what a building owner would pay a repair contractor. Table 4.5 RSMeans data for material, labour, and equipment costs  CSI Code Description Unit $ CAD2019 (Vancouver) Material Labour Equipment Bare Total Total with Overhead and Profit 024119161000 Selective demolition, cutout, concrete, elevated slab, bar reinforced, under 6 C.F., excludes loading and disposal CF - 35.97 7.4 43.37 67.04 031113255000 C.I.P. concrete forms, column, square, plywood, 8" x 8", 1 use, includes erecting, bracing, stripping and cleaning SFCA 3.34 6.17 - 9.51 13.88 033053403300 Structural concrete, in place, elevated slab, floor fill, (Portland cement Type I), placing and finishing, excl forms, reinforcing SF 1.34 0.91 0.47 2.72 3.35 The direct cost of repair, cCSI, is calculated in this dissertation as   (60) where ds=demand surge, a scaling factor greater than or equal to 1, K=number of CSI items, = cost of item k from the RSMeans database, including markup, and =number of items k. A demand surge is included for repair costs because immediately after an earthquake the costs are likely to increase due to the scarcity of labour and materials (Olsen & Porter, cCSI = dS ⋅ CkCSI ⋅NkCSIk=1K∑CkCSI NkCSI 110 2011). The demand surge is assumed to be 20% of the cost from RSMeans. To address uncertainty in the calculation of repair costs, the costs from RSMeans are imported into Rts as Lognormal random variables. The mean of the random variable is taken as the value provided by RSMeans, and the coefficient of variation is assumed to be 30%.  Two time-related considerations are made in this research, i.e., repair duration and total labour time. The repair duration is the amount of time it takes a repair crew to complete its allotted tasks. The total labour-time is the accrued time spent by all labourers to complete the repair. Suppose a task requires a crew of 10 labourers and it takes 2 hours to complete the task. In that case, the repair duration is 2 hours and the total labour-time is 20 hours. The repair duration, tREPAIR, in hours, required to complete K tasks is calculated here as   (61) where K=total number of labour tasks, each corresponding to a CSI code, = labour rate, in hours, for a crew to complete one unit of task k, and =number of units of task k. The labour rate represents the productivity of a crew and is specific for each CSI task. However, crews can be reused for multiple tasks. Note that with multiple crews, the actual repair duration can be less than the time calculated here as some tasks could be completed in parallel. Labour rates are provided in Table 4.6 for several tasks along with their CSI codes, descriptions, units, and recommended crews.   tREPAIR = lkCSI ⋅NkCSIk=1K∑lkCSINkCSI 111 Table 4.6 RSMeans data for labour  CSI Code Description Unit Crew Code Labour rates (hour) 024119161450 Selective demolition, cutout, concrete, walls, bar reinforced, 6-12 C.F., excludes loading and disposal CF B9 0.571 024119180300 Selective demolition, disposal only, urban buildings with salvage value allowed, concrete frame, includes loading and 5 mile haul to dump CY B3 0.132 031113852400 C.I.P. concrete forms, wall, job built, plywood, over 8' to 16' high, 1 use, includes erecting, bracing, stripping and cleaning SFCA C2 0.171 033113704950 Structural concrete, placing, walls, pumped, 8" thick, includes leveling (strike off) & consolidation, excludes material CY C20 0.640 032111600750 Reinforcing steel, in place, walls, #8 to #18, A615, grade 60, incl labor for accessories, excl material for accessories TON 4 Rodm 8.0 033529600600 Concrete finishing, walls, float finish, 1/16" thick SF 1 Cefi 0.027 To calculate the total labour-time, tLABOUR, in hours, Eq. (61) is modified to include a term for the number of labourers in a crew so that   (62) where =number of labourers in a crew. The labour rates are imported from RSMeans as Lognormal random variables, taking the RSMeans value as the mean and assuming a 30% coefficient of variation.   Detailed crew information is important because, when earthquakes occur, skilled labourers and specialized equipment may be difficult to procure as a result of a high demand. To demonstrate how crew information is obtained, Table 4.7 provides the crew rosters for the crews from Table 4.6. Table 4.7 Crew labour and equipment requirements from RSMeans Crew Code Labourers Equipment B9 1 Labour foreman Air compressor, 250 cfm tLABOUR = lkCSI ⋅NkCSI ⋅k=1K∑ NkLABOURNkLABOUR 112 4 Labourers 2 Breakers, pavement, 60 lb. with 2 50’ air hoses B3 1 Labour foreman 1 Crawler loader, 3 CY 2 Labourers 1 Equipment operator (medium) 1 Crawler loader, 3 CY 2 Truck drivers (heavy) C2 1 Carpenter foreman Personal hand tools 4 Carpenters 1 Labourer C20 1 Labour foreman 2 Gas engine vibrators 5 labourers 1 Cement finisher 1 Concrete pump (small) 1 Equipment operator (medium) 4 Rodm 4 Reinforcement installation rodmen Personal hand tools 1 Cefi 1 Cement finisher Personal hand tools RSMeans provides unique crew identifiers, displayed under the column heading “Crew Code” in the tables. The breakdown of the labourer and equipment requirements for each crew is given in Table 4.7. The middle column provides the itemized list of labourers including foremen, equipment operators, common labourers, etc. Summing up the labourers gives the size of the crew. Specialty equipment that a crew requires is highlighted in the rightmost column of the table. Some codes in Table 4.7 correspond to crews that contain the same type of skilled labourer, such as Rodm which stands for reinforcement installer, or Cefi which stands for cement finisher.  4.6 Study of a Shear Wall  To compare the FEMA approach with the proposed approach, the B1044.092 shear wall from the PACT tool is subjected to a pushover analysis in Rts. The shear wall is 0.305 m thick, 3.658 m high, and 6.096 m long. Using a nonlinear static pushover analysis, the repair cost is plotted with respect to the drift ratio. In addition, the visual damage is rendered at several key storey drift ratios and compared to the descriptions of visual damage provided by FEMA.   113 The PACT tool relies on fragility curves to estimate the “damage state” of a component, i.e., visual damage. Figure 4.13 shows the three damage state fragility curves for the considered wall that are provided by the PACT tool. The median storey drift values for each damage state are shown in the figure above the dashed vertical lines. The repair cost, cFEMA, is calculated using fragility functions and the theorem of total probability (FEMA, 2018):   (63) where DS=discrete random variable representing the damage state, ds∈{1,2,3}=realizations of DS, f=drift ratio, and Cds=repair cost associated with damage state ds. Utilizing the fragility functions in Figure 4.13, the probability of a particular damage state is    (64) As an example, the probability of being in damage state 2 is shown graphically in Figure 4.13 as P(DS=2). The repair duration is calculated using a similar approach, except that the repair cost is replaced with repair time. Per wall panel area of 13.38 m2, values provided by FEMA for the repair cost are $6,570 for ds=1, $21,402 for ds=2, and $49,028 for ds=3.  cFEMA = P(DS = ds φ) ⋅Cdsds=13∑P(DS = ds φ) = P(DS > ds φ)− P(DS > ds+1φ) 114  Figure 4.13 Damage state fragility functions   Figure 4.14 shows screenshots of Rts, rendering the visual damage of the shear wall at the median drift values, d, of the three damage states. To generate these renders, a load is applied along the top of the wall, from left to right, until the drift value is reached. The render corresponding to Damage State 1 is given at the top of Figure 4.14, and shows cracking along the left-hand side and minor spalling in the bottom-right corner of the wall. The middle plot of Damage State 2 shows more advanced cracking and spalling. Given at the bottom of the figure, the render of Damage State 3 shows cover loss and core crushing in the bottom-right corner, and heavy cracking and spalling elsewhere. The damage renders in Figure 4.14 coincide with the FEMA descriptions of damage. FEMA describes Damage State 1 as spalling of cover and cracks greater than 1/16”. Damage States 2 and 3 are characterized by 0.0093 0.0128 0.01860.00.20.40.60.81.00.00 0.01 0.02 0.03 0.04 0.05 0.06P(D>DS n| f)Storey Drift Ratio f [rad]Damage State 1Damage State 2Damage State 3P(DS=2) 115 mixed damage with exposed longitudinal reinforcement, core concrete damage, and/or reinforcement buckling.   Figure 4.14 Visual damage at the median storey drift values of the damage states The comparison between the proposed approach and the FEMA approach is shown in Figure 4.15. The FEMA repair cost curve is calculated with Eq. (63), including collateral work, e.g., finish removal and replacement, scaffolding, relocation of utilities, debris removal. The approach proposed here considers the structural repair of the wall, with no allowance made for collateral work. To facilitate comparison, the values given by FEMA are scaled by a value of 0.25. That choice is supported by the repair cost breakdowns in Beck et al. (2002), which results in a ratio of roughly 0.15 between the cost of structural repair and collateral works. Furthermore, the FEMA values are in US dollars from 2007 (FEMA, 2018). Damage State 3ẟ = 0.019Damage State 2ẟ = 0.013Damage State 1ẟ = 0.009 116 Accounting for inflation and currency exchange rates (USD2007 to CAD2020) results in the selected scaling of 0.25.   It is observed in Figure 4.15 that the two approaches are generally in agreement. The proposed approach, represented by a solid line in the figure, results in higher repair costs except for drift values between about 0.02 and 0.03. The early rise in cost of the proposed approach is from epoxy repair of cracking, and from sporadic repair of spalling. The initial plateau, seen in the proposed approach, occurs when the replacement of the cover concrete becomes more economical than repairing a myriad of cracking and spalling. It is seen in the figure that this initial plateau occurs fairly quickly, at a drift ratio of 0.01, just past the median drift value of Damage State 1. Concrete cover replacement continues to be the best repair action until a drift ratio of about 0.03. After this point, the final plateau follows, where the component replacement cost, shown as a dotted line in Figure 4.15, becomes more economical than the cost of repair.   117  Figure 4.15 Repair cost of reinforced concrete shear wall A comparison of repair duration between the proposed and FEMA approach is given in Figure 4.16. As seen in the figure, the repair duration of the proposed approach jumps to its highest value when the cover replacement repair action is selected; at a storey drift ratio of about 0.01. In contrast to the repair cost, the repair duration goes down slightly when component replacement becomes the preferred repair action. This is because removing and patching damaged cover concrete is more economical, but slightly more labour intensive than replacing the entire component.  05,00010,00015,00020,00025,0000 0.01 0.02 0.03 0.04 0.05 0.06Repair Cost [$]Wall Drift Ratio [rad]ProposedFEMAReplacement Cost 118  Figure 4.16 Repair duration of reinforced concrete shear wall 4.7 Study of a Six-storey Building  The proposed visual damage centred approach is here applied to a six-storey building to provide additional insights into the repair of earthquake damaged structures. A visual rendering of a building information model, BIM, of the considered building is shown in the top of Figure 4.17. The image is created with the computer program ArchiCAD. The bottom-left side of Figure 4.17 shows the floor plan and structural layout. The reinforced concrete shear walls in the centre are intended to carry lateral load on the building and serve as stairwells and elevator shafts. Detailed building information is provided in Section 1.6. 0246810121416180 0.01 0.02 0.03 0.04 0.05 0.06Repair Duration [days]Wall Drift Ratio [rad]ProposedFEMA 119  Figure 4.17 Rendering of building (top), floor plan (bottom left), and finite element model (bottom right) In order to understand the repair of damage over a wide range of deformations, a series of nonlinear static pushover analyses are first conducted. The repair cost, duration, and labour-time is determined for loading in different directions. The loads are first applied in E-W and N-S directions individually, and then in both directions at the same time. Stiffness GSPublisherEngine 0.50.100.100 19 x 0'-6 5/8" = 10'-6"1 2 3 4 5 6 7 8 910111213141516171819 19 x 0'-6 5/8" = 10'-6"1 2 3 4 5 6 7 8 91011121314151617181936 m30 m5.2 m4 mN 120 contributions from partition walls are neglected and the members on the ground floor are fully fixed to the ground.  Figure 4.18 shows the repair cost plotted against the building drift ratio. The results from loading in the E-W direction are given as a solid line, in the N-S direction as a dashed line, and in both directions as a dotted line. It is seen in the figure that the repair costs increase substantially around 0.5% to 0.8% drift for all three curves. The nonlinear finite element analyses stop converging at around 3.5% drift. An observation made in Figure 4.18 is that the curve for dual-direction loading is greater than the individual load cases up to a drift ratio of 1.4%. After this point, the loading in the N-S direction causes higher repair costs. When loading is applied exclusively along the N-S direction, i.e., the weak direction, more damage occurs than if it is applied in both directions. Figure 4.18 also shows that, once the repair cost starts to accumulate around the 1% drift level, the curves follow an approximately linear trend. Because of this, it can be tempting to scale repair costs that have been calculated at smaller drift ratios. However, it is shown later in this chapter that this is not the case when the structure is subjected to an earthquake ground motion.  121  Figure 4.18 Repair cost vs. building drift ratio from pushover analysis  The repair duration, shown in Figure 4.19, is closely correlated to the repair cost. As the repair cost increases, so does the repair duration. The curves in Figure 4.19 show that the repair duration becomes significant around a 1% drift. Like repair cost, from a drift ratio of 1% the increase in repair duration is approximately linear. 050,000100,000150,000200,000250,000300,000350,000400,000450,000500,0000 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04Repair Cost [$]Building Drift Ratio [rad]E-W DirectionN-S DirectionE-W and N-S 122  Figure 4.19 Repair duration vs. storey drift ratio for building pushover analysis Values for the repair cost, duration, and labour-time are listed in Table 4.8  at the maximum drift that was attained in the pushover analyses prior to non-convergence. The table breaks down the cost according to slab, column, and shear wall contributions. The results in Table 4.8 show that damage to the shear walls, and to an extent the columns, are the predominant drivers of the repair cost. This is expected because the shear walls are the primary lateral force resisting system of the building, thus the lateral loads will have the greatest effect on the walls. Table 4.8 also highlights the difference between the repair duration and labour-time. It is observed that the labour times are several times greater than the repair durations. The reason for this is that labour-time is determined by the number of labourers in a crew, while the repair duration only depends on the number of crews. Not 0501001502002503000 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045Repair Duration [Days]Building Drift Ratio [rad]E-W DirectionN-S DirectionE-W and N-S 123 shown in the table, the worst-case repair for bi-directional loading requires 59 labourers and 15 crews. In total, these crews and labourers are responsible for 1,087 repair tasks.  Table 4.8 Repair cost and duration for pushover analysis  Load Direction Final Drift Ratio [rad] Repair Cost [$] Repair Duration [Days] Labour- time [Worker- days] Slabs [$] Columns [$] Shear Walls [$] E-W 0.034 334,592 231 932 0 46,380 288,212 N-S 0.026 303,185 162 674 477 2,817 299,891 E-W and N-S 0.037 356,940 224 856 1,907 28,960 326,073 To demonstrate the proposed approach in a more realistic earthquake scenario, the building is subjected to a damaging ground motion. The considered M7.3 earthquake occurs in the Strait of Georgia, 27 km from the building. This scenario is addressed in several studies of potentially severe shaking in the Vancouver region (Kay, 2009). As a ground motion for this earthquake, the 1949 M7.1 Olympia, Washington, earthquake is employed (Baker & Langston, 1987). The magnitudes are similar and the distance from the epicenter and the soil characteristics are comparable between the recorded ground motion and the site of the considered building. The employed time-histories were recorded at the Olympia Highway Test Laboratory. The top two graphs in Figure 4.20 show the acceleration time-histories of the ground motion in the N-S and E-W directions. As seen in the second-from-top plot, the peak ground acceleration is about 0.26 g along the E-W direction. The peak acceleration occurs about 20 seconds into the earthquake with considerable shaking beforehand. In the N-S direction, the maximum acceleration is about 0.17 g.  In order to study a broad spectrum of damage, the selected ground motion is also scaled. The two bottom plots in Figure 4.20 show the evolution of the repair cost and repair duration during the earthquake time-history for four different values of the scaling factor.  124 Focusing on the repair cost, the bottom-most graph in Figure 4.20, it is unsurprising that the cost accumulates rapidly during the first 25 seconds of the earthquake. The reason is seen in the acceleration time-history plots; the shaking is most severe during this time period. After the initial 25 seconds, the shaking subsides considerably while the repair cost continues to increase appreciably. This appears counter-intuitive because with a decrease in accelerations a drop in the accumulation of repair cost is expected. However, the building has suffered damage up to that point, with deteriorating stiffness as a result. Thus, even at low intensity shaking the damage continues to accumulate.  It is further observed in Figure 4.20 that the scaling of the ground motion have the greatest impact on the cost and duration during the initial period of shaking. Looking at the repair cost, the slope of the cost evolution curves is different during the first 20 seconds of shaking. Then, after the intense shaking has subsided, the repair cost and duration curves increase at similar rates, regardless of scaling factor. The repair duration, shown in the second graph from the bottom in Figure 4.20, is correlated with the repair cost. In fact, the majority of the repair cost comes from the cost of labour. This study exhibits a cost of labour that is generally 1.5 to 2 times that of the cost of materials. Thus, as the cost of repair increases, so does the time to complete the repairs. In summary, Figure 4.20 reveals that shaking intensity, earthquake duration, and damage in the initial portion of the ground motion are all important factors influencing the repair cost and duration.  125  Figure 4.20 Evolution of repair cost and duration during earthquake 0100,000200,000300,000400,000500,000600,000700,000800,000900,0000 10 20 30 40 50 60 70 80 90Repair Cost [$]Time [s]-0.30-0.20-0.100.000.100.200.300 10 20 30 40 50 60 70 80 90Acceleration [g]E-W Component-0.20-0.15-0.10-0.050.000.050.100.150.200 10 20 30 40 50 60 70 80 90Acceleration [g]N-S Component0501001502002503003504004500 10 20 30 40 50 60 70 80 90Repair Duration [Days]0100,000200,000300,000400,000500,000600,000700,000800,000900,0000 10 20 30 40 50 60 70 80 90Repair Cost [$]Time [s]1.51.00.50.2Ground Motion Scaling Factor  126 Figure 4.21 plots the repair cost and duration against the ground motion scaling factor. An inelastic dynamic analysis is conducted at several values of the ground motion scaling factor. The cost is on the left axis in Figure 4.21 and the duration on the right; the solid line represents the repair cost while the dashed line denotes the repair duration. Beyond a scaling factor of 1.8 the structural analysis did not converge, due to severe loss of lateral stiffness. After a scaling factor of about 1.4 the repair cost plateaus at about $850,000. At that point the structure is heavily damaged, and several components require replacement. Consequently, additional deformation does not result in an increase in repair costs.   Figure 4.21 Repair cost and duration at various ground motion scaling factors    It is also noted in Figure 4.21 that nearly half of the maximum repair cost occurs relatively early, at a scaling factor of about 0.2. After that point, an increase in the ground motion intensity results in a slower but nonetheless steady increase in the repair cost. 0501001502002503003504004500100,000200,000300,000400,000500,000600,000700,000800,000900,0000.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0Repair Duration [Days]Repair Cost [$]Ground Motion Scaling FactorCostDuration 127 Interestingly, the repair duration, shown as a dashed line in in Figure 4.21, follows a different trajectory. At low ground motion intensities, the repair duration does not increase at the same pace as the repair cost. Conversely, at high ground motion intensities the repair duration increases at a rate higher than the repair cost. Figure 4.22 illustrates the trend in repair cost versus the building storeys. At each building storey the individual component repair costs are summed up to provide a storey-level cost. For high ground motion intensity, represented by scaling factors 1.0 and 1.5, the repair cost follows a downward trend from the ground floor to the top storey. It is expected that the components closer to ground level will undergo more damage than those that are higher up in the building. Conversely, with lower intensity shaking the repair cost in the different storeys are comparable. Similar trends are observed in Figure 4.23 for labour-time. As with the repair cost, the longest labour-times occur at the buildings storeys that are closer to the ground.    128  Figure 4.22 Repair cost vs. building storey   Figure 4.23 Repair labour-time vs. building storey  020,00040,00060,00080,000100,000120,000140,000160,000180,000200,0001 2 3 4 5 6Repair Cost [$]Building Storey 0100,000200,000300,000400,000500,000600,000700,000800,000900,0000 10 20 30 40 50 60 70 80 90Repair Cost [$]Time [s]1.51.00.50.2Ground Motion Scaling Factor0100,000200,000300,000400,000500,000600,000700,000800,000900,0000 10 20 30 40 50 60 70 80 90Repair Cost [$]Time [s]1.51.00.50.20501001502002503003504004505001 2 3 4 5 6Labour-time [Worker-days]Building Storey 0100,000200,000300,000400,000500,000600,000700,000800,000900,0000 10 20 30 40 50 60 70 80 90Repair Cost [$]Time [s]1.51.00.50.2Ground Motion Scaling Factor  129 Figure 4.24 plots the individual component repair costs versus their maximum drift. It is observed that the costs are clustered around particular drift values. This is because components that are on the same storey will have similar drift values. Figure 4.24 shows that the largest costs do not necessarily correspond to the highest drift values. That is especially true for the larger scaling factors, i.e., the highest ground shaking intensity. Assuming that the lower drift values belong to building storeys that are closer to the ground, the results in Figure 4.24 agree with the results in Figure 4.22, where greater damage is observed near the bottom of the structure. These results highlight that it is not always appropriate to employ drift for repair cost estimation, as is common with drift-based fragility curves. The present study shows that the highest repair costs occur at the ground storey, while the highest drift occurs at the top storey. The bottom part of the building, which is fixed to the ground experiences the lowest drift, but higher strains and thus damage. Conversely, at the top storeys there is greater drift, but less damage.    130  Figure 4.24 Component repair cost vs. storey drift ratio  Another observation in Figure 4.24 is that the dispersion in cost values increases with ground motion intensity. Larger scaling factors result in a wider spread of drift values across the storeys, resulting in more varied damage along the height of the building. The opposite is true for lower shaking intensities; the drift values are closer together and the costs are less dispersed.   The individual component repair labour-times are provided in Figure 4.25 for the storey drift values of the considered building. As before, the repair labour-times closely parallel the repair cost. Those components with larger repair costs will also require more labour-time to complete the repair. Also, similar to the component repair cost, the dispersion in repair duration increases with the scaling factor.  05,00010,00015,00020,00025,0000 0.005 0.01 0.015 0.02 0.025Repair Cost [$]Inter-storey Drift Ratio [rad]Ground Motion Scaling Factor 05,00010,00015,00020,00025,0000 0.005 0.01 0.015 0.02 0.025Repair Cost [$]Inter-storey Drift Ratio [rad]1.5 1.00.5 0.2 131  Figure 4.25 Component repair duration vs. storey drift ratio  The models that are employed to obtain the results presented above are given in Figure 4.26. The arrows show the flow of responses between the interacting models. In the top-left corner of the figure, a scaled ground motion model scales a given ground motion time-history, th, by a scaling factor. The scaled time-history is then fed into a structural analysis model, which conducts the structural analysis and outputs finite element responses, u. The visual damage model takes the finite element responses and evaluates the visual damage, VD. The visual damage is subsequently used by the damage repair model, in the top-right of Figure 4.26, to select repair actions. In the damage repair model, the repair actions are used to calculate the repair cost, $, repair duration, t, labour requirements, L, and equipment needs, Eq. As shown by a diamond symbol, which represents aggregation, the damage repair model contains CSI knowledge, or sets of repair actions with CSI codes. 010203040506070800 0.005 0.01 0.015 0.02 0.025Labour-time [Worker-days]Inter-storey Drift Ratio [rad]Ground Motion Scaling Factor 05,00010,00015,00020,00025,0000 0.005 0.01 0.015 0.02 0.025Repair Cost [$]Inter-storey Drift Ratio [rad]1.5 1.00.5 0.2 132 Likewise, the structural analysis model in the figure contains structural analysis methods, and building information knowledge with components, finite elements, and a damage mesh.   Figure 4.26 Analysis framework and class map The triangle symbol under the structural analysis method denotes inheritance. The inelastic dynamic structural analysis is employed for the scaled ground motion analyses of the considered building. Another type of structural analysis method, inelastic static structural analysis, is used in the pushover analyses.  4.8 Visualizing Damage on the Computer Visualization of damage on a BIM is useful for several reasons: 1) model validation; 2) repair contractors can review computer renders of damage to provide input on repair methodologies and for “virtual” repair estimates; 3) communicating the risks of earthquake damage to stakeholders who may otherwise not understand engineering results (Bernhardt et al., 2019); and 4) to decide inspection or repair priority of a suite of structures post-earthquake, i.e., assign degrees of urgency for inspection without any knowledge of the on-site damage.  The basic approach of visualizing damage, adopted by Christodoulou et al. (2010), involves coloring the damaged regions to set them apart from the undamaged structure. Similarly, previous implementations in Rts (Javaherian Yazdi, 2015) used colors to highlight Scaled Ground Motion ModelthStructural Analysis Model   u Damage Repair Model$, t, L, EqVisual Damage Model VDInelastic Dynamic Structural AnalysisStructural Analysis MethodComponentBIM KnowledgeFinite Element Mesh Damage MeshElementsNodesMaterialsSectionsVisual Damage ContainersInelastic Static Structural AnalysisCSI  KnowledgeRepair Action CSI Codes 133 damaged areas of reinforced concrete columns and shear walls. In a more advanced approach, Anil et al. (2015; 2016) use pictures and hand-sketches to visualize existing earthquake damage onto a BIM. Their approach uses actual post-earthquake damage to generate an “as-damaged” BIM that can later be used for engineering analyses. To the author’s knowledge, no previous study uses finite element responses to visualize damage on a BIM in real-time. Figure 4.27 illustrates the visual damage on a reinforced concrete elevator core following an earthquake ground motion. The finite element model of the elevator core is shown on the left of Figure 4.27, consisting of nonlinear layered shell elements described earlier. The graphic in the middle of the figure shows the damage mesh after the earthquake has occurred; with the damaged areas colored and the undamaged areas in grey. Yellow signifies cracking, green cover spalling, and blue complete cover loss. The graphic on the right of the figure shows the visual damage mesh rendered onto a three-dimensional BIM model of the elevator core.   134  Figure 4.27 Finite element model (left) and visual damage (middle and right) of a reinforced concrete elevator core following an earthquake  Figure 4.28 illustrates the visual damage of the building from Figure 4.17 following the considered earthquake. The graphic on the left of the figure highlights the damage on the deformed finite element model, while the graphic on the right shows the visual damage on the deformed BIM of the structure.    135  Figure 4.28 Visual damage of the considered building following an earthquake  These renders are updated dynamically, in that the visualization of damage is shown over time, i.e., progression of damage during an earthquake. To a layman, a render of earthquake damage, e.g., the graphic on the far-right of Figure 4.27, or the bottom graphic in Figure 4.28, communicates earthquake risks more effectively than a verbal or written description.   136 4.9 Conclusions A methodology for seismic loss estimation is presented with new models for visual damage in reinforced concrete components. Estimates for cost and duration of repairs are obtained by predicting the tasks needed to complete the repairs. The tasks are formulated as MasterFormat CSI codes, which catalogue the material, labour, and equipment requirements of the repair work. In conjunction with information-rich finite element models imported from BIM the presented methodology yields damage and repair estimates with an unprecedented level of detail. With this tool it is possible to gain new insights into earthquake damage and subsequent repairs. For example, it is demonstrated in this research that inter-storey drift ratio may not be a precise predictor for the cost of repairs. The work presented in this dissertation extends previous research conducted at the University of British Columbia in Vancouver, including the creation of a computer program for seismic loss predictions (Haukaas, Talachian, & Elwood, 2010; Javaherian Yazdi, 2015; Mahsuli & Haukaas, 2013a). Potential future work to complement this research includes the development of additional visual damage models and repair actions for an array of structural and non-structural components. Another direction of future research is the improvement of repair actions to address collateral work, e.g., finishing removal, utility relocation, and re-installation. Further insights and generalization of the results presented here would be gained by investigating both low-rise and high-rise buildings, in conjunction with a broader spectrum of ground motions.   137 Chapter 5: Environmental and Human Health Impacts of Earthquake Damage 5.1 Introduction  This chapter presents a detailed account of the environmental and human health impacts of damage caused by earthquakes. Adopting the vision that computer simulations of structural behavior will include a wide range of concerns, the goal is to expand our understanding of how earthquakes affect the environment. This vision represents an extension of performance-based earthquake engineering initiatives aimed at predicting direct and indirect costs of earthquake damage.   A key short-term objective in this chapter is to create new and detailed results for a specific building that is representative of a large building stock. Studies are therefore conducted on the case study building subjected to a damaging earthquake. The new results for environmental and human health impacts are compared with existing predictions and guidelines. It is also an objective to compare the performance of wood, steel, and concrete options for the load-bearing system.   The primary motivation behind this study is to improve the understanding of the impacts of earthquake damage. If the negative impacts of earthquake damage are comprehensively modeled, it may justify an increase in seismic safety levels when structures are designed and retrofitted. The desire to have broad impact motivated the selection of the six-storey building, which is a common building type for new construction in the Vancouver region in Canada and elsewhere.   The scope of this study focuses on the structural system, rather than non-structural components. It is assumed that the building is repaired after damage; building demolition and  138 reconstruction are not considered. However, the considered repairs include the possibility of replacement of entire components, such as slabs and columns. Detailed repair actions are developed for the reinforced concrete components, but not for wood and steel components. For that reason, those components are not repaired when substantial damage occurs; they are replaced. Finally, in terms of scope, calculation of emissions from the manufacturing of materials needed for repairs is made with no consideration of reduction in emissions from the reuse of recycled material.  The analyses in this chapter build upon the models for visual damage and corresponding repair actions presented in Chapter 4. That chapter develops the methodology to predict detailed damage, but omits the consideration of environmental and human health impacts. The models for those impacts in material manufacturing and construction are presented in Chapter 3. However, a scalar ground motion intensity measure and fragility functions were employed in Chapter 3 to address the cost of earthquakes. The present study develops a methodology that includes ground motion records, prediction of visual damage, such as cracking and spalling of concrete, prediction of repair quantities based on realistic repair actions, and prediction of environmental and human health impacts.  In recent literature, efforts have been made to broaden the scope of the concerns addressed in the repair of earthquake-damaged buildings. Initial efforts utilized a building damage ratio, i.e., the ratio of the repair cost to the building replacement value, to calculate environmental impacts. For instance, the paper by Feese et al. (2015) studied the repair cost and energy needed for the repair of damage. In their paper, the energy expended during repair is estimated by multiplying the building damage ratio with the energy used during the initial construction of the building. They employed the HAZUS-MH methodology, which  139 uses fragility functions to calculate the repair cost of a building. The Athena computer program was used to estimate the energy consumed during initial building construction. In contrast, this work employs a visual damage-based approach to explicitly predict the damage to building components. Detailed repair quantities are calculated from the visual damage, allowing for a direct calculation of environmental impacts from actual quantities of material. The study by Padgett and Li (2016) extends the breadth of concerns to consider both embodied energy and carbon from repair. In addition, they consider the repair cost, downtime, and cost of casualties. Fragility functions are also used in their paper to predict the cost of repair, and the environmental impacts are again calculated using a damage ratio and whole-building results from Athena. In this dissertation, the aforementioned visual damage models provide exact quantities of material, labour, and equipment, which is used to estimate a broad array of emissions. The study of a building by Menna et al. (2013) addresses climate change, human health, ecosystem quality, and resource depletion impacts from the Impact 2002+ methodology. They also employ fragility functions for evaluating damage, where the amount of materials for repair is computed as a percentage in weight of the quantities of material from initial construction. Although their study is comprehensive, building-wide emissions estimates using a damage-ratio approach are approximate in nature. Conversely, the approach presented in this dissertation considers damage at the component level. In this study, the detailed repair quantities provided by the visual damage models are employed in the calculation of repair cost, downtime, and emissions. The emissions accounted for in this dissertation are from material manufacturing and from worker and material transportation to site.  140  Narrowing the focus from building-level damage to component-level damage culminated in the FEMA P-58 seismic performance assessment of buildings method (FEMA, 2018). The FEMA P-58 methodology employs fragility functions to predict the damage state of a building component, e.g., light, moderate, or heavy damage. In the Performance Assessment Calculation Tool (PACT), developed by FEMA (2019), the repair cost, carbon emissions, and embodied energy are provided for each damage state. Provided the inter-storey drift of a component, the fragility functions conveniently provide the damage state of the component and the repair cost, emissions, and energy. The PACT tool is employed in a study by Huang and Simonen (2020) to address carbon emissions from the repair of several buildings with different types of lateral force-resisting systems. However, their study uses simplified building models, unlike the detailed model employed here.   A limitation of the PACT approach is that it does not provide repair material quantities.  This makes it difficult to perform the type of lifecycle-based environmental assessment that is employed in this dissertation. Several studies address this limitation by estimating the material quantities associated with the repair activities of a damage state. For example, the paper by Chhabra et al. (2018) employs fragility functions and damage states from the FEMA PACT tool to predict building damage. However, they do not use the PACT tool to calculate emissions. Repair material quantities are specified for each damage state, and the TRACI methodology is used to assess the environmental impacts from repair. Results from their study are based on a two-dimensional frame subjected to an earthquake ground motion. Conversely, a detailed building model used in the current work. The study by Anwar et al. (2019) employs a detailed model, considering repair cost, downtime, and carbon emissions. However, they also employ a fragility-based approach where they estimate the  141 quantity of material associated with a particular damage state to calculate emissions. In contrast to the above-mentioned fragility-based approaches, the current work does not rely on repair material estimates from damage states. Based on the aforementioned visual damage models, exact repair quantities are employed in this dissertation to calculate the environmental impacts.   The study by Gencturk et al. (2016) considers repair cost, downtime, casualties, and environmental emissions of a two-dimensional plane reinforced concrete frame. Similar to the other studies in the literature, they use fragility functions to estimate the damage state of the structural components. Also paralleling the previous studies, environmental impacts are calculated through material quantities that are associated with particular damage states, using the TRACI methodology in their lifecycle assessments. However, they go a step further in that the final results of their environmental assessment are amalgamated into an “environmental performance score.” In this dissertation, the impacts of emissions on human health are also explicitly considered, in addition to the environment, and all impacts are translated into a well-understood monetary cost.  Presenting results in the form of a monetary cost follows traditions in performance-based earthquake engineering, where all concerns are translated into a cost in dollars. The study by Arroyo et al. (2015) considers environmental costs in seismic loss estimation. They calculate both repair and environmental costs through the previously mentioned building damage ratio approach. However, their study focuses solely on carbon emissions, utilizing a carbon-tax to translate carbon emissions into a cost. In contrast, this study adopts maxims from lifecycle costing, translating all environmental concerns into a cost. Costs are presented  142 for each emission and impact individually, allowing for the comparison of costs between emissions.  In this chapter, visual damage is predicted in building components, from which exact repair quantities are calculated. From these repair quantities, a lifecycle analysis is performed to calculate the cost of damage to human health and the environment. Described in the next section, the ReCiPe2016 methodology is employed in the lifecycle analysis. The contribution of this chapter is new insights from the results of the case study building subjected to an earthquake ground motion.  5.2 Methodology The methodology employed in this chapter builds upon detailed finite element models of buildings, created from Building Information Models in Chapter 2. The models are subjected to ground motion records, and the visual damage, such as cracking and spalling, is predicted during the ground shaking. Based on the visual damage, a detailed set of repair actions, referred to by CSI codes, is selected, as described in Chapter 4. With that information, exact material quantities and labour hours are obtained. Those quantities are required by the type of environmental lifecycle assessment presented in this study. The left-hand side of Figure 5.1 shows that the aforementioned information is required for the next steps, i.e., the prediction of impacts of emissions. The emissions cause two impacts: As shown in the right-hand side of Figure 5.1, the prediction of emissions facilitates the calculation of 1) the cost of environmental damage, such as climate change, and 2) the cost of damage to human health, such as respiratory diseases.  143  Figure 5.1 Methodology  As described in Chapter 3, the emissions from material manufacturing, and their associated impacts, are calculated with the OpenLCA computer program (Ciroth, 2007). These calculations are based on data from the ecoinvent database (Wernet et al., 2016), which contains information associated with the extraction, processing, and manufacturing of materials. The material manufacturing process is often complex, resulting in an intractable number of emissions. Instead of addressing the individual impacts of each emission, the ReCiPe2016 method (Huijbregts et al., 2017) is employed to combine the impacts of many emissions into a more manageable set of “impact categories.”   Apart from the emissions from the manufacturing of repair material, emissions are also calculated for the transportation of repair material and workers to site. These emissions stem from the energy consumed during transport, e.g., gasoline and diesel, and they depend on the energy consumption mode, heavy-duty truck, medium-duty truck, etc. The quantity of energy consumed, emissions from energy consumption, and the cost of energy used is calculated utilizing models from Chapter 3.  For the material manufacturing stage, i.e., before a repair starts, both emissions and the ReCiPe2016 impact categories are calculated. The cost of environmental damage is calculated from the ReCiPe2016 impact categories with costs provided by Bijleveld et al. (2018a). However, it is assumed that the cost of damage to human health is not included in Activities related to repairsManufacturing of materialsTransportation of materialsTransportation of workersEmissionsCarbon dioxide (CO2)Methane (CH4)Nitrous oxide (N2O)Hydrofluorocarbon (HFC-134a)Black carbon (BC)Sulphur dioxide (SO2)Carbon monoxide (CO)Organic carbon (OC)Nitrogen oxides (NOx)Ammonia (NH3)Environmental impactsClimate changeOzone depletionEtc. $Human health impactsRespiratory diseasesSkin cancerEtc.Visual damageCrackingSpallingEct. 144 these costs. Thus, the human health costs are calculated from the ten emissions shown in Figure 5.1, utilizing the cost values provided by Shindell (2015). During the repair, i.e., after the material manufacturing stage, emissions are estimated for material and worker transport to site. Again, Shindell is employed to calculate the human health costs, while the environmental costs are calculated with values from Bijleveld et al. (2018b).  5.3 Study of a Shear Wall To compare emissions values from proposed approach with those provided by the aforementioned FEMA P-58 methodology, the “B1044.092 shear wall” from the PACT tool is subjected to a pushover analysis in Rts. The shear wall is 0.305 m thick, 3.658 m high, and 6.096 m long, which are the dimensions of the default 12”x12’x20’ wall in the PACT tool. Using a nonlinear static pushover analysis, the CO2 emissions associated with repairs are plotted with respect to the wall drift ratio.  The PACT tool relies on fragility functions to estimate the damage state of a component. The CO2 emissions from repair, EFEMA, in kg, are calculated using the fragility functions and the theorem of total probability (FEMA, 2018):   (65) where DS=discrete random variable representing the damage state, ds∈{1,2,3}=realizations of DS, f=drift ratio, and Eds=CO2 emissions associated with damage state ds. Utilizing fragility functions, the probability of a particular damage state is    (66) EFEMA = P(DS = ds φ) ⋅Edsds=13∑P(DS = ds φ) = P(DS > ds φ)− P(DS > ds+1φ) 145 The PACT tool employs a standard 12’x12’=144 sqft wall panel as a reference entity. For that wall panel, which has area 13.378 m2, the values provided by the FEMA P-58 guidelines for the CO2 emissions are 1472 kg for ds=1, 6780 kg for ds=2, and 7913 kg for ds=3.   The comparison between the proposed approach and the FEMA approach is shown in Figure 5.2. The FEMA emissions curve is calculated with Eq. (65), and it includes collateral work, e.g., finish removal and replacement, scaffolding, relocation of utilities, debris removal. Conversely, the approach proposed in this study considers the structural repair of the wall, with no allowance made for collateral work. To facilitate the comparison, Figure 5.2 is plotted against two vertical axes, with the emissions from the proposed approach on the left, and the FEMA emissions on the right.   Figure 5.2 CO2 from repair of reinforced concrete shear wall (notice two vertical axes with different scales) 01,0002,0003,0004,0005,0006,0007,0008,0009,00005001,0001,5002,0002,5003,0003,5004,0000 0.01 0.02 0.03 0.04 0.05 0.06FEMA CO2[kg]Proposed CO2[kg]Drift Ratio [rad]ProposedFEMA 146 It is seen in Figure 5.2 that the dashed FEMA curve and the proposed solid curve follow similar trends. For example, is observed that both curves begin their increase and then ultimately plateau at similar drift values. For the proposed approach, the initial rise in CO2 levels is from epoxy crack grouting and spalling repair. At a drift of about 1%, the first plateau occurs when cover replacement becomes the preferred repair action over smaller sporadic repairs. The final plateau occurs at a drift of 3%, i.e., when component replacement is the repair action. A direct comparison of CO2 emission values is not possible because one approach includes collateral work, while the other does not. 5.4 Study of a Six-storey Building The proposed approach is applied to the six-storey case study building in order to gain insights into the sustainability of earthquake damage repair. The top of Figure 5.3 shows a computer rendering of the building. A summary of the case study building, described in detail in Section 1.6, is provided here. The building is located in Vancouver Canada, but it has not yet been built. The building has 1,041 m2 of commercial area on the ground floor and five equally sized residential floors above with 40 residential units. The building also contains 6 slabs, 156 columns, 616 non-load-bearing walls, 165 exterior walls, 60 shear walls, 356 windows, 171 m2 of window area, and 22.5 m total height. In addition, the building has a reinforced concrete shear wall in the center that is intended to carry lateral load on the building and serve as elevator shaft.  For the columns and slabs, three material options are analyzed for the structural system: 1) A wood option with glue-laminated timber columns and cross-laminated timber floor slabs; 2) A steel option with wide-flange columns and composite floor slabs with steel decking and lightweight concrete topping; and 3) A concrete option with reinforced concrete  147 columns and slabs. The column and slab members were sized so that similar building drift ratios are observed with all three options. All material options have the same reinforced concrete shear wall mentioned above, serving as lateral force resisting system.  Figure 5.3 Computer rendering of the building BIM (top) and finite element model (bottom)  The bottom of Figure 5.3 shows a screenshot from Rts of the finite element model of the building. The current work integrates OpenSees (McKenna et al., 2010) for the structural analysis methods, linear equation solvers, and finite element objects such as elements, cross-sections, and materials. Details of the nonlinear finite element modelling approach employed here are described in Section 4.3. Section 4.3 also provides the material models and their  148 parameters for the concrete and steel options. The material model for the wood option is introduced for the first time in this chapter. A material model proposed by Bazan (1980) is utilized for the wood material option, whose stress-strain relationship is provided in Figure 5.4.  Figure 5.4 Wood material model stress-strain backbone The wood model is implemented in the current work with the generic bilinear material model from OpenSees. The various symbols shown in Figure 5.4, e.g., Ew, fcw, correspond to the wood material model parameters, whose values are given in Table 5.1. The parameter values shown in the table are taken from Lindyberg and Dagher (2012). Table 5.1 Material model parameters Material Parameter Description Value ecw Strain at fcw  Stress [MPa]Strain [mm/mm]Wood Material Modelm·EwftwfcwεtwuεcwufcwEw 149 etw Strain at ftw  m Ratio between post-compressive failure tangent and initial elastic tangent -0.001 Random Variables Material Parameter Description Mean Value Coefficient of Variation fcw Ultimate compressive strength of glulam parallel to grain 41.64 MPa 0.10 ftw Ultimate tensile Strength of glulam parallel to grain 25.44 MPa 0.10 Ew Modulus of elasticity of glulam 10,620 MPa 0.15 rw Glulam mass density 600 kg/m3 0.10 nw Glulam Poission’s ratio 0.25 0.05  The building is subjected to a damaging earthquake ground motion to simulate a scenario relevant to the building site. The ground motion was recorded at the Olympia Highway Test Laboratory during the 1949 M7.1 Olympia, Washington earthquake. The full 3D ground motion is utilized, characterized by a 0.26 g peak ground acceleration, occurring after about 20 seconds with significant shaking beforehand, and a 0.16 g maximum acceleration in the perpendicular direction. The maximum vertical acceleration is 0.09 g.  Before getting into the detailed results related to human health and environmental impacts, Figure 5.5 shows a breakdown of all the costs related to earthquake damage. These include the direct cost of repairs, emissions from repair, downtime, and human casualties directly due to damage, i.e., injuries and deaths. The calculation of the cost of downtime and human casualties is explained in Chapter 3. The methodology employed to calculate the cost of material and labour is provided in Chapter 4. It is observed in Figure 5.5 that the concrete material option results in the largest total cost. Specifically, the cost of casualties governs, as shown by the red boxes in the figure. The cost of casualties for the wood material option is ftwEw 150 substantially lower than the costs from steel and concrete. This is due to the building drift values provided by HAZUS for the fragility functions that are employed to calculate damage to the building, and henceforth casualties. It is seen in Table 3.15 that the median drift values for a particular damage state are considerably higher for the wood building than for steel and concrete. Casualties, especially deaths, occur when a building is in the severe or extensive damage states, which occur at lower drift values for the steel and concrete structures.  Figure 5.5 Breakdown of earthquake costs Figure 5.5 also shows that wood results in the lowest overall earthquake costs, mostly due to the low costs associated with emissions and casualties. Focusing on the direct costs of material and labour, it is seen in Figure 5.5 that the steel option becomes the preferred choice. This is due to the high cost of labour associated with the concrete material option, 99,086 38,302 108,862222,676 472,114 331,784417,969193,656 84,7291,625,67064,2741,492,660217,036223,375208,2190500,0001,000,0001,500,0002,000,0002,500,0003,000,000Concrete Wood SteelCost [$]Emissions Materials Labour Casualties Downtime 151 and the high cost of materials for the wood option. Concrete has the highest costs of labour because the repair actions for concrete are more labour intensive than for steel and wood. Concrete repair actions include formwork installation, concrete placing, surface finishing, form stripping, etc. For the wood and steel options, detailed repair models are not yet available. Thus, when damage occurs, the damaged component is removed and replaced, which results in a low cost of labour and a high cost of materials.   Not shown in Figure 5.5, the cost of emissions from energy consumed in worker and material transport to site is comparatively small. It was found that the emissions from energy usage contributed to about 3-5% of the total emissions cost. It is also seen in Figure 5.5  that the downtime costs are similar for all three material options. This is because the repair times are similar for all three material options; calculated as 114, 117, and 109 days for the concrete, wood, and steel options, respectively.   The breakdown of emissions costs for the three materials is provided in Figure 5.6. It is seen in the figure that the costs associated with steel supersede the others for every emission except carbon dioxide. The concrete material option results in the greatest cost of carbon dioxide emissions. The five emissions that are the largest contributors to the steel costs are: 1) human toxicity; 2) sulfur dioxide; 3) black carbon particulate matter; 4) particulate matter formation; and 5) nitrogen oxides. These five emissions account for 86% of the total emissions cost for steel. The cost of damage to human health, i.e., the cost of the ten emissions listed in Figure 5.1, accounts for about 75%, 65%, and 50% of the total cost of emissions for the concrete, wood, and steel options, respectively.  152  Figure 5.6 Cost of emissions for earthquake damage repair Figure 5.7 shows how the cost of emissions accumulates during the earthquake ground motion time-history. It is seen that the wood option results in the lowest overall cost of emissions, while the steel option results in the highest. The cost of emissions for concrete and steel are comparable before the largest shock occurs at around 20 seconds, after which the steel cost appreciates rapidly. It is observed in Figure 5.7 that the cost accumulates at the greatest rate during the first 40 seconds of the earthquake for all three material options. This is understandable since most of the damage occurs during this initial period of heavy shaking, as seen in the acceleration time-histories at the top of Figure 5.7. Another observation in Figure 5.7 is that the costs from wood and concrete accumulate relatively smoothly, while there are distinct jumps in the cost from steel. These jumps occur when multiple steel columns yield in succession.  0 10,00020,00030,00040,00050,00060,000Ammonia EmissionsBlack Carbon PM EmissionsCarbon Dioxide EmissionsCarbon Monoxide EmissionsHFC134a EmissionsMethane EmissionsNitrogen Oxides EmissionsNitrous Oxide EmissionsClimate ChangeFreshwater EcotoxicityFreshwater EutrophicationHuman ToxicityIonising RadiationMarine EcotoxicityMarine EutrophicationOzone DepletionParticulate Matter FormationPhotochemical OxidantTerrestrial AcidificationTerrestrial EcotoxicityUrbanLand OccupationOrganic Carbon EmissionsSulfur Dioxide EmissionsCost [$]SteelWoodConcrete 153  Figure 5.7 Evolution of the emissions cost along the earthquake duration -0.30-0.20-0.100.000.100.200.300 10 20 30 40 50 60 70 80 90Acceleration [g]E-W Component-0.20-0.15-0.10-0.050.000.050.100.150.200 10 20 30 40 50 60 70 80 90Acceleration [g]N-S Component020,00040,00060,00080,000100,000120,0000 10 20 30 40 50 60 70 80 90Cost of Emissions [$]Earthquake Duration [s]SteelConcreteWood 154 To examine the impact of the earthquake intensity on the cost of emissions, the ground motion is scaled from 0 to 2 times its original intensity. Figure 5.8 provides the cost of emissions against the ground motion scaling factor. At the largest scaling factor of 2, the wood option results in the lowest cost, followed by concrete, and then steel. It is further observed in Figure 5.8 that below a scaling factor of 1, steel results in lower emissions costs than concrete, and is comparable to wood up until a scaling factor of 0.6. After a scaling factor of 1, the cost of emissions from steel increases rapidly, and the highest cost is over double that of concrete. One reason for this is that the damage and repair models implemented in this study replace the entire steel column once yielding occurs. It is also revealed in Figure 5.8 that the cost of emissions of the wood option is least impacted by the intensity of the ground motion. In proportion to the scaling factor the increase in cost is approximately constant, with about half of the maximum cost occurring at a scaling factor of 0.8. It is seen in Figure 5.8 that the cost of emissions of the steel option is the most sensitive to increases in the ground motion intensity.  155  Figure 5.8 Cost of emissions at various ground motion scaling factors Figure 5.9 plots the cost of emissions against the peak inter-storey drift ratio recorded during the time-history analyses from Figure 5.8, i.e., the peak inter-storey drift recorded at each scaling factor. It is seen in the figure that steel results in the lowest costs up to a drift of 2.3%. At drift values above 3%, the costs of the steel option increase substantially as more columns begin to yield. At the highest drift levels, the wood option results in the lowest cost of emissions. It is found that the steel option is the most sensitive to the stiffness of the floor slab. Higher slab stiffness values cause the steel columns to yield earlier, which results in an increase in cost.  050,000100,000150,000200,000250,000300,0000.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0Cost of Emissions  [$]Ground Motion Scaling FactorSteelConcreteWood 156  Figure 5.9 Cost of emissions vs. the peak inter-storey drift ratio 5.5 Conclusions A key contribution of this chapter is richer results for environmental and human health costs associated with the repair of damage due to earthquakes. A more complete assessment allows for additional insights into the impacts of repairs after earthquakes. Starting with detailed repair quantities from visual damaged-based models, a broad range of emissions are considered in this dissertation. These emissions are used to calculate the cost of environmental damage, and the cost of damage to human health. In addition, the costs of materials and labour associated with repairs, earthquake casualties, and downtime are considered. 050,000100,000150,000200,000250,000300,0000 0.01 0.02 0.03 0.04Cost of Emissions [$]Peak Inter-storey Drift RatioSteelConcreteWood 157 A case study is presented of a shear wall from the FEMA PACT tool. It is found that the carbon dioxide emissions from the FEMA PACT tool follow similar trends as the emissions calculated with the approach proposed in this dissertation. Next, a real-world six-storey building is subjected to a damaging earthquake ground motion. Wood, steel, and concrete material options are compared for the structural system. Overall, the wood option results in the lowest earthquake costs, including the lowest costs of emissions. The concrete option results in the highest casualties, while the emission-related costs are the greatest for steel.  This work considers only the damage and repair of the structural system. Potential future work includes the assessment of impacts from collateral repair work, e.g., finishing removal, utility relocation, and re-installation. Moreover, the inclusion of the repair of non-structural components is needed for more complete results. Another direction of future research is to implement additional lifecycle impact assessment methodologies, e.g., TRACI and CML, to compare results with the ReCiPe2016 methodology that is used in this work. Currently, detailed repair actions are not available for the wood and steel components, which is another consideration for future work.    158 Chapter 6: Conclusions 6.1 Overview of Research and Contributions In Chapter 2, information-rich building components are developed, with both finite elements and information required for lifecycle analysis. IFC import algorithms are implemented to extract useful BIM information, such as material and geometry, that is used to create the components. Next, a finite element model is generated from the components. Procedures are developed to establish connectivity between components and their finite elements, to create a functional structural model. To demonstrate the BIM import and component creation algorithms, an input file of a structural model is generated for the computer program OpenSees. The components created from BIM contain many random variables, e.g., material parameters, which may require correlation. Without building-wide statistical data, which may be difficult to acquire, correlation coefficients are specified using expert judgement. Unfortunately, it is easy to specify invalid correlations that cannot be used in an analysis. To remedy this problem, a valid correlation structure is created for correlating random variables within and between components.  Chapter 3 introduces detailed building models for lifecycle analysis. Models are developed for the material manufacturing, construction, operations, damage and repair, and demolition phases of a building. For the manufacturing, construction, and demolition phases, “actions” are described that use MasterFormat CSI codes to enumerate the material, labour and equipment requirements of each phase. Lists of these CSI-based actions are used in conjunction with the RSMeans database to calculate the costs, time, labour, and equipment of an action. Chapter 3 also presents a host of models that are implemented in this work to  159 translate lifecycle impacts into direct and indirect costs. The sum of these costs gives the total lifecycle cost of a building.  In Chapter 3, a comprehensive lifecycle analysis is performed for the case study building. Concrete, steel, and wood material options are considered for the structural system. A simplified structural model is used, covering all hazard combinations in the region. Many building lifetime scenarios are sampled, and the total lifecycle cost for each material option is compared. For the selected building dimensions and choice of structural members, the analyses found that the largest contributors to the lifecycle cost are from operational emissions. This is followed by the cost of environmental and human health impacts from material manufacturing. Also, it was found that the earthquake-related costs account for about 4% of the total lifecycle cost. Although the mean costs are low, when large earthquakes occur, the worst-case casualty and repair costs can exceed the value of the building. The wood building is the most economical to repair when damage occurs, but it gets damaged more often. Overall, it is found that steel has the lowest repair cost. In the context of life safety, the greatest number of casualties occurred in the concrete structure, while the least in the wood structure.  In Chapter 4, a methodology for the detailed seismic loss estimation of buildings is developed. Models that predict visual damage from finite element responses are implemented. A collection of repair actions is described, addressing the anticipated types of visual damage. As in the construction and demolition phases, MasterFormat CSI codes are used to catalogue the material, labour, and equipment requirements of repairs. From the CSI codes, more complete estimates of the cost and time of repair are obtained from RSMeans. The proposed methodology is compared to the existing FEMA P-58 approach for a shear  160 wall component. Next, comprehensive analyses are conducted on the case study building, using a detailed finite element model of the structure. In order to investigate the effects of damage repair over a wide range of deformations, nonlinear static pushover analyses are conducted. Next, to demonstrate the proposed approach in a more realistic earthquake scenario, the building is subjected to a damaging earthquake ground motion. The ground motion is scaled to determine the effects of acceleration intensity on the repair cost and repair duration. It is found that the ground motion acceleration level, earthquake duration, and initial damage from the early shock are all important factors that influence the repair cost and repair duration. Additionally, it was discovered that the commonly used inter-storey drift ratio may yield inaccurate estimates of damage to structural components.  Chapter 5 combines the models and methods from the previous chapters to perform an environmental analysis on the case study building; employing a finite element model and an earthquake ground motion. First, a finite element model of the building is generated by the BIM import algorithms from Chapter 2. Next, the environmental and human health costs are assessed with the models described in Chapter 3, using the detailed material and labour quantities from the models from Chapter 4. For a particular ground motion, the wood option results in the lowest earthquake costs considering the cost of casualties, emissions, and repair costs. The concrete option results in the highest casualties, while the emission-related costs are the greatest for steel.    161 6.2 Limitations and Future Research Directions A limitation of this research is that the results are centred around the case study building. Further investigations should include different building layouts, and both low-rise and tall buildings to generalize the results. Moreover, validation needs to be performed on a real-world structure that has suffered earthquake damage and then repaired. Another limitation is that the focus is on the structural components of a building. One of the main directions of future research is to develop damage models and repair actions for non-structural components. It is well-known that the cost of repair of non-structural components can be magnitudes higher than structural components. Still, the damage to non-structural components is a consequence of the structural performance. It would not be worthwhile to focus on non-structural components without detailed modelling of the structural system. Another limitation is that this dissertation does not include maintenance or structural degradation in the lifecycle analyses. It is assumed that the initial structural conditions remain constant throughout the life of a building. Concrete and steel structures are particularly susceptible to degradation in harsh environments, and wood structures may require periodic maintenance to avoid decay. Future work should address the gradual reduction and periodic maintenance of structural condition over time. Another limitation is that this work does not consider structural retrofits of existing buildings, only new construction. In the case where a potential land development has an existing building, it may be more worthwhile to perform a retrofit than to demolish and build a new building.   In regard to Chapter 2, BIM import algorithms are presented for several common solid geometry representations. Future work should consider the development of algorithms for the import of other, less-frequently occurring geometry representations. Moreover, the  162 BIM import framework may not be able to import unique and complex component geometries other than those used in the current work. Additional BIM examples are needed to validate the generalizability of the import framework. During BIM import, components are created that contain many random variables, for which a correlation structure is implemented. However, there are also random variables that are created at the building level, e.g., the cost of labour, or the emissions from energy usage, that may require correlation. Moreover, the autocorrelation of random variables that are periodically sampled over time, e.g., the monthly cost of electricity, is another subject of future work.   Chapter 4 presents detailed visual damage and repair models for concrete, steel, and wood components. Future work should extend the component library to include other components and other materials. The damage models that are implemented in this research address common failure modes. Nevertheless, some components have special failure modes that need addressing, e.g., punching shear in slabs, sudden shear failure in columns, that are not considered here. Another major direction of future research is to develop repair actions for collateral work repair work, e.g., finishing removal and replacement, and utility relocation. Components that are slightly damaged, requiring minimal repair to the structure, may still require expensive collateral work to perform the repair. It may be more advantageous to make a component slightly stronger than to perform small repairs with a high cost of collateral work.  In Chapters 3 and 5, lifecycle analyses are performed on the case study building. Wood, steel, and concrete material options are considered for the columns and slabs. Future work should examine other construction materials and structural configurations, moment frame, infill frame, etc. In this research, the environmental impacts were assessed using the  163 ReCiPe2016 methodology. Further investigations should compare the ReCiPe2016 methodology to other methods (TRACI, Ecoindicator, etc.) for calculating environmental impacts. Additionally, a sensitivity analysis is warranted to examine which impacts are the largest contributors to the lifecycle cost.   164 References Adams, J., & Halchuk, S. (2003). 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The file is the result of the “BIM import algorithms” implemented in this work. That means the IFC file for the building information model exported from the program ArchiCAD is translated into the OpenSees file shown below. Due to the large number of objects, the entire input file is not shown. Where there are many repetitions of nodes, elements, sections, etc., lines have been removed for brevity.   ### 3-D model with all units in N, m, kg ###  ### Nodes ###  node 522 119.940049 1.181728 4.876800 node 524 157.938449 1.181728 4.876800 node 526 157.938449 33.338128 4.876800 ⋮ <lines removed here for brevity> ⋮ node 44997 136.408618 19.831577 22.402800 node 44998 136.408618 19.449097 22.402800 node 44999 136.408618 19.066617 22.402800  ### Nodal Boundary Conditions ###  fix 534 1 1 1 1 1 1 fix 536 1 1 1 1 1 1 fix 546 1 1 1 1 1 1 ⋮ <lines removed here for brevity> ⋮ fix 651 1 1 1 1 1 1 fix 663 1 1 1 1 1 1 fix 665 1 1 1 1 1 1  ### Multi-point Constraints ###  rigidLink beam 29553 44258 rigidLink beam 29534 44259 rigidLink beam 15848 44996 ⋮ <lines removed here for brevity> ⋮ rigidLink beam 15848 44997 rigidLink beam 15848 44998 rigidLink beam 15848 44999   181 ### Uniaxial Materials ###  uniaxialMaterial Steel02 13733 400000000 200000000000 0.02 18 0.925 0.15 0.0 1.0 0.0 1.0 0.0 uniaxialMaterial Steel02 14671 400000000 200000000000 0.02 18 0.925 0.15 0.0 1.0 0.0 1.0 0.0 ⋮ <lines removed here for brevity> ⋮ uniaxialMaterial Steel02 14686 400000000 200000000000 0.02 18 0.925 0.15 0.0 1.0 0.0 1.0 0.0 uniaxialMaterial Steel02 14688 400000000 200000000000 0.02 18 0.925 0.15 0.0 1.0 0.0 1.0 0.0  uniaxialMaterial Concrete02 14637 45557315.37 0.010223 42435273.66 0.0488 0.1 5000000 2340000000 uniaxialMaterial Concrete02 14637 45557315.37 0.010223 42435273.66 0.0488 0.1 5000000 2340000000 ⋮ <lines removed here for brevity> ⋮ uniaxialMaterial Concrete02 14637 45557315.37 0.010223 42435273.66 0.0488 0.1 5000000 2340000000 uniaxialMaterial Concrete02 14637 45557315.37 0.010223 42435273.66 0.0488 0.1 5000000 2340000000  uniaxialMaterial ElasticBilin 14653 23400000000 0.0 0.002 23400000000 0.0 -0.002 uniaxialMaterial ElasticBilin 14657 23400000000 0.0 0.002 23400000000 0.0 -0.002 ⋮ <lines removed here for brevity> ⋮ uniaxialMaterial ElasticBilin 14661 23400000000 0.0 0.002 23400000000 0.0 -0.002 uniaxialMaterial ElasticBilin 14023 23400000000 0.0 0.002 23400000000 0.0 -0.002  uniaxialMaterial Elastic 14615 5081435.35 0.0 5081435.35 uniaxialMaterial Elastic 15065 5081435.35 0.0 5081435.35 ⋮ <lines removed here for brevity> ⋮ uniaxialMaterial Elastic 15245 8833216.41 0.0 8833216.41 uniaxialMaterial Elastic 15692 8833216.41 0.0 8833216.41  ### nD Materials ###  nDmaterial PlateRebar 13763 13733 90 nDmaterial PlateRebar 13764 13733 90 ⋮ <lines removed here for brevity> ⋮ nDmaterial PlateRebar 15290 15260 90 nDmaterial PlateRebar 15291 15260 90  nDMaterial PlasticDamageConcretePlaneStress 13765 27771032557.0 0.15 8000000 55783832.22 0.50 1.0 2.0 0.8 nDMaterial PlasticDamageConcretePlaneStress 43105 27771032557.0 0.15 8000000 55783832.22 0.50 1.0 2.0 0.8 ⋮ <lines removed here for brevity> ⋮ nDMaterial PlasticDamageConcretePlaneStress 43705 27771032557.0 0.15 8000000 55783832.22 0.50 1.0 2.0 0.8  182 nDMaterial PlasticDamageConcretePlaneStress 44044 27771032557.0 0.15 8000000 55783832.22 0.50 1.0 2.0 0.8  nDMaterial PlateFromPlaneStress 13768 13765 12074361981.35 nDMaterial PlateFromPlaneStress 15295 15292 12074361981.35 ⋮ <lines removed here for brevity> ⋮ nDMaterial PlateFromPlaneStress 43108 43105 12074361981.35 nDMaterial PlateFromPlaneStress 43713 43710 12074361981.35  nDMaterial ElasticIsotropic 13770 27771032557.11 0.15 2450.0 nDMaterial ElasticIsotropic 15297 27771032557.11 0.15 2450.0 ⋮ <lines removed here for brevity> ⋮ nDMaterial ElasticIsotropic 16149 27771032557.11 0.15 2450.0 nDMaterial ElasticIsotropic 16407 27771032557.11 0.15 2450.0  ### Sections ###  section LayeredShell 13775 8 13773 0.025 13763 0.0015 13764 0.00133 13768 0.0738 13768 0.0738 13763 0.0015 13764 0.00133 13773 0.025 section LayeredShell 43715 8 43713 0.025 43703 0.0015 43704 0.00133 43708 0.0738 43708 0.0738 43703 0.0015 43704 0.00133 43713 0.025  ⋮ <lines removed here for brevity> ⋮ section LayeredShell 44054 8 44052 0.025 44042 0.0015 44043 0.00133 44047 0.0738 44047 0.0738 44042 0.0015 44043 0.00133 44052 0.025  section LayeredShell 43973 8 43971 0.025 43961 0.0015 43962 0.00133 43966 0.0738 43966 0.0738 43961 0.0015 43962 0.00133 43971 0.025  section Fiber 14077 14075 {; fiber -0.038300 0.063700 0.009759 14007; fiber -0.038300 -0.063700 0.009759 14019; fiber 0.089100 0.069950 0.003497 14033; fiber 0.089100 -0.069950 0.003497 14035; fiber 0.076600 -0.127400 0.000200 14064; fiber 0.076600 -0.042467 0.000200 14066; fiber 0.076600 0.042467 0.000200 14068; fiber 0.076600 0.127400 0.000200 14070; fiber 0.038300 -0.063700 0.009759 14021; fiber -0.044550 -0.139900 0.002227 14029; fiber 0.044550 -0.139900 0.002227 14031; fiber -0.025533 -0.127400 0.000200 14060; fiber 0.025533 -0.127400 0.000200 14062; fiber 0.038300 0.063700 0.009759 14017; fiber -0.089100 0.069950 0.003498 14023; fiber -0.089100 -0.069950 0.003498 14027; fiber -0.076600 0.127400 0.000200 14041; fiber -0.076600 0.042467 0.000200 14054; fiber -0.076600 -0.042467 0.000200 14056; fiber -0.076600 -0.127400 0.000200 14058; fiber 0.044550 0.139900 0.002227 14037; fiber -0.044550 0.139900 0.002227 14039; fiber 0.025533 0.127400 0.000200 14072; fiber -0.025533 0.127400 0.000200 14074; }; ⋮ <lines removed here for brevity>  183 ⋮ section Fiber 44001 43997 {; fiber -0.038300 0.063700 0.009759 43929; fiber -0.038300 -0.063700 0.009759 43941; fiber 0.089100 0.069950 0.003497 43955; fiber 0.089100 -0.069950 0.003497 43957; fiber 0.076600 -0.127400 0.000200 43986; fiber 0.076600 -0.042467 0.000200 43988; fiber 0.076600 0.042467 0.000200 43990; fiber 0.076600 0.127400 0.000200 43992; fiber 0.038300 -0.063700 0.009759 43943; fiber -0.044550 -0.139900 0.002227 43951; fiber 0.044550 -0.139900 0.002227 43953; fiber -0.025533 -0.127400 0.000200 43982; fiber 0.025533 -0.127400 0.000200 43984; fiber 0.038300 0.063700 0.009759 43939; fiber -0.089100 0.069950 0.003498 43945; fiber -0.089100 -0.069950 0.003498 43949; fiber -0.076600 0.127400 0.000200 43963; fiber -0.076600 0.042467 0.000200 43976; fiber -0.076600 -0.042467 0.000200 43978; fiber -0.076600 -0.127400 0.000200 43980; fiber 0.044550 0.139900 0.002227 43959; fiber -0.044550 0.139900 0.002227 43961; fiber 0.025533 0.127400 0.000200 43994; fiber -0.025533 0.127400 0.000200 43996; };  ### Elements ###  element ShellMITC4 13896 13778 13779 13789 13788 13775 element ShellMITC4 13897 13779 13780 13790 13789 13775 ⋮ <lines removed here for brevity> ⋮ element ShellMITC4 44253 44143 44144 44154 44153 44054 element ShellMITC4 44254 44144 44145 44155 44154 44054  element dispBeamColumn 14004 44798 14003 3 -sections 14077 14078 14079 14004 2450.0 -integration Lobatto element dispBeamColumn 14005 14003 44942 3 -sections 14077 14078 14079 14005 2450.0 -integration Lobatto ⋮ <lines removed here for brevity> ⋮ element dispBeamColumn 43926 44545 43925 3 -sections 43999 44000 44001 43926 2450.0 -integration Lobatto element dispBeamColumn 43927 43925 44669 3 -sections 43999 44000 44001 43927 2450.0 -integration Lobatto  ### Analysis tools typically appear here, but they are not part of the BIM import algorithm developed in this work ###    184 Appendix B: Construction and Demolition Actions A list of construction and demolition actions are listed below to provide the different tasks, i.e., CSI codes, employed when the case study building is constructed and demolished. The total cost of the actions listed below gives the direct construction and demolition cost of the considered building, including material, labour, and equipment. The CSI codes and descriptions are provided by RSMeans. Table B.1 Concrete material CSI codes Concrete Type CSI Code Unit Description C15 033113350020 CY Structural concrete, ready mix, heavyweight, 2000 psi, includes local aggregate, sand, Portland cement (Type I) and water, delivered, excludes all additives and treatments C18 033113350100 CY Structural concrete, ready mix, heavyweight, 2500 psi, includes local aggregate, sand, Portland cement (Type I) and water, delivered, excludes all additives and treatments C20 033113350150 CY Structural concrete, ready mix, heavyweight, 3000 psi, includes local aggregate, sand, Portland cement (Type I) and water, delivered, excludes all additives and treatments C25 033113350200 CY Structural concrete, ready mix, heavyweight, 3500 psi, includes local aggregate, sand, Portland cement (Type I) and water, delivered, excludes all additives and treatments C30 033113350300 CY Structural concrete, ready mix, heavyweight, 4000 psi, includes local aggregate, sand, Portland cement (Type I) and water, delivered, excludes all additives and treatments C35 033113350400 CY Structural concrete, ready mix, heavyweight, 5000 psi, includes local aggregate, sand, Portland cement (Type I) and water, delivered, excludes all additives and treatments C40 033113350411 CY Structural concrete, ready mix, heavyweight, 6000 psi, includes local aggregate, sand, Portland cement (Type I) and water, delivered, excludes all additives and treatments C55 033113350412 CY Structural concrete, ready mix, heavyweight, 8000 psi, includes local aggregate, sand, Portland cement (Type I) and water, delivered, excludes all additives and treatments C25 033113250340 CF Concrete, hand mix, for small quantities or remote areas, 4000 psi, using wheelbarrow, includes bagged pre-mixed dry ingredients (80-Lb bag = 0.6 C.F.) and water, excludes, forms, reinforcing, placing & finishing    185 Table B.2 Reinforced concrete column construction action  Condition CSI Code Unit Description Formwork Max width <= 8 in 031113255000 SFCA C.I.P. concrete forms, column, square, plywood, 8" x 8", 1 use, includes erecting, bracing, stripping and cleaning 8 in < Max width <= 12 in 031113255500 SFCA C.I.P. concrete forms, column, square, plywood, 12" x 12", 1 use, includes erecting, bracing, stripping and cleaning 12 in < Max width <= 16 in 031113256000 SFCA C.I.P. concrete forms, column, square, plywood, 16" x 16", 1 use, includes erecting, bracing, stripping and cleaning 16 in < Max width <= 24 in 031113256500 SFCA C.I.P. concrete forms, column, square, plywood, 24" x 24", 1 use, includes erecting, bracing, stripping and cleaning 24 in < Max width <= 36 in 031113257000 SFCA C.I.P. concrete forms, column, square, plywood, 36" x 36", 1 use, includes erecting, bracing, stripping and cleaning Installation of reinforcement (longitudinal bar with transverse hoop) Spiral transverse reinforcement 032111600300 TON Reinforcing steel, in place, columns, spirals, 8" to 15" diameter, A615, grade 60, incl labor for accessories, excl material for accessories Reinforcement diameter <= 20M 032111600200  TON Reinforcing steel, in place, columns, #3 to #7, A615, grade 60, incl labor for accessories, excl material for accessories Reinforcement diameter > 20M 032111600250 TON Reinforcing steel, in place, columns, #8 to #18, A615, grade 60, incl labor for accessories, excl material for accessories Concrete placing (pumped) Max width <= 12 in 033113700400 CY Structural concrete, placing, column, square or round, pumped, 12" thick, includes leveling (strike off) & consolidation, excludes material 12 in < Max width <= 18 in 033113700600 CY Structural concrete, placing, column, square or round, pumped, 18" thick, includes leveling (strike off) & consolidation, excludes material 18 in < Max width <= 24 in 033113700800 CY Structural concrete, placing, column, square or round, pumped, 24" thick, includes leveling (strike off) & consolidation, excludes material 24 in < Max width <= 36 in 033113701000 CY Structural concrete, placing, column, square or round, pumped, 36" thick, includes leveling (strike off) & consolidation, excludes material Concrete placing (crane and bucket) Max width <= 12 in 033113700450 CY Structural concrete, placing, column, square or round, with crane and bucket, 12" thick, includes leveling (strike off) & consolidation, excludes material 12 in < Max width <= 18 in 033113700650 CY Structural concrete, placing, column, square or round, with crane and bucket, 18" thick,  186 includes leveling (strike off) & consolidation, excludes material 18 in < Max width <= 24 in 033113700850 CY Structural concrete, placing, column, square or round, with crane and bucket, 24" thick, includes leveling (strike off) & consolidation, excludes material 24 in < Max width <= 36 in 033113701050 CY Structural concrete, placing, column, square or round, with crane and bucket, 36" thick, includes leveling (strike off) & consolidation, excludes material Finishing and curing  033913500100 CSF Curing, burlap, 10 oz., 4 uses assumed Table B.3 Reinforced concrete slab construction action Condition CSI Code Unit Description Formwork (elevated plywood pan forms on stringers with shoring or scaffolding) Storey height <= 15 ft 031113351000 SF C.I.P. concrete forms, elevated slab, flat plate, plywood, to 15' high, 1 use, includes shoring, erecting, bracing, stripping and cleaning 15 ft < Storey height <= 20 ft 031113351500 SF C.I.P. concrete forms, elevated slab, flat plate, plywood, to 20' high, 1 use, includes shoring, erecting, bracing, stripping and cleaning 20 ft < Storey height <= 35 ft 031113351600 SF C.I.P. concrete forms, elevated slab, flat plate, plywood, 21' to 35' high ceilings, 4 use, includes shoring, erecting, bracing, stripping and cleaning Slab thickness <= 6 in 031113357000 LF C.I.P. concrete forms, elevated slab, edge forms, to 6" high, 4 use, includes shoring, erecting, bracing, stripping and cleaning 6 in < Slab thickness <= 12 in 031113357070 LF C.I.P. concrete forms, elevated slab, edge forms, 7" to 12" high, 1 use, includes shoring, erecting, bracing, stripping and cleaning Box-out per each opening 031113355500 EA C.I.P. concrete forms, elevated slab, box-out for shallow slab openings, to 10 S.F., includes shoring, erecting, bracing, stripping and cleaning Installation of reinforcement Reinforcement diameter <= 25M 032111600400  TON Reinforcing steel, in place, elevated slabs, #4 to #7, A615, grade 60, incl labor for accessories, excl material for accessories Concrete placing (pumped) Slab thickness <= 6 in 033113701400 CY Elevated slabs, less than 6" thick, pumped 6 in < Slab thickness <= 10 in 033113701500 CY Elevated slabs, 6" to 10" thick, pumped Slab thickness > 10 in 033113701600 CY Elevated slabs, over 10" thick, pumped  187 Concrete placing (crane and bucket) Slab thickness <= 6 in 033113701450 CY Elevated slabs, less than 6" thick, with crane and bucket 6 in < Slab thickness <= 10 in 033113701550 CY Elevated slabs, 6" to 10" thick, with crane and bucket Slab thickness > 10 in 033113701650 CY Elevated slabs, over 10" thick, with crane and bucket Finishing and curing  033513300250 SF Concrete finishing, bull float, machine float & steel trowel (walk-behind), excl placing, striking off & consolidating  033913500100 CSF Curing, burlap, 10 oz., 4 uses assumed Table B.4 Reinforced concrete shear wall construction action Condition CSI Code Unit Description Formwork (site-built from plywood, assuming multiple uses) Wall height <= 8 ft 031113852150 SFCA C.I.P. concrete forms, wall, job built, plywood, to 8' high, 4 use, includes erecting, bracing, stripping and cleaning 8 ft < Wall height <= 16 ft 031113852550 SFCA C.I.P. concrete forms, wall, job built, plywood, over 8' to 16' high, 4 use, includes erecting, bracing, stripping and cleaning Wall height > 16 ft 031113852850 SFCA C.I.P. concrete forms, wall, job built, plywood, over 16' high, 4 use, includes erecting, bracing, stripping and cleaning Formwork (modular prefabricated plywood) Wall height <= 8 ft 031113857860 SFCA C.I.P. concrete forms, walls, modular prefabricated plywood, to 8' high, includes erecting, bracing, stripping and cleaning 8 ft < Wall height <= 16 ft 031113858060 SFCA C.I.P. concrete forms, walls, modular prefabricated plywood, over 8' to 16' high, includes erecting, bracing, stripping and cleaning Formwork (steel framed plywood) Wall height <= 8 ft 031113859060 SFCA C.I.P. concrete forms, walls, steel framed plywood, to 8' high, based on 50 uses of purchased forms, 4 uses of bracing lumber, includes erecting, bracing, stripping and cleaning 8 ft < Wall height <= 16 ft 031113859260 SFCA C.I.P. concrete forms, walls, steel framed plywood, over 8' to 16' high, based on 50 uses of purchased forms, 4 uses of bracing lumber, includes erecting, bracing, stripping and cleaning 16 ft < Wall height <= 20 ft 031113859460 SFCA C.I.P. concrete forms, walls, steel framed plywood, over 16' to 20' high, based on 50 uses of purchased forms, 4 uses of bracing lumber, includes erecting, bracing, stripping and cleaning  188 Box-out per each opening 031113850150 EA C.I.P. concrete forms, wall, box out for opening, to 16" thick, over 10 S.F. (use perimeter), includes erecting, bracing, stripping and cleaning Installation of reinforcement Reinforcement diameter <= 20M 032111600700 TON Reinforcing steel, in place, walls, #3 to #7, A615, grade 60, incl labor for accessories, excl material for accessories Reinforcement diameter > 20M 032111600750 TON Reinforcing steel, in place, walls, #8 to #18, A615, grade 60, incl labor for accessories, excl material for accessories Concrete placing (pumped) Wall thickness <= 8 in 033113704950 CY Structural concrete, placing, walls, pumped, 8" thick, includes leveling (strike off) & consolidation, excludes material 8 in < Wall thickness <= 12 in 033113705100 CY Structural concrete, placing, walls, pumped, 12" thick, includes leveling (strike off) & consolidation, excludes material 12 in < Wall thickness <= 15 in 033113705350 CY Structural concrete, placing, walls, pumped, 15" thick, includes leveling (strike off) & consolidation, excludes material Concrete placing (pumped) Wall thickness <= 8 in 033113705000 CY Structural concrete, placing, walls, with crane and bucket, 8" thick, includes leveling (strike off) & consolidation, excludes material 8 in < Wall thickness <= 12 in 033113705200 CY Structural concrete, placing, walls, with crane and bucket, 12" thick, includes leveling (strike off) & consolidation, excludes material 12 in < Wall thickness <= 15 in 033113705400 CY Structural concrete, placing, walls, with crane and bucket, 15" thick, includes leveling (strike off) & consolidation, excludes material Finishing and curing  033529600050 SF Concrete finishing, walls, burlap rub with grout, includes breaking ties and patching voids  033913500100 CSF Curing, burlap, 10 oz., 4 uses assumed Table B.5 Steel wide flange and glue laminated timber column construction actions  CSI Code Unit Description Wide flange column 051223176850 LF Material, framing labour, wide flange section W8X31    051223176900 LF Material, framing labour, wide flange section W8X48    051223176950 LF Material, framing labour, wide flange section W8X67    051223177000 LF Material, framing labour, wide flange section W10X45   051223177050 LF Material, framing labour, wide flange section W10X68    189 051223177100 LF Material, framing labour, wide flange section W10X112  051223177150 LF Material, framing labour, wide flange section W12X50   051223177200 LF Material, framing labour, wide flange section W12X87   051223177250 LF Material, framing labour, wide flange section W12X120  051223177300 LF Material, framing labour, wide flange section W12X190  051223177350 LF Material, framing labour, wide flange section W14X74   051223177400 LF Material, framing labour, wide flange section W14X120  051223177450 LF Material, framing labour, wide flange section W14X176  Glue laminated timber column  061813204400 MBF Laminated framing, alternate pricing method: (use nominal footage of components), columns, includes hardware Table B.6 Steel skin pan and cross-laminated timber (CLT) slab construction action  CSI Code Unit Description 061523000000 SF Laminated wood decking, CLT floor/roof, includes fire proofing and acoustical treatment Steel skin pan with lightweight concrete topping  Condition CSI Code Unit Description 16-gauge pan, 1.5 in depth  053113505100 SF Metal floor decking, steel, non-cellular, composite, galvanized, 1-1/2 in depth, 16 gauge 16-gauge pan, 2.0 in depth 053113505500 SF Metal floor decking, steel, non-cellular, composite, galvanized, 2 in depth, 16 gauge 16-gauge pan, 3.0 in depth 053113506000 SF Metal floor decking, steel, non-cellular, composite, galvanized, 3 in depth, 16 gauge 18-gauge pan, 1.5 in depth  053113505120 SF Metal floor decking, steel, non-cellular, composite, galvanized, 1-1/2 in depth, 18 gauge 18-gauge pan, 2.0 in depth 053113505400 SF Metal floor decking, steel, non-cellular, composite, galvanized, 2 in depth, 18 gauge 18-gauge pan, 3.0 in depth 053113505900 SF Metal floor decking, steel, non-cellular, composite, galvanized, 3 in depth, 18 gauge 20-gauge pan, 1.5 in depth  053113505140 SF Metal floor decking, steel, non-cellular, composite, galvanized, 1-1/2 in depth, 20 gauge 20-gauge pan, 2.0 in depth 053113505300 SF Metal floor decking, steel, non-cellular, composite, galvanized, 2 in depth, 20 gauge 20-gauge pan, 3.0 in depth 053113505800 SF Metal floor decking, steel, non-cellular, composite, galvanized, 3 in depth, 20 gauge 22-gauge pan, 2.0 in depth 053113505200 SF Metal floor decking, steel, non-cellular, composite, galvanized, 2 in depth, 22 gauge 22-gauge pan, 3.0 in depth 053113505700 SF Metal floor decking, steel, non-cellular, composite, galvanized, 3 in depth, 22 gauge CLT Slab CSI Code Unit Description  190 061523000000 SF Laminated wood decking, CLT floor/roof, includes fire proofing and acoustical treatment Table B.7 Building demolition actions  Condition CSI Code Unit Description Concrete material 024116130050 CF Building demolition, large urban projects, concrete, includes 20 mile haul, excludes foundation demolition, dump fees Steel material 024116130020 CF Building demolition, large urban projects, steel, includes 20 mile haul, excludes foundation demolition, dump fees Wood 024116130700 CF Building demolition, small buildings or single buildings, wood, elevated slabs, includes 20 mile haul, excludes salvage, foundation demolition or dump fees Table B.8 Miscellaneous project-level CSI codes  Condition CSI Code Unit Description  032111602000 TON Reinforcing steel, unload and sort, add to base Number of building stories > 5 033113703510 CY Structural concrete, placing, high rise, with crane and bucket, more than 5 stories, includes leveling (strike off) & consolidation, excludes material, add per story Building height < 130 ft 015419600100 MONTH Crane crew, tower crane, static, 130' high, 106' jib, 6200 lb. capacity, monthly use, excludes concrete footing Reinforcement diameter < 25M tons of reinforcement < 10 tons 032111601000 EA Reinforcing steel, in place, under 10 ton job, #3 to #7, add 10 tons <= tons of reinforcement  < 50 tons 032111601050 EA Reinforcing steel, in place, 10 to 50 ton job, #3 to #7, add 60 tons <= tons of reinforcement  < 100 tons 032111601100 EA Reinforcing steel, in place, 60 to 100 ton job, #3 to #7, deduct tons of reinforcement > 100 tons 032111601150 EA Reinforcing steel, in place, over 100 ton job, #3 to #7, deduct Reinforcement diameter >= 25M tons of reinforcement < 10 tons 032111601010 EA Reinforcing steel, in place, under 10 ton job, #8 to #18, add 10 tons <= tons of reinforcement  < 50 tons 032111601060 EA Reinforcing steel, in place, 10 to 50 ton job, #8 to #18, add 60 tons <= tons of reinforcement  < 100 tons 032111601110 EA Reinforcing steel, in place, 60 to 100 ton job, #8 to #18, deduct tons of reinforcement > 100 tons 032111601160 EA Reinforcing steel, in place, over 100 ton job, #8 to #18, deduct     191 Appendix C: Repair Actions  Several lists of repair actions, given as CSI codes, are provided below. These lists provide the tasks required to repair different types of visual damage after earthquakes. For example, the tables in Appendix C.2 provide the concrete cover repair actions for a slab, shear wall, and column. The CSI codes and descriptions are provided by RSMeans.  C.1 Cracking, spalling, and cover patching repair actions Table C.1 Epoxy-injection crack repair and spalling repair actions for all concrete components CSI Code Unit Description Epoxy injection 036423000000 CF Concrete resurfacing, epoxy injection grouting Spalling repair 030130620100 SF Patching concrete, Floors, 1/4" thick, small areas, regular grout 030130620150 SF Patching concrete, Floors, 1/4" thick, small areas, epoxy grout 030130622100 SF Patching concrete, Walls, including chipping, cleaning and epoxy grout, 1/4” deep 030130622150 SF Patching concrete, Walls, including chipping, cleaning and epoxy grout, 1/2" deep 030130622200 SF Patching concrete, Walls, including chipping, cleaning and epoxy grout, 3/4" deep Cover patch repair 033113250340 CF Concrete, hand mix, for small quantities or remote areas, 4000 psi, using wheelbarrow, includes bagged pre-mixed dry ingredients (80-Lb bag = 0.6 C.F.) and water, excludes, forms, reinforcing, placing & finishing 033529600600 SF Concrete finishing, walls, float finish, 1/16" thick 033513300200 SF Concrete finishing, fresh concrete flatwork, floors, basic finishing for unspecified flatwork, bull float, manual float & manual steel trowel, excl placing, striking off & consolidating 033113705620 CY Structural concrete, placing, by walking cart, 150' haul, excludes material, add to placing costs above C.2 Cover replacement repair actions Table C.2 Reinforced concrete column cover replacement repair action  Condition CSI Code Unit Description Demolition Reinforcement ratio <= 0.01 030505100050 CY Selective concrete demolition, reinforcing less than 1% of cross-sectional area, break up into  192 small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping 0.01 < Reinforcement ratio <= 0.02 030505100060 CY Selective concrete demolition, reinforcing 1% - 2% of cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping Reinforcement ratio > 0.02 030505100070 CY Selective concrete demolition, reinforcing more than 2% cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping Removal and disposal 0-50 ft hauling distance of material 024119192000 CY Selective demolition, rubbish handling, 0'-50' haul, load, haul, dump and return, hand carried, cost to be added to demolition cost Distance to disposal facility < 5 miles 024119180300 CY Selective demolition, disposal only, urban buildings with salvage value allowed, concrete frame, includes loading and 5 mile haul to dump Formwork installation Max dimension <= 8 in 031113255000 SFCA C.I.P. concrete forms, column, square, plywood, 8" x 8", 1 use, includes erecting, bracing, stripping and cleaning 8 in < Max width <= 12 in 031113255500 SFCA C.I.P. concrete forms, column, square, plywood, 12" x 12", 1 use, includes erecting, bracing, stripping and cleaning 12 in < Max width <= 16 in 031113256000 SFCA C.I.P. concrete forms, column, square, plywood, 16" x 16", 1 use, includes erecting, bracing, stripping and cleaning 16 in < Max width <= 24 in 031113256500 SFCA C.I.P. concrete forms, column, square, plywood, 24" x 24", 1 use, includes erecting, bracing, stripping and cleaning 24 in < Max width <= 36 in 031113257000 SFCA C.I.P. concrete forms, column, square, plywood, 36" x 36", 1 use, includes erecting, bracing, stripping and cleaning Concrete placing Pumped concrete 033113700400 CY Structural concrete, placing, column, square or round, pumped, 12" thick, includes leveling (strike off) & consolidation, excludes material Finishing and curing  033913500100 CSF Curing, burlap, 10 oz., 4 uses assumed    193 Table C.3 Reinforced concrete slab top cover replacement repair action  Condition CSI Code Unit Description Demolition Reinforcement ratio <= 0.01 030505100050 CY Selective concrete demolition, reinforcing less than 1% of cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping 0.01 < Reinforcement ratio <= 0.02 030505100060 CY Selective concrete demolition, reinforcing 1% - 2% of cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping Reinforcement ratio > 0.02 030505100070 CY Selective concrete demolition, reinforcing more than 2% cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping Removal and disposal 0-50 ft hauling distance of material 024119192000 CY Selective demolition, rubbish handling, 0'-50' haul, load, haul, dump and return, hand carried, cost to be added to demolition cost Distance to disposal facility < 5 miles 024119180300 CY Selective demolition, disposal only, urban buildings with salvage value allowed, concrete frame, includes loading and 5 mile haul to dump Concrete placing  033113701400 CY Structural concrete, placing, elevated slab, pumped, less than 6" thick, includes leveling (strike off) & consolidation, excludes material Finishing and curing  033513300200 SF Concrete finishing, fresh concrete flatwork, floors, basic finishing for unspecified flatwork, bull float, manual float & manual steel trowel, excl placing, striking off & consolidating  033913500100 CSF Curing, burlap, 10 oz., 4 uses assumed Table C.4 Reinforced concrete slab bottom cover replacement repair action  Condition CSI Code Unit Description Demolition Reinforcement ratio <= 0.01 030505100050 CY Selective concrete demolition, reinforcing less than 1% of cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping 0.01 < Reinforcement ratio <= 0.02 030505100060 CY Selective concrete demolition, reinforcing 1% - 2% of cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping  194 Reinforcement ratio > 0.02 030505100070 CY Selective concrete demolition, reinforcing more than 2% cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping Removal and disposal 0-50 ft hauling distance of material 024119192000 CY Selective demolition, rubbish handling, 0'-50' haul, load, haul, dump and return, hand carried, cost to be added to demolition cost Distance to disposal facility < 5 miles 024119180300 CY Selective demolition, disposal only, urban buildings with salvage value allowed, concrete frame, includes loading and 5 mile haul to dump Concrete placing  033713300900 SF Gunite, preparation of old walls, excludes scaffolding, good condition Per inch of thickness 033713300020 SF Gunite, dry mix, applied in layers, 1" thick, excludes reinforcing mesh  033713301100 SF Gunite, high finish requirement or close tolerance, add Table C.5 Reinforced concrete shear wall cover replacement repair action  Condition CSI Code Unit Description Demolition Reinforcement ratio <= 0.01 030505100050 CY Selective concrete demolition, reinforcing less than 1% of cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping 0.01 < Reinforcement ratio <= 0.02 030505100060 CY Selective concrete demolition, reinforcing 1% - 2% of cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping Reinforcement ratio > 0.02 030505100070 CY Selective concrete demolition, reinforcing more than 2% cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping Removal and disposal 0-50 ft hauling distance of material 024119192000 CY Selective demolition, rubbish handling, 0'-50' haul, load, haul, dump and return, hand carried, cost to be added to demolition cost Distance to disposal facility < 5 miles 024119180300 CY Selective demolition, disposal only, urban buildings with salvage value allowed, concrete frame, includes loading and 5 mile haul to dump Formwork (site-built from plywood) Wall height <= 8 ft 031113852000 SFCA C.I.P. concrete forms, wall, job built, plywood, to 8' high, 1 use, includes erecting, bracing, stripping and cleaning  195 8 ft < Wall height <= 16 ft 031113852400 SFCA C.I.P. concrete forms, wall, job built, plywood, over 8' to 16' high, 1 use, includes erecting, bracing, stripping and cleaning Wall height > 16 ft 031113852700 SFCA C.I.P. concrete forms, wall, job built, plywood, over 16' high, 1 use, includes erecting, bracing, stripping and cleaning Box-out per each opening 031113850150 EA C.I.P. concrete forms, wall, box out for opening, to 16" thick, over 10 S.F. (use perimeter), includes erecting, bracing, stripping and cleaning Concrete placing (pumped) Wall thickness <= 8 in 033113704950 CY Structural concrete, placing, walls, pumped, 8" thick, includes leveling (strike off) & consolidation, excludes material 8 in < Wall thickness <= 12 in 033113705100 CY Structural concrete, placing, walls, pumped, 12" thick, includes leveling (strike off) & consolidation, excludes material 12 in < Wall thickness <= 15 in 033113705350 CY Structural concrete, placing, walls, pumped, 15" thick, includes leveling (strike off) & consolidation, excludes material Finishing and curing  033529600050 SF Concrete finishing, walls, burlap rub with grout, includes breaking ties and patching voids  033913500100 CSF Curing, burlap, 10 oz., 4 uses assumed C.3 Component replacement repair actions Table C.6 Reinforced concrete column replacement repair action  Condition CSI Code Unit Description Bracing and shoring Assume 8 frames 031505705040 EA Frame shoring system, frame, 12000# per leg, 2' wide x 6' high, steel, buy 031505705250 EA Frame shoring system, X-brace, 12000# per leg, steel, buy 031505705600 EA Frame shoring system, screw jack, 12000# per leg, steel, buy 031505705550 EA Frame shoring system, base plate, 12000# per leg, steel, buy 031505705650 EA Frame shoring system, U-head, 12000# per leg, 8" x 8", steel, buy Demolition Reinforcement ratio <= 0.01 030505100050 CY Selective concrete demolition, reinforcing less than 1% of cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping 0.01 < Reinforcement ratio <= 0.02 030505100060 CY Selective concrete demolition, reinforcing 1% - 2% of cross-sectional area, break up into  196 small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping Reinforcement ratio > 0.02 030505100070 CY Selective concrete demolition, reinforcing more than 2% cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping Removal and disposal 0-50 ft hauling distance of material 024119192000 CY Selective demolition, rubbish handling, 0'-50' haul, load, haul, dump and return, hand carried, cost to be added to demolition cost Distance to disposal facility < 5 miles 024119180300 CY Selective demolition, disposal only, urban buildings with salvage value allowed, concrete frame, includes loading and 5 mile haul to dump Formwork Max width <= 8 in 031113255000 SFCA C.I.P. concrete forms, column, square, plywood, 8" x 8", 1 use, includes erecting, bracing, stripping and cleaning 8 in < Max width <= 12 in 031113255500 SFCA C.I.P. concrete forms, column, square, plywood, 12" x 12", 1 use, includes erecting, bracing, stripping and cleaning 12 in < Max width <= 16 in 031113256000 SFCA C.I.P. concrete forms, column, square, plywood, 16" x 16", 1 use, includes erecting, bracing, stripping and cleaning 16 in < Max width <= 24 in 031113256500 SFCA C.I.P. concrete forms, column, square, plywood, 24" x 24", 1 use, includes erecting, bracing, stripping and cleaning 24 in < Max width <= 36 in 031113257000 SFCA C.I.P. concrete forms, column, square, plywood, 36" x 36", 1 use, includes erecting, bracing, stripping and cleaning Drilling and embedment of reinforcement dowels Assume 16 dowels per column, 8 on each end 038216100700 EA Concrete impact drilling, for anchors, up to 4" D, 1" dia, in concrete or brick walls and floors, includes bit cost, layout and set up time, excl anchor 036305101535 EA Chemical anchoring, for fastener 1" diam x 8" embedment, incl epoxy cartridge, excl layout, drilling & fastener Installation of reinforcement (longitudinal bar with transverse hoop) Reinforcement diameter <= 20M 032111600200  TON Reinforcing steel, in place, columns, #3 to #7, A615, grade 60, incl labor for accessories, excl material for accessories Reinforcement diameter > 20M 032111600250 TON Reinforcing steel, in place, columns, #8 to #18, A615, grade 60, incl labor for accessories, excl material for accessories Concrete placing (pumped) Max width <= 12 in 033113700400 CY Structural concrete, placing, column, square or round, pumped, 12" thick, includes leveling (strike off) & consolidation, excludes material  197 12 in < Max width <= 18 in 033113700600 CY Structural concrete, placing, column, square or round, pumped, 18" thick, includes leveling (strike off) & consolidation, excludes material 18 in < Max width <= 24 in 033113700800 CY Structural concrete, placing, column, square or round, pumped, 24" thick, includes leveling (strike off) & consolidation, excludes material 24 in < Max width <= 36 in 033113701000 CY Structural concrete, placing, column, square or round, pumped, 36" thick, includes leveling (strike off) & consolidation, excludes material Finishing and curing  033913500100 CSF Curing, burlap, 10 oz., 4 uses assumed Table C.7 Reinforced concrete slab replacement repair action  Condition CSI Code Unit Description Bracing and shoring Assume one frame for 36 sq ft of area of repair 031505705040 EA Frame shoring system, frame, 12000# per leg, 2' wide x 6' high, steel, buy 031505705250 EA Frame shoring system, X-brace, 12000# per leg, steel, buy 031505705600 EA Frame shoring system, screw jack, 12000# per leg, steel, buy 031505705550 EA Frame shoring system, base plate, 12000# per leg, steel, buy 031505705650 EA Frame shoring system, U-head, 12000# per leg, 8" x 8", steel, buy Demolition Reinforcement ratio <= 0.01 030505100050 CY Selective concrete demolition, reinforcing less than 1% of cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping 0.01 < Reinforcement ratio <= 0.02 030505100060 CY Selective concrete demolition, reinforcing 1% - 2% of cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping Reinforcement ratio > 0.02 030505100070 CY Selective concrete demolition, reinforcing more than 2% cross-sectional area, break up into small pieces, excludes shoring, bracing, saw or torch cutting, loading, hauling, dumping Up to 3 inches deep 038113500500 LF Concrete sawing, concrete slabs, rod reinforced, up to 3" deep, includes blade cost, layout and set up time Each additional inch of slab depth 038113500520 LF Concrete sawing, concrete, existing slab, rod reinforced, for each additional inch of depth over 3", includes blade cost, layout and set up time Removal and disposal  198 0-50 ft hauling distance of material 024119192000 CY Selective demolition, rubbish handling, 0'-50' haul, load, haul, dump and return, hand carried, cost to be added to demolition cost Distance to disposal facility < 5 miles 024119180300 CY Selective demolition, disposal only, urban buildings with salvage value allowed, concrete frame, includes loading and 5 mile haul to dump Formwork (site-built from plywood) Storey height <= 15 ft 031113351000 SF C.I.P. concrete forms, elevated slab, flat plate, plywood, to 15' high, 1 use, includes shoring, erecting, bracing, stripping and cleaning 15 ft < Storey height <= 20 ft 031113351500 SF C.I.P. concrete forms, elevated slab, flat plate, plywood, to 20' high, 1 use, includes shoring, erecting, bracing, stripping and cleaning 20 ft < Storey height <= 35 ft 031113351600 SF C.I.P. concrete forms, elevated slab, flat plate, plywood, 21' to 35' high ceilings, 4 use, includes shoring, erecting, bracing, stripping and cleaning Slab thickness <= 6 in 031113357000 LF C.I.P. concrete forms, elevated slab, edge forms, to 6" high, 4 use, includes shoring, erecting, bracing, stripping and cleaning 6 in < Slab thickness <= 12 in 031113357070 LF C.I.P. concrete forms, elevated slab, edge forms, 7" to 12" high, 1 use, includes shoring, erecting, bracing, stripping and cleaning Box-out per each opening 031113355500 EA C.I.P. concrete forms, elevated slab, box-out for shallow slab openings, to 10 S.F., includes shoring, erecting, bracing, stripping and cleaning Drilling and embedment of reinforcement dowels Assume 1 dowel every foot of repair perimeter 038216100700 EA Concrete impact drilling, for anchors, up to 4" D, 1" dia, in concrete or brick walls and floors, includes bit cost, layout and set up time, excl anchor 036305101535 EA Chemical anchoring, for fastener 1" diam x 8" embedment, incl epoxy cartridge, excl layout, drilling & fastener Installation of reinforcement Reinforcement diameter <= 25M 032111600400  TON Reinforcing steel, in place, elevated slabs, #4 to #7, A615, grade 60, incl labor for accessories, excl material for accessories Concrete placing (pumped) Slab thickness <= 6 in 033113701400 CY Elevated slabs, less than 6" thick, pumped 6 in < Slab thickness <= 10 in 033113701500 CY Elevated slabs, 6" to 10" thick, pumped Slab thickness > 10 in 033113701600 CY Elevated slabs, over 10" thick, pumped Finishing and curing  033513300200 SF Concrete finishing, fresh concrete flatwork, floors, basic finishing for unspecified flatwork,  199 bull float, manual float & manual steel trowel, excl placing, striking off & consolidating  033913500100 CSF Curing, burlap, 10 oz., 4 uses assumed  

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