TY - THES
AU - Gill, Gurvinder Singh
PY - 2017
TI - Probabilistic cost models for lifecycle design of buildings
KW - Thesis/Dissertation
LA - eng
M3 - Text
AB - This thesis presents a collection of numerical models that predict the total lifetime cost of buildings. Different models are developed for different phases in the life of a building, i.e., extraction and manufacturing of materials, construction, operation, hazards, demolition, and recycling. Models forecast direct costs, environmental impact costs, and human health costs related to each such phase. The variability in the parameters that enter the cost models is addressed using random variables. The estimate of the total cost of a building can be used in future work to optimize the structural design.
Despite powerful new optimization algorithms, the answer to what is holistically the optimal choice of materials, dimensions, and configurations is often unanswered in practice. One reason is that developers, architects, users, and societies may have different objectives, ranging from the cost of construction to aesthetic appeal and environmental impact. Another problem is the lack of unbiased models to predict the costs and benefits that matter to private and public stakeholders. Thus, concerns such as environmental impacts and cost of potential earthquakes are rarely quantified in an explicit and comprehensive manner. This issue is addressed in this thesis through the development of a collection of unified probabilistic cost models for a broad range of costs and benefits. The models proposed in this thesis are implemented in a computer program for simulation of building behaviour.
N2 - This thesis presents a collection of numerical models that predict the total lifetime cost of buildings. Different models are developed for different phases in the life of a building, i.e., extraction and manufacturing of materials, construction, operation, hazards, demolition, and recycling. Models forecast direct costs, environmental impact costs, and human health costs related to each such phase. The variability in the parameters that enter the cost models is addressed using random variables. The estimate of the total cost of a building can be used in future work to optimize the structural design.
Despite powerful new optimization algorithms, the answer to what is holistically the optimal choice of materials, dimensions, and configurations is often unanswered in practice. One reason is that developers, architects, users, and societies may have different objectives, ranging from the cost of construction to aesthetic appeal and environmental impact. Another problem is the lack of unbiased models to predict the costs and benefits that matter to private and public stakeholders. Thus, concerns such as environmental impacts and cost of potential earthquakes are rarely quantified in an explicit and comprehensive manner. This issue is addressed in this thesis through the development of a collection of unified probabilistic cost models for a broad range of costs and benefits. The models proposed in this thesis are implemented in a computer program for simulation of building behaviour.
UR - https://open.library.ubc.ca/collections/24/items/1.0343527
ER - End of Reference