International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP) (12th : 2015)

Systems reliability of flow control in dam safety Komey, Adiel; Deng, Qianli; Baecher, Gregory B.; Zielinski, P. Andy; Atkinson, Tyler Jul 31, 2015

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12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12 Vancouver, Canada, July 12-15, 2015  1 Systems Reliability of Flow Control in Dam Safety  Adiel Komey Graduate Student, Civil and Environmental Engineering, Univ. of Maryland, College Park, USA  Qianli Deng Graduate Student, Civil and Environmental Engineering, Univ. of Maryland, College Park, USA  Gregory B. Baecher Professor, Civil and Environmental Engineering, Univ. of Maryland, College Park, USA P. Andy Zielinski Senior Manager, Technology & Dam Safety, Ontario Power Generation, Toronto, Canada  Tyler Atkinson Senior Protection and Controls Engineer, Ontario Power Generation, Niagara, Canada ABSTRACT: The reliable performance of a spillway system depends on the many environmental and operational demand functions placed upon it by basin hydrology, the hydraulic conditions at reservoirs and dams, operating rules for the cascade of reservoirs in the basin, and the vagaries of human and nat-ural factors such as operator interventions or natural disturbances such as ice and floating debris. These systems interact to control floods, condition flows, and filter high frequencies in the river discharge. Their function is to retain water volumes and to pass flows in a controlled way. A systems simulation approach is presented for grappling with these varied influences on flow-control systems in hydropow-er installations. The river system studied is a series of four power stations in northern Ontario. At the head of the cascade is a seasonally-varying inflow. The remaining three dams downstream have little storage capacity. Each has two vertical lift gates and all four structures have approximately the same spillway capacity. The problem is to conceptualize a systems engineering model for the operation of the dams, spillways, and other components; then to employ the model through stochastic simulation to investigate protocols for the safe operation of the spillway and flow control system.   The reliable performance of dams and their ap-purtenant systems depends on the complex inter-actions of a large number of natural, engineered, and human systems. Historically, such systems have been designed for extreme loads, e.g., the largest flood or earthquake that might occur dur-ing some service life. But accidents and failures seldom derive from such loads: They more often occur through uncommon combinations of mis-haps that are difficult or impossible to identify during design. The challenge is to develop analy-sis approaches that capture these systems effects. Emergent behaviors are patterns or regularities that arise through the interactions among system elements which themselves do not exhibit such properties. Adverse performance typically arises from unanticipated combinations of loadings and responses within the normal operating ranges of a dam’s performance.  1. SYSTEMS APPROACH TO DAM SAFETY The function of a flow-control system is to retain water volumes and to pass flows in a controlled way. Their reliability involves structural, me-chanical, electrical, control systems and subsys-tems reliability, as well as human interactions, organization issues, policies and procedures, all of which, occurring in a broad spectrum of envi-ronmental conditions.  12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12 Vancouver, Canada, July 12-15, 2015  2 Adverse performance typically arises from unan-ticipated combinations of loadings and responses within the normal operating ranges of a dam’s performance. That is, failures often do not occur under the extreme loadings considered in design, but under the uncommon combination of rela-tively common things. For example, instrumenta-tion mis-performs so pool levels rise, simultane-ously ice has formed on spillway gates, which then cannot be opened to accommodate dis-charges, and finally the operator misperceives the danger and an accident follows.  A new approach is required to risk analysis for dam safety, as current engineering practices do not address the character of the most probable causes of accidents and failures. Combinations of unforeseen yet unfortunate events cannot be pre-dicted easily—or maybe at all—ahead of time. They are emergent behaviors. In a review of the performance of spillways and operating equipment, McCann (2013) reports that exclusive of the failure of spillway structures themselves, the performance of hydraulic sys-tems is important even during normal operations. These systems are affected by mal-operation, control system errors, and a host of interactions among factors. Figure 1.   Figure 1: Causes of dam flow-control accidents (McCann 2013)  The observation that most accidents and failures occur not from extreme loads but through more common yet unforeseen sequences of events is now widely recognized. Perrow (1999) argues that ever increasing complexity in technological systems makes these failures inevi-table. He argues that complex rather than linear interactions among components leads to systems performance that is difficult to understand. Flow-control in dam systems displays both sorts of in-teractions. Many dams may be considered to be tightly coupled systems because they have little flexibil-ity and have time-dependent operational needs. That is, a dam cannot usually wait while disturb-ances are attended to in an orderly way. Water flows into the reservoir and it must be dealt with now, not at some more convenient time in the fu-ture. Characteristics of tightly coupled systems are that delays in processing are not possible; production sequences are invariant; little slack exists in methods, equipment, or personnel; and substitutions of supplies, equipment, or person-nel are limited. All of these things increase the likelihood of accidents. Redundancy, segrega-tion, diversity, and defence in depth must be de-signed into the system from the start (Rigbey 2013). Leveson (2012) argues that the chain of cau-sality leading to an accident is often opaque. The causal path to an accident will be “prepared by resident conditions that are latent effects of earli-er events or acts.” Thus, the length of the causal path depends to a large extent on the stopping-rule for seeking contributing causes: Do the causes stop with technical faults, or with operator “errors,” or do they extend back to management and design decisions? Regan (2010) makes this same argument but with specific reference to dams: […] chain-of-event models, such as a typical-ly defined failure mode or risk assessment event tree, oversimplify the causes of inci-dents and exclude many systemic factors and non-linear interactions. The failures of Teton, Silver Lake and Taum Sauk all had contribu-tions from systemic factors and non-linear in-teractions that were unrecognized prior to the failure. Our current dam safety programs are, in essence, trying to determine the safety of 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12 Vancouver, Canada, July 12-15, 2015  3 the dam by examining a few components of the dam, one component at a time. […]. Analysing individual components against a pre-scribed standard is insufficient to assure the safe-ty of dams. Reducing the risk associated with dams to a level that is as low as reasonably prac-ticable requires evaluating the dam as a complex system with interactions of sub-systems that may be difficult to recognize. 2. A SECOND-GENERATION APPROACH TO DAM SAFETY RISK To achieve Regan’s suggested goal of a new ap-proach to dam safety risk analysis, one needs to take a systems view of the function and failure of flow control in dam systems. This is contrary to recent decades’ separation of analysis according to different fields. However, it is more in accord-ance with the approach used when most dams were planned in earlier times. The specialties and methods of analysis used today are still absolute-ly required, but need to be supplemented with an improved overview of how things come together and influence each other.  This view of how things come together—including requirements (purpose), functions, and components—is a systems view. This is not a re-version to the old times of qualitative judgment, but demands more, not less, scientific study. Al-so the evolving notion of how risks arise moti-vates a new perspective and a new mind-set. Risk analysis is predicated on a systematic de-composition of all things that might go awry, and as a result it forces us to think about systems per-formance. The ‘new approach’ attempts to de-velop a systems-engineering approach into a practical methodology. To achieve this, the entire flow control sys-tem at dams needs to be considered, including not only spillways, but also all other waterways, including low-level (bottom) outlets and power intakes. In a dam system there are special ways and arrangements for how things are connected, forms, hierarchies, delay and feedback mechan-ics, systems dynamics, mathematically challeng-ing nonlinearities, and so on which lead to simu-lation approaches. Of course, not only the tech-nical parts of the system are important: organiza-tion, social context and human reliability are also a part of flow control systems (Figure 2).    Figure 2: Systems operations of a dam (adapted from Leveson 2011).  Dam systems for flow control comprise a broad set of components such as structures, equipment, sensors, communication facilities, personnel, management arrangements and poli-cies that enable the handling of water flows through the reservoir and past the relevant dam to the downstream reach of river (Leveson 2011). In this sense the totality created by man between the river upstream and the river downstream may be considered a flow control system. The dam body is an integral part of this system and, de-pending on the objectives of the modeler, it may or may not be included in the purpose-built sys-tem model for flow control being the object for certain types of system failures caused by slid-ing, internal or external erosion, or excessive set-tlements.  3. PROJECT  This new simulation approach to systems is be-ing applied to a cascade of hydropower stations operated by Ontario Power Generation (OPG) in northeast Ontario. The project is a cascade of four dams. The number of riparians in the river flood plain is few and there is no commercial riverine navigation, so potential loss of life is negligible and operational safety dominates the MANAGEMENTPolicy & plansOPERATIONSSTAFFControl Actions DataReportsControlvariablesPerformanceindicatorsControlsDisplaysHumanoperatorAutomated8controllerOpera:ng8sysetmSensorsActuatorsDisturbancesOutputsInputs12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12 Vancouver, Canada, July 12-15, 2015  4 considerations. The problem facing the engineer-ing analysis was to conceptualize a systems en-gineering model for the operation of the dams, generating stations, spillways, and other compo-nents; then to employ the model through stochas-tic simulation to investigate protocols for the safe operation of the project.  3.1. Generating stations Several hydroelectric generating stations were built in the basin during the twentieth century. In late 1989, Ontario Hydro purchased the plants and through its successor organization (OPG) has operated the facilities since.  Figure 3: Project layout  Transmission of electricity from the four stations is provided by a 230 kV transmission line from the lowest plant through the others and to the re-gional grid (Figure 3). When river flows exceed the maximum power flow of top reservoir, a bypass spillway structure, located 2.5 km to the east, is used to pass excess water into a bypass channel. The by-pass spillway comprises eight sluices with a ca-pacity of 4870cms. The waters so bypassed flow north and re-enter the river 17km downstream of the lowest GS. A secondary spillway structure constructed in the former river channel has a ca-pacity of 1217cms, and provides for diversion flow to the downstream GSs in case of shutdown of the upper units and to augment the bypass ca-pacity. The second dam in the sequence is concrete and incorporates intakes for a powerhouse, a spillway structure to bypass flows in the event of a sudden unit outage, and an earth-fill retaining structure located near the spillway. The head pond extends upstream about 7km, has a surface area of about 5.3km2 and a live storage of 106 mcm. The powerhouse contains four vertical Francis type turbine units, with the capacity to generate 52 MW at a rated flow of 190cms and operating head of 34.5m. The existing spillway structure consists of ten gated sluices, each 8.4m wide by 9.2m high, plus a 230m long overflow crest. The spillway structure was originally de-signed (prior to the construction of the bypass) to convey what was then the full design flood flow on the river. The third GS has a single concrete dam that incorporates the intakes for the power station and a spillway to bypass flows in the event of a plant outage. The head pond extends 4 km upstream. Its surface area is approximately 3 km2 and live storage is about 6.9mcm. The oper-ating head is 31m and the rated flow is 525cms. The final GS has a single concrete dam incorpo-rating an intake structure and spillway. The head pond is 5.6 km. It has a surface area of 1.2 km2, with live storage of 3.2mcm. The power plant is similar to those upstream but operates at 0.5m lower generating head.  3.2. Historic hydrologic series  Fifty year historic time series data on reservoir inflows are available and were used to generate stochastic reservoir inflows through time series forecasting (Figure 4). An autoregressive time-series model was fit to these historical data, and used to generate synthetic reservoir inflows over long periods of time. Modeling river systems by simulation has a long tradition in water and envi-GS 4GS 3GS 2GS 1OpsPWPWPWInflowSPSPSPPW SPAccessRoadBypassOutflow12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12 Vancouver, Canada, July 12-15, 2015  5 ronmental management, especially for economic optimization (Simonovic 2008).   Figure 4: Historic Daily Inflow Statistics 4. SIMULATION MODEL The objective of the modeling was to understand the systems interactions in the cascade, and the potential for accidents and failures caused by the interactions of components of that system. This includes: • Applying the systems modeling framework to understand the systems interactions in the cas-cade of four dams. • Formulating and constructing a model to characterize the hydrodynamics of the cascade including the dynamics of transport, storage, and power generation.  • Holistically integrating river basin hydrolo-gy, routing of inflows through the reservoir sys-tem, operating rules and human factors of operat-ing the spillway, and the dam component fragili-ties (structural, mechanical and electrical). • Generating stochastic time series by using the historic inflow time series to forecast inflows for several thousand years and multiple replications to identify unforeseen chain of events that could lead to accidents and failures. • Reviewing the current operating rules to de-termine whether further optimization techniques can be adopted to improve the power generation capabilities of the system. • Modeling inherent disturbances (lightening, seismic, floating ice, grid disturbances and de-bris) via a probabilistic framework. • Incorporating human reliability analysis (HRA) into the model by using expert judgment and available data to estimate human reliability probabilities on spillway gate and possibly other operations. 4.1. The system model The general model interface with the salient as-pects of the physical system being modeled was developed. When the simulation is started, the software iterates over many years (millions) of performance and evaluates the long history of the system, saving selected results for subsequent analysis. Initial work had been based on the Matlab™ software platform and its associated Simulink™ package. However, with the proliferation of commercial off-the-shelf party simulation en-gines at least as well optimized for engineering reliability, other alternatives were evaluated. Ul-timately, the choice was made to build the model on the GoldSim™ platform. While this platform is less powerful than some of the others re-viewed, it had the advantage of simplicity. 4.2. Normal operations and power generation Under normal operations, water flows for the GSs are provided from the uppermost reservoir. The water level is normally within the operating headwater level range. The limit of the headwa-ter level is the “absolute maximum operating level.” The difference between the absolute max-imum and maximum operating levels is the flood allowance, which is used to hold water in ex-treme conditions to reduce downstream flooding. The storage between the absolute minimum and minimum operating levels is used if a system en-ergy emergency occurs. Under normal operating conditions with equivalent discharges at each sta-tion, the full operating range would rarely be uti-lized. Under normal operating conditions, the out-flow from the uppermost reservoir passes through all the GSs. During any outage of a GS, the spillway at the station experiencing the out-age will be operated to pass the flow to the other GSs. During high river flow conditions (e.g., 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12 Vancouver, Canada, July 12-15, 2015  6 spring runoff) when the uppermost reservoir is near its maximum limit, the spillway into the di-version is operated in conjunction with GS to pass the full river flow. 4.3. Gate operations Gated spillways are designed to engineering standards, however with aging, exposure, pre-ventative maintenance, and lack of frequent op-erations they become more vulnerable to non-availability. On-demand failures of gated spill-ways may be caused by a gate component that can be repaired in minutes to hours or a compo-nent that may cause complete failure of the gate system and unexpected release of the reservoir containment. Gated spillways contain a complex integra-tion of structural, mechanical, and electrical (SME) components that must operate on de-mand. There are a total of 10 sluices with gates. Two of the 10 sluices (Nos. 1 and 2) are along-side the generating station and open into the riv-er, while 8 are nearly 3.2 km upstream and open into the bypass. Sluices 1, 2, 3, 4, 7 and 8 are remotely controlled. Sluices 5, 6, 9 and 10 are locally controlled by the operator agents at the gate. The sluices are numbered from right to left looking upstream at the dam.  The model includes the effects of hydraulic loads, debris, ice, and operator actions. These loads are related to gate availability through tra-ditional fragility curve relations. The inputs to the gate operations simulation at any time step are the respective states of the input and disturb-ance variables. The outputs are the gate availabil-ities (probability of use on demand). Gate operations are also affected by instru-mentation, supervisory control and data acquisi-tion (SCADA) systems and controls. The simula-tion approach is well suited to uncovering the implications of component performance assump-tions on overall systems operations. 5. DISTURBANCES Sometimes in the course of the operation of a dam system an extraordinary event occurs, such as an earthquake, an earth or rock slide into the reservoir or conveyance works, a major fire in the drainage area, or the like, at a time which cannot be anticipated, but that may affect dam operations or safety. Within the simulation, such events are treated as exogenous disturbances. Disturbances, in principle, include a broad varie-ty of phenomena, both of natural origin such as lightening strikes affecting power supplies or in-strumentation, or of anthropogenic origin such as the grid being unable to accept power and thus the powerhouse waterway having diminished discharge capacity, or operational incidents or accidents such as powerhouse fires.   Figure 5. Simulated effect of disturbances: red is res-ervoir inflow, blue is SCADA controlled spill, and green is structural binding of gate.  A disturbance of major concern in the pro-ject is ice build up. The time series in Figure 6 shows the simulated ice build up on the gates of any of the dams during one randomly simulated year. The stochastic input for this simulation is the variability in daily temperature generated from a statistical time series identified to temper-ature data over the past century. Daily tempera-tures are simulated, and Stefan’s Equation (USACE 2002) is used to calculate ice thickness on the reservoir.  The disturbances included in the present model are limited to external loss of grid availa-bility, lightening (affecting grid availability), floating ice, icing on structures, instrument or SCADA mis-operation, and human error. Each is treated as a Poisson process of time, possibly 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12 Vancouver, Canada, July 12-15, 2015  7 with a corresponding probability distribution of magnitude.   Figure 6. Ice build up in reservoir based on Stefan Equation, red curve is ice build up in cm, green curve is simulated temperature in C. 6. HUMAN RELIABILITY  It comes as no surprise that human actions are a source of vulnerability for industrial systems, giving rise to modern methods and models of human reliability analysis (HRA). HRA aims to deepen the examination of the human factor in the workplace, and is important due to the con-tributions of humans to the resilience of systems and to possible adverse consequences of human errors or oversights—especially when the human is a crucial part of the large systems.  HRA involves qualitative and quantitative methods to assess human contribution to risk. There are many and varied methods available for HRA, with some safety critical domains develop-ing industry focused methods. Human error has been classified by Reason (1990) into three lev-els: behavioral, contextual, and conceptual. Rea-son concludes that the first two types include the different errors that can result from the same process but the conceptual level leads to under-standing the causal mechanisms using more theo-ry than observation.  The current simulation effort using the SPAR-H approach to HRA (Gertman et al. 2005). A NASA report (Chandler et al. 2006) re-port documents many of the HRA methodologies that have been developed to estimate human er-ror potential. The report compares of these meth-ods and provides a selection of four methods that could be used for the NASA risk analysis pro-gram. The report recommends for NASA HRA: THERP (Swain and Guttmann 1983), CREAM (Hollnagel 1998), NARA (Kirwan 1994), and SPAR-H. The report recommends that all the four methods be deployed and their results doc-umented to be able to select the best suitable program for HEP estimation for future NASA endeavors. In regards to spillway systems, these HRA methods are focused to nuclear power plants and will need significant adaptations be-fore they could be applied to the operation of spillway subsystems. 7. CONCLUSIONS In the simulations to date, among the drivers to which the frequencies of accidents and failures are most sensitive appear to be: (1) loss of re-mote control through communications or other breakdowns, (2) incorrect operations decisions that fail to establish the appropriate spill profile for the prevailing conditions, (3) loss of power supplies or other supporting or auxiliary services, (4) loss of access to the dam in emergency, (5) excessive weather, (6) common cause disruptions such as fire, (7) failure of control or instrumenta-tion, (8) lack of qualified personnel to provide an emergency response, and (9) failure of the gates or supporting structures.  Obviously, the observation that these appear to contribute to high frequencies of accidents and failures depends on the input assumptions about rates, stochastic processes, and fragilities that the modeling has made. So, at this point no generic conclusions are warranted about the causes of operational problems from these results. Simulation has proven a promising approach to modeling the reliability of dam systems and supporting a second-generation evolution for dam safety risk analysis. The reasons appear to be that simulation allows for time in failure anal-ysis, it incorporates feedback on operating pro-cedures and human reliability in systems func-tion, it provides a way to fuse models across dif-ferent technological and human systems, and it provides for the chaining of precursors in acci-dent sequences. 0246810121416182022242628Jan 2013 Apr 2013 Jul 2013 Oct 2013 Jan 2014Steffans_Ice_Equation (cm)Time -30-20-100102030Selector1 (C)Result2Realization #14Steffans_Ic _Equation Selector112th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12 Vancouver, Canada, July 12-15, 2015  8 8. REFERENCES Chandler, F., Chang, J., and Mosleh, A. (2006). Hu-man Reliability Analysis Methods Selection Guidance for NASA. OSMA Technical Report, NASA, Washington DC. Gertman, D., Blackman, H. S., Marble, J., Byers, J., Haney, L. N., and Smith, C. (2005). The SPAR-H - Human Reliability Analysis Method. U.S. Nuclear Regulatory Commission, Washington DC. Hazen, A. (1914). “Storage to be provided in im-pounding reservoirs for municipal water sup-ply.” Trans. Amer. Soc. Civil Eng., 77, 1539–1569. Hollnagel, E. (1998). Cognitive reliability and error analysis method: CREAM. Elsevier, Oxford  ; New York. Hufschmidt, M. M. (1966). Simulation techniques for design of water-resource systems. Harvard University Press, Cambridge. Kirwan, B. (1994). A Guide To Practical Human Re-liability Assessment. CRC Press. Leveson, N. G. (2011). “Applying systems thinking to analyze and learn from events.” Safety Sci-ence, 49(1), 55–64. Leveson, N. G. (2012). Engineering a Safer World: Systems Thinking Applied to Safety. The MIT Press. McCann, M. (2012). “Performance of hydraulic sys-tesm.” National Performance of Dams Pro-gram, National Performance of Dams Program, Montreal. Perrow, C. (1999). Normal Accidents: Living with High-Risk Technologies. Princeton University Press. Regan, P. (2010). “Dams as systems — a holistic ap-proach to dam safety.” US Society on Dams, Sacramento. Rigbey, S. (2013). “BC Hydro Spillway Gate Relia-bility Program.” HydroVision International, Denver. Simonovic, S. P. (2008). Managing Water Resources: Methods and Tools for a Systems Approach. Routledge. Swain, A. D., and Guttmann, H. E. (1983). Handbook of Human Reliability with Emphasis on Nucle-ar Power Plant Applications. Washington, DC. USACE. (2002). Ice Engineering Manual. US Army Corps of Engineers, Hanover NH. Chandler, F., Chang, J., and Mosleh, A. (2006). Hu-man Reliability Analysis Methods Selection Guidance for NASA. OSMA Technical Report, NASA, Washington DC. Gertman, D., Blackman, H. S., Marble, J., Byers, J., Haney, L. N., and Smith, C. (2005). The SPAR-H - Human Reliability Analysis Method. U.S. Nuclear Regulatory Commission, Washington DC. Hazen, A. (1914). “Storage to be provided in im-pounding reservoirs for municipal water sup-ply.” Trans. Amer. Soc. Civil Eng., 77, 1539–1569. Hollnagel, E. (1998). Cognitive reliability and error analysis method: CREAM. Elsevier, Oxford  ; New York. Hufschmidt, M. M. (1966). Simulation techniques for design of water-resource systems. Harvard University Press, Cambridge. Kirwan, B. (1994). A Guide To Practical Human Re-liability Assessment. CRC Press. Leveson, N. G. (2011). “Applying systems thinking to analyze and learn from events.” Safety Sci-ence, 49(1), 55–64. Leveson, N. G. (2012). Engineering a Safer World: Systems Thinking Applied to Safety. The MIT Press. McCann, M. (2012). “Performance of hydraulic sys-tesm.” National Performance of Dams Pro-gram, National Performance of Dams Program, Montreal. Perrow, C. (1999). Normal Accidents: Living with High-Risk Technologies. Princeton University Press. Regan, P. (2010). “Dams as systems — a holistic ap-proach to dam safety.” US Society on Dams, Sacramento. Rigbey, S. (2013). “BC Hydro Spillway Gate Relia-bility Program.” HydroVision International, Denver. Simonovic, S. P. (2008). Managing Water Resources: Methods and Tools for a Systems Approach. Routledge. Swain, A. D., and Guttmann, H. E. (1983). Handbook of Human Reliability with Emphasis on Nucle-ar Power Plant Applications. Washington, DC. USACE. (2002). Ice Engineering Manual. US Army Corps of Engineers, Hanover NH.     

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