Abstract
Simulation has become more widely applied for analysis of dam safety flow control in recent years. Stochastic simulation has proven to be a useful tool that allows for easy estimation of the overall probability of dam overtopping failure. However, it is difficult to analyze “uncommon combinations of events” with a stochastic approach given current computing abilities, because (a) the likelihood of these combinations of events is small, and (b) there may not be enough simulated instances of these rare scenarios to determine their criticality. In this research, a Deterministic Monte Carlo approach is presented, which uses an exhaustive list of possible combinations of events (scenarios) as a deterministic input. System dynamics simulation is used to model the dam system interactions so that low-level events within the system can be propagated through the model to determine high-level system outcomes. Monte Carlo iterations are performed for each input scenario. A case study is presented with results from a single example scenario to demonstrate how the simulation framework can be used to estimate the criticality parameters for each combination of events simulated. The approach can analyze these rare events in a thorough and systematic way, providing a better coverage of the possibility space as well as valuable insights into system vulnerabilities.
Highlights
Typical dam safety assessments tend to focus on analyzing a subjectively chosen group of scenarios, often at or near the edge of the design envelope, analyzed probabilistically using event tree analysis.Event trees are a useful tool in quantification of probability, but are unable to model non-linear behavior, component interactions, and system feedbacks, which are often observed in dam failure.Event trees are unable to determine the dynamic system response to input conditions, which includes the resulting reservoir levels associated with a particular scenario
This research details a new simulation framework for systematic and dynamic analysis of combinations of events that can occur during dam system operation
The system dynamics simulation model represents interactions among a hierarchical system-of-systems, where events can be initiated within a low-level of the system to determine the resulting system behavior, including the value of the reservoir level over time
Summary
Typical dam safety assessments tend to focus on analyzing a subjectively chosen group of scenarios, often at or near the edge of the design envelope, analyzed probabilistically using event tree analysis.Event trees are a useful tool in quantification of probability, but are unable to model non-linear behavior, component interactions, and system feedbacks, which are often observed in dam failure.Event trees are unable to determine the dynamic system response to input conditions, which includes the resulting reservoir levels associated with a particular scenario. Typical dam safety assessments tend to focus on analyzing a subjectively chosen group of scenarios, often at or near the edge of the design envelope, analyzed probabilistically using event tree analysis. Event trees are a useful tool in quantification of probability, but are unable to model non-linear behavior, component interactions, and system feedbacks, which are often observed in dam failure. Event trees are unable to determine the dynamic system response to input conditions, which includes the resulting reservoir levels associated with a particular scenario. Regan [1] cites examples of dam failures, including Teton and Taum Sauk, in which non-linear behavior was observed, noting that event trees are too simplistic to anticipate the complex interactions occurring within various levels of a dam system. Baecher et al [5] present the framework for a methodology for achieving such an approach using stochastic simulation, with events occurring randomly in a continuous simulation based on fragility curves
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