Abstract:

Dynamic simulation-based approaches for probabilistic risk assessment (PRA) offer several key advantages over traditional “static” techniques such as traditional event tree-fault tree based methods. For example, dynamic simulation approaches can more realistically represent event sequence and timing, provide a better representation of thermal hydraulic success criteria, and permit more detailed modeling of operator response. Version 2.0 of the Accident Dynamics Simulator paired with the Information, Decision, and Action cognitive model in a Crew context (ADS-IDAC) is one such dynamic method that shows promise for supporting nuclear power plant PRAs and other risk-informed applications. By linking a realistic nuclear plant thermal-hydraulic model with a crew behavior model, ADS-IDAC creates a rich simulation environment. The crew behavior model describes the operators’ preferences and tendencies, knowledge, and situation-response rules. ADS-IDAC generates a discrete dynamic event tree (DDET) by applying simple branching rules that reflect variations in crew responses to plant events and system status changes. Branches can be generated to simulate a variety of operator behaviors, including procedure execution speed and adherence, evolving situational assessments, and variations in plant control preferences. This is the second of two papers in this volume and describes the dynamic modeling capabilities supported by the ADS-IDAC Version 2.0 simulation platform and provides examples of their application.