Abstract
A supervisory control system (SCS) concept developed by Oak Ridge National Laboratory provides automated risk-informed decision-making capabilities with the ultimate
goal of significantly boosting plant availability while reducing dependency on human resources for multi-module advanced reactors. The decision-making process integrates online-monitoring systems, and the associated diagnostic and prognostics tools to continuously take into account the component health in an integrated probabilistic/deterministic meta model to capture the system behavior during a select set of postulated anticipated operational occurrence scenarios. The operational performance risk assessment (OPRA) approach is introduced to support SCS decisions probabilistically to minimize/prevent unnecessary trips and challenges to plant safety systems. OPRA identifies and ranks the success paths, combination of the non-safety systems and components, with the real-time failure data using event tree/fault tree method. OPRA does not interfere with the safety systems and adds a buffer zone to the existing probabilistic risk assessment (PRA) domain by minimizing the possible transients. In this work, failure scenarios of feedwater and turbine control valves are analyzed for ALMR PRISM (Power Reactor Innovative Small Module) design at full power. As an alternative to the default shutdown option, five and seven success paths (full and reduced power operation) are defined respectively within the OPRA framework.
