Mutual Integration of Classical and Dynamic PRA

Abstract

A new generation of dynamic methods has started receiving attention for nuclear reactor probabilistic risk assessment (PRA). These methods, which are commonly referred to as dynamic PRA (DPRA) methodologies, directly employ system simulators to evaluate the impact of timing and sequencing of events (e.g., failure of components) on accident progression. Compared to classical PRA (CPRA) methods, which are based on static Boolean logic structures such as fault trees and event trees (ETs), DPRA methods can provide valuable insights from an accident management perspective. However, as of today this class of methods has received limited attention in practical applications. One factor is DPRA research and development has progressed mostly as an alternative to state-of-practice CPRA methods (i.e., disconnected from currently employed PRA methods). This disconnect is addressed in this paper by presenting several algorithms that can be employed to bridge the gap between CPRA and DPRA. First, algorithms designed to identify differences between CPRA and DPRA results are presented. The identification process compares the CPRA ET sequence or the minimal cut sets (MCSs) obtained by CPRA with the set of transients simulated by the DPRA. If inconsistencies are observed, solutions are provided to incorporate these differences back into the CPRA by employing DPRA to inform existing CPRA. We performed this incorporation either probabilistically (e.g., by updating MCS probability) or topologically (by adding new branching conditions or sequences in the ET).

Keywords:

• Dynamic probabilistic risk assessment
• integration
• probabilistic risk assessment