Human Reliability Analysis-Based Method for Manual Fire Suppression Analysis in an Integrated Probabilistic Risk Assessment

Abstract

Abstract Fire is one of the most critical initiating events that can lead to core damage in nuclear power plants (NPPs). To evaluate the potential vulnerability of plants to fire hazards, fire probabilistic risk assessment (PRA) is commonly conducted. Manual fire protection features, performed by the first responders (e.g., fire brigade), play a key role in preventing and mitigating fire-induced damage to the plant systems. In the current fire PRA methodology of NPPs, there are two main gaps in the modeling of manual fire protection features: (i) the quantification of the first responder performance is solely based on empirical data (industry-wide historical fire events), and so the plant-specific design and conditions cannot be explicitly considered; and (ii) interactions of first responders with fire propagation are not fully captured. To address these challenges, the authors develop a model-based approach, grounded on human reliability analysis (HRA) and coupled with the fire dynamics simulator (FDS), to model the first responder performance more realistically and consider the interface between the first responder performance and fire propagation more explicitly. In this paper, the HRA-based approach is implemented in an integrated PRA (I-PRA) methodological framework for fire PRA and applied to a switchgear room fire scenario of an NPP. The proposed model-based approach (a) adds more realism to fire PRA and so to risk assessment in NPPs and (b) provides opportunities for sensitivity and importance measure analyses with respect to design conditions; therefore, contributes to risk management in NPPs.

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