Reliability mapping for FBR: Adapting generic data for enhanced safety assessments

Abstract

Accurate probabilistic safety assessments (PSA) for the Fast Breeder Reactor (FBR) are hindered by limited plant-specific failure data and its unique design, including sodium coolant and electromagnetic control rods. This study develops a novel methodology to adapt generic reliability data from legacy sodium-cooled fast reactors (BN-600, Phénix, Monju) to FBR-specific applications. The approach integrates systematic data collection, classification, and normalization with Bayesian updating, expert elicitation, and rigorous validation through sensitivity and uncertainty analyses. Case studies on critical subsystems—sodium pumps, steam generator tube rupture, intermediate heat exchanger tube failure, sodium–water reaction events, and control rods—demonstrate the methodology’s ability to refine failure probability estimates by accounting for FBR’s enhanced materials, optimized operating conditions, and advanced safety systems. Validation against Indira Gandhi Centre for Atomic Research (IGCAR) test data and international benchmarks ensures robustness and regulatory compliance. This methodology significantly enhances PSA accuracy, supporting risk-informed decision-making and maintenance planning for FBR. By tailoring generic data to FBR’s unique operational context, the framework provides a scalable solution for next-generation reactors, contributing to improved safety and operational efficiency. Future work will incorporate FBR’s operational data to further refine reliability estimates.