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A Review of the Progress with Statistical Models of Passive Component Reliability
Author(s) -
Bengt Lydell
Publication year - 2017
Publication title -
nuclear engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.737
H-Index - 40
eISSN - 2234-358X
pISSN - 1738-5733
DOI - 10.1016/j.net.2016.12.008
Subject(s) - piping , reliability (semiconductor) , probabilistic logic , engineering , reliability engineering , context (archaeology) , component (thermodynamics) , computer science , mechanical engineering , artificial intelligence , biology , thermodynamics , paleontology , power (physics) , physics , quantum mechanics
During the past 25 years, in the context of probabilistic safety assessment, efforts have been directed towards establishment of comprehensive pipe failure event databases as a foundation for exploratory research to better understand how to effectively organize a piping reliability analysis task. The focused pipe failure database development efforts have progressed well with the development of piping reliability analysis frameworks that utilize the full body of service experience data, fracture mechanics analysis insights, expert elicitation results that are rolled into an integrated and risk-informed approach to the estimation of piping reliability parameters with full recognition of the embedded uncertainties. The discussion in this paper builds on a major collection of operating experience data (more than 11,000 pipe failure records) and the associated lessons learned from data analysis and data applications spanning three decades. The piping reliability analysis lessons learned have been obtained from the derivation of pipe leak and rupture frequencies for corrosion resistant piping in a raw water environment, loss-of-coolant-accident frequencies given degradation mitigation, high-energy pipe break analysis, moderate-energy pipe break analysis, and numerous plant-specific applications of a statistical piping reliability model framework. Conclusions are presented regarding the feasibility of determining and incorporating aging effects into probabilistic safety assessment models

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