TY - GEN
T1 - Global sensitivity analysis to rank parameters of stress corrosion cracking in the Spatio-Temporal Probabilistic Model of loss of coolant accident frequencies
AU - Cheng, Wen Chi
AU - Ding, Chenghao
AU - O'Shea, Nicholas
AU - Sakurahara, Tatsuya
AU - Schumock, Grant
AU - Mohaghegh, Zahra
AU - Reihani, Seyed
AU - Kee, Ernie
N1 - Publisher Copyright:
© 2017 by American Nuclear Society. All rights reserved.
PY - 2017
Y1 - 2017
N2 - This research conducts Global Sensitivity Analysis (Global SA) on the Spatio-Temporal Probabilistic methodology, developed for steam generator rupture caused by Stress Corrosion Cracking (SCC), to rank the physical causal factors with respect to their influence on the probability of rupture within the lifetime of a nuclear power plant (NPP). The Spatio-Temporal Probabilistic Methodology integrates two types of models: (1) Markov Model to depict the renewal processes associated with the physical degradation and periodic maintenance for repair, and (2) The Probabilistic Physics of Failure (PPoF) model to explicitly incorporate physical failure mechanisms into the estimation of rupture probability. The Spatio-Temporal Probabilistic Methodology enables the possibility for explicitly including the effects of location-specific causal factors such as operating conditions (e.g., temperature, pressure, pH), maintenance quality, and material properties (e.g., yield strength and corrosion resistance), on the probability of a rupture occurrence. The ranking obtained from Global SA could help guide resource allocation to reduce the probability of Loss of Coolant Accidents (LOCAs) in NPPs.
AB - This research conducts Global Sensitivity Analysis (Global SA) on the Spatio-Temporal Probabilistic methodology, developed for steam generator rupture caused by Stress Corrosion Cracking (SCC), to rank the physical causal factors with respect to their influence on the probability of rupture within the lifetime of a nuclear power plant (NPP). The Spatio-Temporal Probabilistic Methodology integrates two types of models: (1) Markov Model to depict the renewal processes associated with the physical degradation and periodic maintenance for repair, and (2) The Probabilistic Physics of Failure (PPoF) model to explicitly incorporate physical failure mechanisms into the estimation of rupture probability. The Spatio-Temporal Probabilistic Methodology enables the possibility for explicitly including the effects of location-specific causal factors such as operating conditions (e.g., temperature, pressure, pH), maintenance quality, and material properties (e.g., yield strength and corrosion resistance), on the probability of a rupture occurrence. The ranking obtained from Global SA could help guide resource allocation to reduce the probability of Loss of Coolant Accidents (LOCAs) in NPPs.
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M3 - Conference contribution
AN - SCOPUS:85047790635
T3 - International Topical Meeting on Probabilistic Safety Assessment and Analysis, PSA 2017
SP - 840
EP - 846
BT - International Topical Meeting on Probabilistic Safety Assessment and Analysis, PSA 2017
PB - American Nuclear Society
T2 - 2017 International Topical Meeting on Probabilistic Safety Assessment and Analysis, PSA 2017
Y2 - 24 September 2017 through 28 September 2017
ER -