Nevena Šipčić , Pablo García de Quevedo Iñarritu , Mohsen Kohrangi , Dimitrios Vamvatsikos , Paolo Bazzurro
{"title":"Practical approach to Hazard-Consistent fragility curve estimates using Bayesian updating","authors":"Nevena Šipčić , Pablo García de Quevedo Iñarritu , Mohsen Kohrangi , Dimitrios Vamvatsikos , Paolo Bazzurro","doi":"10.1016/j.nucengdes.2025.114029","DOIUrl":null,"url":null,"abstract":"<div><div>Seismic fragility curves provide the probability of exceedance of a given damage state, should different levels of ground motion intensity be experienced at the site where the structure, or component, is located. Such curves are often derived via multiple nonlinear response history analyses (NLRHA) using sets of “suitable” ground motions that, in line with the best practice, should be consistent with the seismic hazard at the site. Based on the selected sets of records, one can estimate fragility functions that are often assumed to follow a lognormal distribution defined by two parameters, i.e., the logarithmic mean (µ) and the logarithmic standard deviation (β). Our focus is on estimating them using a state-of-the-art approach that involves hazard-consistent record selection via Conditional Spectrum and multiple stripe analysis. However, this approach usually requires many NLRHAs, with high computational costs, especially for the complex structural models typical of the nuclear industry. This study investigates the optimal number of ground motions and intensity levels required to keep the computational burden acceptable without compromising accuracy. To do so, we adopt a Bayesian framework with Markov chain Monte Carlo simulation and Metropolis–Hasting sampling. Our findings show that this approach effectively helps analysts best allocate computational resources while ensuring acceptable accuracy in estimating the probability of reaching or exceeding the considered damage states.</div></div>","PeriodicalId":19170,"journal":{"name":"Nuclear Engineering and Design","volume":"437 ","pages":"Article 114029"},"PeriodicalIF":1.9000,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nuclear Engineering and Design","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0029549325002067","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NUCLEAR SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Seismic fragility curves provide the probability of exceedance of a given damage state, should different levels of ground motion intensity be experienced at the site where the structure, or component, is located. Such curves are often derived via multiple nonlinear response history analyses (NLRHA) using sets of “suitable” ground motions that, in line with the best practice, should be consistent with the seismic hazard at the site. Based on the selected sets of records, one can estimate fragility functions that are often assumed to follow a lognormal distribution defined by two parameters, i.e., the logarithmic mean (µ) and the logarithmic standard deviation (β). Our focus is on estimating them using a state-of-the-art approach that involves hazard-consistent record selection via Conditional Spectrum and multiple stripe analysis. However, this approach usually requires many NLRHAs, with high computational costs, especially for the complex structural models typical of the nuclear industry. This study investigates the optimal number of ground motions and intensity levels required to keep the computational burden acceptable without compromising accuracy. To do so, we adopt a Bayesian framework with Markov chain Monte Carlo simulation and Metropolis–Hasting sampling. Our findings show that this approach effectively helps analysts best allocate computational resources while ensuring acceptable accuracy in estimating the probability of reaching or exceeding the considered damage states.
期刊介绍:
Nuclear Engineering and Design covers the wide range of disciplines involved in the engineering, design, safety and construction of nuclear fission reactors. The Editors welcome papers both on applied and innovative aspects and developments in nuclear science and technology.
Fundamentals of Reactor Design include:
• Thermal-Hydraulics and Core Physics
• Safety Analysis, Risk Assessment (PSA)
• Structural and Mechanical Engineering
• Materials Science
• Fuel Behavior and Design
• Structural Plant Design
• Engineering of Reactor Components
• Experiments
Aspects beyond fundamentals of Reactor Design covered:
• Accident Mitigation Measures
• Reactor Control Systems
• Licensing Issues
• Safeguard Engineering
• Economy of Plants
• Reprocessing / Waste Disposal
• Applications of Nuclear Energy
• Maintenance
• Decommissioning
Papers on new reactor ideas and developments (Generation IV reactors) such as inherently safe modular HTRs, High Performance LWRs/HWRs and LMFBs/GFR will be considered; Actinide Burners, Accelerator Driven Systems, Energy Amplifiers and other special designs of power and research reactors and their applications are also encouraged.