Seismic resilience(SR)has emerged as a critical focus in earthquake engineering to evaluate the ability of structures to endure,recover from,and adapt to seismic events.This study presents an entropy-based multicriter...Seismic resilience(SR)has emerged as a critical focus in earthquake engineering to evaluate the ability of structures to endure,recover from,and adapt to seismic events.This study presents an entropy-based multicriteria approach for selecting optimal intensity measures(IMs)to assess SR of structures.Eight representative IMs,derived from time histories and response spectrum are evaluated.Incremental dynamic analysis is con-ducted on a reinforced concrete structure,using engineering demand parameters such as the maximum interstory drift and floor acceleration to generate fragility curves via a probabilistic seismic demand model.The optimal IMs are identified through a multi-criteria decision-making process,with scores calculated using the entropy weight method to incorporate factors such as efficiency,proficiency,and uncertainty based on infor-mation entropy.An effective SR framework is derived from fragility results.The findings indicate that peak ground velocity and spectral IMs are the most effective,while energy-related IMs underestimate SR.The study highlights the importance of optimizing IMs for more accurate seismic resilience assessments.The proposed entropy-based multi-criteria approach is shown to be both reliable and effective for selecting optimal IMs in this context.展开更多
基金partly supported by Engineering Partners Inter-national,LLC,Richfield,MN 55423(PC13803,482842-58309).
文摘Seismic resilience(SR)has emerged as a critical focus in earthquake engineering to evaluate the ability of structures to endure,recover from,and adapt to seismic events.This study presents an entropy-based multicriteria approach for selecting optimal intensity measures(IMs)to assess SR of structures.Eight representative IMs,derived from time histories and response spectrum are evaluated.Incremental dynamic analysis is con-ducted on a reinforced concrete structure,using engineering demand parameters such as the maximum interstory drift and floor acceleration to generate fragility curves via a probabilistic seismic demand model.The optimal IMs are identified through a multi-criteria decision-making process,with scores calculated using the entropy weight method to incorporate factors such as efficiency,proficiency,and uncertainty based on infor-mation entropy.An effective SR framework is derived from fragility results.The findings indicate that peak ground velocity and spectral IMs are the most effective,while energy-related IMs underestimate SR.The study highlights the importance of optimizing IMs for more accurate seismic resilience assessments.The proposed entropy-based multi-criteria approach is shown to be both reliable and effective for selecting optimal IMs in this context.
