Spatial correlation in building seismic performance for regional resilience assessment

Abstract

Probabilistic seismic performance assessment method for buildings offers a valuable approach to simulate the broader regional impacts: economic losses, downtime, and casualties. A crucial aspect of this process entails accounting for the spatial correlation of building performances, aiming for an accurate estimation of the probability of extreme regional losses, such as the simultaneous collapse of buildings with similar structural characteristics. In this study, a correlation model based on a Gaussian random field is employed, and several key challenges associated with its application are addressed. In addition, efficiency of five different methods of selecting station records from the same earthquake scenario is compared. The minimum number of earthquake records necessary to achieve a stable correlation result is determined. Additionally, spatial correlations derived from different history earthquake events are compared. By addressing these critical issues, this research contributes to refining the reliability of probabilistic methods for regional resilience assessment.

Keywords

Seismic resilience / Spatial correlation / Seismic performance / Regional assessment / Functional recovery

Relevance to resilience

This article discusses the spatial correlation in seismic performances of building clusters, which is an important aspect of performing probabilistic assessment of regional seismic losses and community resilience.

CRediT authorship contribution statement

Tian You: Writing - original draft, Visualization, Methodology, Formal analysis, Conceptualization. Solomon Tesfamariam: Writing - review & editing, Supervision, Resources, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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