An enhanced system reliability framework for regional seismic risk assessment considering inter-structural correlations

Authored by

Meng Jie Xiang, Meng Ze Lyu, Zhe Qu, Jun Chen, Zhen Hua Nie

Abstract

Regional seismic risk assessment (RSRA) is crucial for enhancing urban seismic resilience and guiding disaster reduction strategies. However, correlations in ground motion intensity measures (IMs) and structural damage measures (DMs) across buildings can significantly affect assessment outcomes, and adequately capturing these correlations remains a major challenge. This study presents an enhanced system reliability-based RSRA framework, which reformulates the problem as a dependent k -out-of- n system reliability model, and evaluates the exceedance probability of the number of damaged buildings within a building cluster. While analytical solutions are provided for structurally independent cases, a numerical scheme integrating Gaussian copula sampling with the probability density evolution method (PDEM) is developed for correlated cases. The numerical scheme is validated through comparisons with both analytical solutions and Monte Carlo simulations. The framework is demonstrated by a case study of 29,461 buildings in Shanghai, China, subjected to a magnitude 7.0 earthquake scenario. The probabilities of exceeding four damage states of the building cluster are evaluated to quantify the effect of inter-structural IM and DM correlations on regional seismic risk.

Details

Organisation(s): Institute for Risk and Reliability
External Organisation(s): University of Jinan
China Earthquake Administration (CEA)
Tongji University
Department of Education of Guangdong Province
Type: Article
Journal: Reliability Engineering and System Safety
Volume: 274
ISSN: 0951-8320
Publication date: 15.02.2026
Publication status: E-pub ahead of print
Peer reviewed: Yes
ASJC Scopus subject areas: Safety, Risk, Reliability and Quality, Industrial and Manufacturing Engineering
Sustainable Development Goals: SDG 11 - Sustainable Cities and Communities
Electronic version(s): https://doi.org/10.1016/j.ress.2026.112402 (Access: Closed )