Journal of Shanghai Jiao Tong University ›› 2023, Vol. 57 ›› Issue (10): 1250-1260.doi: 10.16183/j.cnki.jsjtu.2022.359

Special Issue: 《上海交通大学学报》2023年“交通运输工程”专题

• Transportation Engineering • Previous Articles     Next Articles

An Evaluation Method for Link Importance Based on Seismic Resilience of Road Network

CHEN Yiqin, HUANG Shuping()   

  1. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • Received:2022-09-13 Revised:2022-12-09 Accepted:2022-12-14 Online:2023-10-28 Published:2023-10-31
  • Contact: HUANG Shuping E-mail:sphuang@sjtu.edu.cn

Abstract:

The evalution of link resilience importance is essential for improving the seismic resilience level of the road network. Using resilience achievement worth (RAW) as evaluation index, an evaluation method of link importance based on seismic resilience of road networks was proposed. With the help of the bidirectional inference ability of dynamic Bayesian network (DBN), taking the initial DBN as the benchmark and the link connectivity at different times as the evidence, the resilience curve of the road network was updated, the RAW was calculated, and the link resilience importance at different times was evaluated. Taking the local road network in Shinan District of Qingdao as an example, the evaluation method of link importance was verified. The results show that the seismic resilience importance varies with each link at the same time. The resilience importance of the same link is positively correlated with maintenance rate. The resilience importance of different links varies in sensitivity to time. The proposed importance evaluation method redefines and quantifies the seismic resilience importance of links at different times, and identifies the links with high resilience importance and sensitivity to time. The post-earthquake recovery strategy that inclines the limited maintenance resources to these links and the pre-earthquake prevention strategy that reinforces the links with higher resilience importance can more efficiently improve the seismic resilience of the road network.

Key words: road network, seismic resilience, link resilience importance, dynamic Bayesian network (DBN), resilience achievement worth (RAW)

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