Journal of Shanghai Jiao Tong University

Journal of Shanghai Jiaotong University >

2023 , Vol. 57 >Issue 10: 1250 - 1260

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2022.359

Transportation Engineering

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

  • Yiqin CHEN ,
  • Shuping HUANG
Expand
  • School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Received date: 2022-09-13

  Revised date: 2022-12-09

  Accepted date: 2022-12-14

  Online published: 2023-10-31

Fold

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)

Cite this article

Yiqin CHEN , Shuping HUANG . An Evaluation Method for Link Importance Based on Seismic Resilience of Road Network[J]. Journal of Shanghai Jiaotong University, 2023 , 57(10) : 1250 -1260 . DOI: 10.16183/j.cnki.jsjtu.2022.359

References

[1] BARKER K, RAMIREZ-MARQUEZ J E, ROCCO C M. Resilience-based network component importance measures[J]. Reliability Engineering and System Safety, 2013(117): 89-97.
[2] 吕彪, 高自强, 刘一骝. 道路交通系统韧性及路段重要度评估[J]. 交通运输系统工程与信息, 2020, 20(2): 114-121.
[2] LV Biao, GAO Ziqiang, LIU Yiliu. Evaluation of road transportation system resilience and link importance[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(2): 114-121.
[3] LI R Y, GAO Y. On the component resilience importance measures for infrastructure systems[J]. International Journal of Critical Infrastructure Protection, 2022(36): 100481.
[4] 潘星, 蒋卓, 杨艳京. 基于弹性的体系组件重要度及恢复策略[J]. 北京航空航天大学学报, 2017, 43(9): 1713-1720.
[4] PAN Xing, JIANG Zhuo, YANG Yanjing. Resilience-based component importance and recovery strategy for system-of-systems[J]. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43(9): 1713-1720.
[5] ZHANG Y B, KANG R, LI R Y, et al.Resilience-based component importance measures for complex networks[C]//2016 Prognostics and System Health Management Conference (PHM-Chengdu). Chengdu, China: IEEE, 2016: 1-6.
[6] WEN M L, CHEN Y B, YANG Y, et al. Resilience-based component importance measures[J]. International Journal of Robust and Nonlinear Control, 2020, 30(11): 4244-4254.
[7] GAO Z Q, LV B, GUAN X Y, et al. Connectivity resilience assessment of urban road networks under earthquake based on Bayesian network[C]// 2020 IEEE 23rd International Conference on Intelligent Transportation Systems. Rhodes, Greece: IEEE, 2020: 1-6.
[8] 何祥, 袁永博, 周方, 等. 道路网络路段韧性重要度的EFAST评价方法[J]. 安全与环境学报, 2023, 23(8): 675-681.
[8] HE Xiang, YUAN Yongbo, ZHOU Fang, et al. An EFAST-based evaluation method for resilience importance of road-network links[J]. Journal of Safety and Environment, 2023, 23(8): 675-681.
[9] 陈舞, 王浩, 张国华, 等. 基于T-S模糊故障树和贝叶斯网络的隧道坍塌易发性评价[J]. 上海交通大学学报, 2020, 54(8): 820-830.
[9] CHEN Wu, WANG Hao, ZHANG Guohua, et al. Evaluation of tunnel collapse susceptibility based on T-S fuzzy fault tree and Bayesian network[J]. Journal of Shanghai Jiao Tong University, 2020, 54(8): 820-830.
[10] HUANG K Q, GU Y K, LIANG L Q. Reliability risk evaluation method for complex mechanical system based on optimal Bayesian network[J]. Journal of Donghua University (English Edition), 2016, 33(2): 177-182.
[11] HENRY D, RAMIREZ-MARQUEZ J E. Generic metrics and quantitative approaches for system resilience as a function of time[J]. Reliability Engineering & System Safety, 2012(99): 114-122.
[12] QI T, MING Y, ALTYNGUL Z. A dynamic Bayesian network-based approach to resilience assessment of engineered systems[J]. Journal of Loss Prevention in the Process Industries, 2020(65): 104152.
[13] 陈轶钦, 黄淑萍. 基于动态贝叶斯网络的道路交通系统抗震韧性评价[J]. 地震研究, 2023, 46(2): 280-290.
[13] CHEN Yiqin, HUANG Shuping. Seismic resilience evaluation of road traffic system based on dynamic Bayesian network[J]. Journal of Seismological Research, 2023, 46(2): 280-290.
[14] 张洁. 城市应急道路网络构成及抗震可靠性研究[D]. 青岛: 中国海洋大学, 2013.
[14] ZHANG Jie. Building of urban emergency road network and seismic reliability research[D]. Qingdao: Ocean University of China, 2013.
[15] 方东平, 李全旺, 李楠, 等. 社区地震安全韧性评估系统及应用示范[J]. 工程力学, 2020, 37(10): 28-44.
[15] FANG Dongping, LI Quanwang, LI Nan, et al. An evaluation system for community seismic resilience and its application in a typical community[J]. Engineering Mechanics, 2020, 37(10): 28-44.
Options
Outlines

/

〈 〉