[1]董正方,李乐意,昝子卉,等.城市轨道交通系统震后修复顺序优化[J].长安大学学报(自然科学版),2025,45(6):216-226.
　DONG Zheng-fang,LI Le-yi,ZAN Zi-hui,et al.Post-earthquake repair sequence optimization of urban rail transit system[J].Journal of Chang’an University (Natural Science Edition),2025,45(6):216-226.
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城市轨道交通系统震后修复顺序优化()
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长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
第45卷
期数:
2025年6期
页码:
216-226
栏目:
交通工程
出版日期:
2025-11-30

文章信息/Info

Title:
Post-earthquake repair sequence optimization of urban rail transit system
文章编号:
1671-8879(2025)06-0216-11
作者:
董正方1; 李乐意1; 昝子卉2; 代鹏翔1; 李运华1
(1. 河南大学 建筑工程学院,河南 开封 475004; 2. 广州地铁设计研究院股份有限公司,广东 广州 510010)
Author(s):
DONG Zheng-fang1;  LI Le-yi1;  ZAN Zi-hui2;  DAI Peng-xiang1;  LI Yun-hua1
(1. School of Civil and Architectural Engineering, Henan University, Kaifeng 475004, Henan, China; 2. Guangzhou Metro Design & Research Institute Co., Ltd., Guangzhou 510010, Guangdong, China)
关键词:
交通工程;  城市轨道交通系统;  修复顺序优化;  NSGA-Ⅱ
Keywords:
traffic engineering;  urban rail transit system;  repair sequence optimize;  NSGA-Ⅱ
分类号:
U239.5
文献标志码:
A
摘要:
为了提高城市轨道交通系统的抗震韧性,基于复杂网络理论和抗震韧性评估理论,对城市轨道交通系统震后结构修复顺序进行优化研究。首先,从单元失效情况、网络连通性、网络交通运输功能3个维度定义城市轨道交通系统的性能响应函数,并据此求其相应的恢复力,将其加权求和得到综合恢复力。其次,以单一维度恢复力最大为目标,建立城市轨道交通系统单目标优化模型,通过遗传算法来进行求解。进一步综合考虑多维度(例如三维度)恢复力最大建立城市轨道交通系统多目标优化模型,通过多目标遗传算法(例如改进的非支配排序遗传算法(NSGA-Ⅱ))进行求解。最后,以郑州市轨道交通系统网络为典型案例,对其地震后结构修复顺序进行优化,设置结构失效单目标优化、网络连通单目标优化、网络功能单目标优化、多目标优化、随机修复、偏好修复6种修复工况。研究结果表明:优化的修复顺序较随机修复的恢复力均有所提升,提升幅度为0.8%～12%; 多目标优化修复顺序的综合恢复力最大,较其他工况提升幅度为4%～6%; 通过优化震后结构的修复顺序可以有效提高城市轨道交通系统的抗震韧性,其中多目标优化可以得到系统综合恢复力最大的优化方案。研究成果可为城市轨道交通系统的震后抢修工作提供参考。
Abstract:
In order to improve the seismic resilience of urban rail transit system, based on complex network theory and seismic resilience evaluation theory, the post-earthquake structural repair sequence of urban rail transit system was optimized. Firstly, the performance response function of urban rail transit system was defined from three perspectives: unit failure, network connectivity and network transportation function. Based on this, the corresponding restoring force was obtained, and the comprehensive restoring force was obtained by weighted sum. Secondly, aiming at maximizing the single dimensional resilience, a single-objective optimization model of urban rail transit system was established and solved by genetic algorithm. Further, considering the maximum three-dimensional resilience, a multi-objective optimization model of urban rail transit system was established and solved by multi objective genetic algorithm(such as improved non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)). Finally, taking Zhengzhou rail transit network as a typical case, the post-earthquake structural repair sequence was optimized. Six repair conditions were set up, including single-objective optimization of structural failure, single-objective optimization of network connectivity, single-objective optimization of network function, multi-objective optimization, random repair and preference repair. The results show that the restoring force of the optimized repair sequence is higher than that of the random repair, with an increase of 0.8%-12%. Comprehensive restoring force of multi-objective optimization repair sequence is the largestand 4%-6% higher than other working conditions. Therefore, by optimizing the repair sequence of the post-earthquake structure, the seismic resilience ofurban rail transit system can be effectively improved, and the multi-objective optimization can obtain the optimization scheme with the largest comprehensive restoring force of the system. The research in this paper can provide reference for the post-earthquake repair work of urban rail transit system.8 tabs, 14 figs, 27 refs.

参考文献/References:

[1] 中华人民共和国交通运输部.2025年8月城市轨道交通运营数据速报[EB/OL].[2025-05-01]https://www.mot.gov.cn/fenxigongbao/yunlifenxi/202509/t20250909_4176362.html.
Ministry of Transport of the People's Republic China. Quick report of urban rail transit operation data in August 2025[EB/OL]. [2025-05-01]https://www.mot.gov.cn/fenxigongbao/yunlifenxi/202509/t20250909_4176362.html.
[2]IIDA H, HIROTO T, YOSHIDA N, et al. Damage to daikai subway station[J]. Soils and foundations,1996, 36(S): 283-300.
[3]刘爱文,夏 珊,徐 超.汶川地震交通系统震害及震后抢修[J].震灾防御技术,2008,3(3):243-250.
LIU Ai-wen, XIA Shan, XU Chao. Earthquake damage and post-earthquake repair of traffic system in Wenchuan earthquake[J]. Technology for Earthquake Disaster Prevention, 2008, 3(3): 243-250.
[4]YASHIRO K, KOJIMA Y, SHIMIZU M. Historical earthquake damage to tunnels in Japan and case studies of railway tunnels in the 2004 Niigataken-Chuetsu Earthquake[J]. Quarterly Report of RTRI, 2007, 48(3): 136-141.
[5]HOLLING C S. Resilience and stability of ecological systems[J]. Annual Review of Ecology and Systematics, 1973, 4(1): 1-23.
[6]BRUNEAU M, CHANG S E, EGUCHI R T, et al. A framework to quantitatively assess and enhance seismic resilience of communities[J]. Earthquake Spectra, 2003, 19(4): 733-752.
[7]刘 威,武千翔.考虑多组件的供水管网抗震韧性分析与韧性提升策略[J].地震研究,2023,46(2):271-279.
LIU Wei, WU Qian-xiang. Seismic resilience analysis of water distribution networks with multi-components and resilience improvement strategies[J]. Journal of Seismological Research,2023, 46(2): 271-279.
[8]宗成才,冀 昆,温瑞智,等.城市燃气管网三维度抗震韧性定量评估方法[J].工程力学,2021,38(2):146-156.
ZONG Cheng-cai, JI Kun, WEN Rui-zhi, et al. Quantitative evaluation method of three-dimensional seismic resilience of urban gas pipeline network[J]. Engineering Mechanics, 2021, 38(2): 146-156.
[9]吴秋婷.城市地铁网络韧性的评价及提升研究[D].北京:中国矿业大学,2022.
WU Qiu-ting. Evaluation and improvement of urban subway network resilience[D]. Beijing: China University of Mining and Technology, 2022.
[10]袁万城,王思杰,李怀峰,等.桥梁抗震智能与韧性的发展[J].中国公路学报,2021,34(2):98-117.
YUAN Wan-cheng, WANG Si-jie, LI Huai-feng, et al. Development of intelligence and resilience for bridge seismic design[J]. China Journal of Highway and Transport, 2021, 34(2): 98-117.
[11]黄 莺,刘梦茹,魏晋果.基于韧性曲线的城市地铁网络恢复策略研究[J].灾害学,2021,36(1):32-36.
HUANG Ying, LIU Meng-ru, WEI Jin-guo, et al. Research on urban subway network recovery strategy based on resilience curve[J]. Disasterology, 2021, 36(1): 32-36.
[12]LI Z L, JIN C, HU P, et al. Resilience-based transportation network recovery strategy during emergency recovery phase under uncertainty[J]. Reliability Engineering & System Safety, 2019, 188(8): 503-514.
[13]马 敏,胡大伟,舒 兰,等.城市轨道交通网络韧性评估及恢复策略[J].吉林大学学报(工学版),2023,53(2):396-404.
MA Min, HU Da-wei, SHU Lan, et al. Urban rail transit network resilience assessment and recovery strategy[J]. Journal of Jilin University(Engineering edition), 2023, 53(2): 396-404.
[14]AL-SHALABI M, ANBAR M, WAN T C. Energy efficient multi-hop path in wireless sensor networks using an enhanced genetic algorithm[J]. Information Sciences, 2019, 500(10): 259-273.
[15]王金贺,张晓红,曾建潮.非完美维修模型下的风电机组最优维修决策[J].计算机集成制造系统,2019,25(5):1151-1160.
WANG Jin-he, ZHANG Xiao-hong, ZENG Jian-chao. Optimal maintenance decision of wind turbine under imperfect maintenance model[J]. Computer Integrated Manufacturing Systems, 2019, 25(5): 1151-1160.
[16]杨国俊,毛建博,田 里,等.基于碎片化分区的桥梁网络震后修复优先级分析与优化[J].工程力学,2024,41(5):211-223.
YANG Guo-jun, MAO Jian-bo, TIAN Li, et al. Analysis and optimization of post-earthquake restoration priority of bridge network upon fragmentation[J]. Engineering Mechanics, 2024, 41(5): 211-223.
[17]HAN X, YANG D Y, FRANGOPOL D M. Risk-based life-cycle optimization of deteriorating steel bridges: Investigation on the use of novel corrosion resistant steel[J]. Advances in Structural Engineering, 2021, 24(8): 1668-1686.
[18]寇 峥,李 宁.基于NSGA-Ⅱ的城市桥梁系统震后可恢复性分析与优化[J].工程力学,2021,38(3):148-158,180.
KOU Zheng, LI Ning. Study on earthquake resilience analysis and optimization for urban bridge network system based on NSGA-Ⅱ algorithm[J]. Engineering Mechanics, 2021, 38(3): 148-158, 180.
[19]李昊昌,张 燕,张雨馨,等.基于改进NSGA-Ⅱ的多目标路面养护决策优化研究[J].兰州交通大学学报,2023,42(6):29-36.
LI Hao-chang, ZHANG Yan, ZHANG Yu-xin, et al. Research on multi-objective road maintenance decision optimization method based on improved fast NSGA-Ⅱ[J]. Journal of Lanzhou Jiaotong University, 2023, 42(6): 29-36.
[20]高培超,王昊煜,宋长青.多目标优化NSGA系列算法与地理决策:原理、现状与展望[J].地球信息科学学报,2023,25(1):25-39.
GAO Pei-chao, WANG Hao-yi, SONG Chang-qing, et al. Multi-objective optimization NSGA series algorithms and geographic decision-making: Principle, current situation and prospect[J].Journal of Earth Information Science, 2023, 25(1): 25-39.
[21]戴理朝,康 哲,陈 瑞,等.基于NSGA-Ⅲ的桥梁网络多目标维修决策优化研究[J].土木工程学报,2024,57(5):41-52.
DAI Li-zhao, KANG Zhe, CHEN Rui, et al. Study on multi-objective maintenance decision optimization of bridge networks based on NSGA-Ⅲ[J]. China Civil Engineering Journal, 2024, 57(5): 41-52.
[22]CIMELLARO G P, FUMO C, REINHORN A, et al. Seismic resilience of health care facilities[J]. Anidis, 2008, 2(4): 64-70.
[23]李 婷,李乐天,毛新华,等.基于复杂网络理论的公交站点便捷性评价方法[J].长安大学学报(自然科学版),2025,45(3):141-151.
LI Ting, LI Le-tian, MAO Xin-hua, et al. Convenience evaluation method of bus stops based on complex network theory[J]. Journal of Chang an University(Natural Science Edition), 2025, 45(3): 141-151.
[24]范世杰,游 丹,侯本伟.基于网络效率的城市轨道交通网络震后性能评估[J].防灾减灾工程学报,2022,42(6):1165-1173,1190.
FAN Shi-jie, YOU Dan, HOU Ben-wei. Post-earthquake performance evaluation of urban rail transit network based on network efficiency[J]. Journal of Disaster Prevention and Mitigation Engineering, 2022, 42(6): 1165-1173, 1190.
[25]吕 彪,管心怡,高自强.地铁网络服务韧性评估与最优恢复策略[J].交通运输系统工程与信息,2021,21(5):198-205,221.
LYU Biao, GUAN Xin-yi, GAO Zi-qiang. Subway network service resilience assessment and optimal recovery strategy[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(5): 198-205, 221.
[26]Federal Emergency Management Agency. Multi-hazard loss estimation methodology, earthquake model, hazus-MH 2.1 technical manual[R]. Washington DC: Federal Emergency Management Agency, 2012.
[27]DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multi objective genetic algorithm: NSGA-Ⅱ[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197.

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备注/Memo

备注/Memo:
收稿日期:2025-05-24
基金项目:河南省自然科学基金项目(242300421433); 中国博士后科学基金项目(2024M750780); 中建六局科技研发计划项目(CSCEC6B-2024-Z-7)
作者简介:董正方(1980-),男,河南滑县人,教授,工学博士,E-mail:dzf@henu.edu.cn。
通讯作者:李运华(1980-),男,河南项城人,高级实验师,E-mail:24561591@qq.com。
更新日期/Last Update: 2025-12-20