吉林大学学报(工学版) ›› 2023, Vol. 53 ›› Issue (6): 1695-1701.doi: 10.13229/j.cnki.jdxbgxb.20221352

• 交通运输工程·土木工程 • 上一篇    

数据驱动的公路桥梁网络全寿命抗震韧性评估

刘振亮1,2(),赵存宝1(),吴云鹏1,2,马迷娜1,2,马龙双1,2   

  1. 1.石家庄铁道大学 安全工程与应急管理学院，石家庄 050043
    2.河北省大型结构健康诊断与控制研究所，石家庄 050043
  • 收稿日期:2022-10-22 出版日期:2023-06-01 发布日期:2023-07-23
  • 通讯作者: 赵存宝 E-mail:liuzhenliangstd@163.com;zhaocb@stdu.edu.cn
  • 作者简介:刘振亮（1991-），男，讲师，博士.研究方向：基于机器学习的区域桥梁与城市公路桥梁网络抗震性能评估.E-mail：liuzhenliangstd@163.com
  • 基金资助:
    河北省自然科学基金青年基金项目(E2022210048);国能朔黄铁路发展有限责任公司技术开发项目(GJNY-20-230)

Life⁃cycle seismic resilience assessment of highway bridge networks using data⁃driven method

Zhen-liang LIU1,2(),Cun-bao ZHAO1(),Yun-peng WU1,2,Mi-na MA1,2,Long-shuang MA1,2   

  1. 1.School of Safety Engineering and Emergency Management，Shijiazhuang Tiedao University，Shijiazhuang 050043，China
    2.Structure Health Monitoring and Control Institute，Shijiazhuang Tiedao University，Shijiazhuang 050043，China
  • Received:2022-10-22 Online:2023-06-01 Published:2023-07-23
  • Contact: Cun-bao ZHAO E-mail:liuzhenliangstd@163.com;zhaocb@stdu.edu.cn

RICH HTML

 3   

PDF (PC)

677

摘要：

首先，提出了综合考虑各种因素（网络拓扑结构、桥梁性能退化、地震动等）和不确定性的公路桥梁网络抗震韧性评估框架。然后，分析了网络拓扑结构、桥梁抗震性能和路段功能特点，建立了震后公路桥梁网络时变功能模拟方法。接着，提出了基于人工神经网络的公路桥梁地震易损性快速分析方法。最后，以美国旧金山地区公路桥梁网络为例，采用本文方法分析了地震发生前、后公路桥梁网络的功能变化，据此揭示了全寿命服役期内抗震韧性的演化规律。结果表明，本文建立的数据驱动易损性模型拟合优度可达0.73，可以代替需要大量动力时程分析的易损性分析方法，且公路桥梁网络抗震韧性评估结果准确可靠，可以为防灾减灾提供决策依据。

关键词: 交通运输系统工程, 公路桥梁网络, 抗震韧性, 数据驱动易损性, 全寿命性能

Abstract:

Firstly， a seismic resilience assessment framework was proposed for highway bridge networks by comprehensively integrating various influencing factors （network topologies， deterioration effects of bridges， regional seismic hazards， etc.） and their uncertainties. Then， the network topologies， seismic performance of regional bridges and traffic functionalities of highway segments were analyzed， and integrated to establish a time-dependent post-disaster simulation of highway bridge networks. Subsequently， an artificial neural network based methodology was proposed for rapid seismic fragility assessment of regional bridges. Finally， the life-cycle seismic resilience of the highway bridge network in San Francisco， USA was analyzed as a case study， which reveals the evolution law of seismic resilience the service life. The results demonstrate the developed data-driven fragility model can act as a reliable surrogate to traditional time-consuming fragility methods， with the goodness of fit of 0.73. Consequently， the proposed methodology for the life-cycle seismic resilience of highway bridge networks is effective and accurate， providing decision-making strategies for disaster prevention and mitigation.

Key words: engineering of communication and transportation system, traffic, highway bridge network, seismic resilience, data-driven fragility, life-cycle seismic performance

中图分类号: 

  • U44

图1

基于数据驱动的公路桥梁网络时变抗震性能分析框架"

图2

全寿命服役期内公路桥梁网络模型"

图3

公路桥梁数据库中桥梁样本特征分布"

图4

ANN模型与IDA分析墩柱需求结果比较"

图5

算例公路桥梁网络示意图"

图6

区域桥梁地震损伤分布结果"

表1

公路损伤状态相关的残余通行能力和自由流速度"

公路损伤状态LD残余功能百分比/%
γcγv
未破坏（LD<0.5）100100
轻微破坏（0.5≤LD<1.0）10075
中等破坏（1.0≤LD<1.5）7550
严重破坏（1.5≤LD<∞）5050
完全破坏（LD=∞）00

图7

全寿命服役期内算例公路桥梁网络抗震韧性"

1 Hosseini S, Barker K, Ramirez-Marquez J E. A review of definitions and measures of system resilience[J]. Reliability Engineering & System Safety, 2016, 145: 47-61.
2 Bruneau M, Reinhorn A. Exploring the concept of seismic resilience for acute care facilities[J]. Earthquake Spectra, 2007, 23(1): 41-62.
3 Liu Z, Li S, Zhao W, et al. Post-earthquake assessment model for highway bridge networks considering traffic congestion due to earthquake-induced bridge damage[J]. Engineering Structures, 2022, 262: No. 114395.
4 Ghosh J, Padgett J E. Probabilistic seismic loss assessment of aging bridges using a component-level cost estimation approach[J]. Earthquake Engineering & Structural Dynamics, 2011, 40(15): 1743-1761.
5 Akiyama M, Frangopol D M, Ishibashi H. Toward life-cycle reliability-, risk- and resilience-based design and assessment of bridges and bridge networks under independent and interacting hazards: emphasis on earthquake, tsunami and corrosion[J]. Structure and Infrastructure Engineering, 2020, 16(1): 26-50.
6 Xiong C, Huang J, Lu X. Framework for city-scale building seismic resilience simulation and repair scheduling with labor constraints driven by time-history analysis[J]. Computer-Aided Civil and Infrastructure Engineering, 2020, 35(4): 322-341.
7 Billah M, Alam M S. Seismic fragility assessment of highway bridges: a state-of-the-art review[J]. Structure and Infrastructure Engineering, 2015, 11(6): 804-832.
8 Jeon J, Mangalathu S, Song J, et al. Parameterized seismic fragility curves for curved multi-frame concrete box-girder bridges using bayesian parameter estimation[J]. Journal of Earthquake Engineering, 2019, 23(6): 954-979.
9 Nielson B G, DesRoches R. Seismic fragility methodology for highway bridges using a component level approach[J]. Earthquake Engineering & Structural Dynamics, 2007, 36(6): 823-839.
10 Salehi H, Burgueño R. Emerging artificial intelligence methods in structural engineering[J]. Engineering Structures, 2018, 171: 170-189.
11 Liu Z, Li S, Guo A, et al. Comprehensive functional resilience assessment methodology for bridge networks using data-driven fragility models[J]. Soil Dynamics and Earthquake Engineering, 2022, 159: No.107326.
12 Lu X, Xu Y, Tian Y, et al. A deep learning approach to rapid regional post-event seismic damage assessment using time-frequency distributions of ground motions[J]. Earthquake Engineering & Structural Dynamics, 2021, 50(6): 1612-1627.
13 Dong Y, Frangopol D M, Saydam D. Sustainability of highway bridge networks under seismic hazard[J]. Journal of Earthquake Engineering, 2014, 18(1): 41-66.
14 Liu Z, Sextos A, Guo A, et al. ANN-based rapid seismic fragility analysis for multi-span concrete bridges[J]. Structures, 2022, 41: 804-817.
15 苑溦, 刘振亮, 宗莉娜, 等. 海洋环境下钢骨混凝土桥墩时变抗震性能分析[J]. 南京工业大学学报: 自然科学版, 2020, 42(3): 342-350.
Yuan Wei, Liu Zhen-liang, Zong Li-na, et al. Time-dependent seismic performance analysis of steel reinforced concrete bridge piers in the marine environment[J]. Journal of Natural Tech University (Natural Science Edition), 2020, 42(3): 342-350.
16 Ghosh J, Padgett J E. Aging considerations in the development of time-dependent seismic fragility curves[J]. Journal of Structural Engineering, 2010, 136(12): 1497-1511.
17 Baker J W, Lin T, Shahi S K, et al. New ground motion selection procedures and selected motions for the PEER transportation research program[R]. Berkeley, CA: Pacific Earthquake Engineering Research Center, 2011.
18 Boore D M, Atkinson G M. Ground-motion prediction equations for the average horizontal component of PGA, PGV, and 5%-damped PSA at spectral periods between 0.01 s and 10.0 s[J]. Earthquake Spectra, 2008, 24(1):99-138.
19 Chen M D, Mangalathu S, Jeon J S. Seismic reliability assessment of bridge networks considering travel time and connectivity reliabilities[J]. Earthquake Engineering & Structural Dynamics, 2022: 51(13): 3097-3110.
[1] 巫威眺,曾坤,周伟,李鹏,靳文舟. 基于多源数据和响应面优化的公交客流预测深度学习方法[J]. 吉林大学学报(工学版), 2023, 53(7): 2001-2015.
[2] 程国柱,盛林,赵浩,冯天军. 基于危险度分析的信号交叉口专用相位设置条件[J]. 吉林大学学报(工学版), 2023, 53(7): 1962-1969.
[3] 何永明,陈世升,冯佳,万亚楠. 基于高精地图的超高速公路虚拟轨道系统[J]. 吉林大学学报(工学版), 2023, 53(7): 2016-2028.
[4] 常玉林,徐文倩,孙超,张鹏. 车联网环境下考虑遵从程度的混合流量逐日均衡[J]. 吉林大学学报(工学版), 2023, 53(4): 1085-1093.
[5] 孙超,尹浩为,汤文蕴,褚昭明. 交通需求估计下的检测器布局和手机数据扩样推断[J]. 吉林大学学报(工学版), 2023, 53(4): 1070-1077.
[6] 贾洪飞,徐英俊,杨丽丽,王楠. 商品车多式联运联盟成员选择及利益分配[J]. 吉林大学学报(工学版), 2023, 53(4): 1060-1069.
[7] 肖雪,李克平,彭博,昌满玮. 基于决策-规划迭代框架的智驾车换道行为建模[J]. 吉林大学学报(工学版), 2023, 53(3): 746-757.
[8] 姚荣涵,徐文韬,郭伟伟. 基于因子长短期记忆的驾驶人接管行为及意图识别[J]. 吉林大学学报(工学版), 2023, 53(3): 758-771.
[9] 王菁,万峰,董春娇,邵春福. 城市轨道交通站点吸引范围及强度建模[J]. 吉林大学学报(工学版), 2023, 53(2): 439-447.
[10] 马敏,胡大伟,舒兰,马壮林. 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.
[11] 黄文博,陈艳艳,柴树山. 手机信息干预下寒冷赛区行人候车决策行为[J]. 吉林大学学报(工学版), 2023, 53(1): 132-140.
[12] 卢辉遒,赵枫,谢波,田彦涛. 冰雪环境下基于神经网络的驾驶人换道意图识别[J]. 吉林大学学报(工学版), 2023, 53(1): 273-284.
[13] 方松,马健霄,李根,沈玲宏,徐楚博. 城市快速路右侧车道移动作业区行车风险分析[J]. 吉林大学学报(工学版), 2022, 52(8): 1786-1791.
[14] 宋现敏,杨舒天,刘明鑫,李志慧. 站点间公交行程时间波动特性及预测方法[J]. 吉林大学学报(工学版), 2022, 52(8): 1792-1799.
[15] 张玮,张树培,罗崇恩,张生,王国林. 智能汽车紧急工况避撞轨迹规划[J]. 吉林大学学报(工学版), 2022, 52(7): 1515-1523.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 《吉林大学学报(工学版)》编辑部
地址：长春市人民大街5988号　电话：+86-431-85095297　传真：+86-431-85094074　E-mail: xbgxb@jlu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发