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

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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"

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