场地效应与贝叶斯网络在城市道路交通系统抗震韧性评估中的应用研究
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作者单位:

1.内蒙古大学 交通学院, 内蒙古 呼和浩特 010020 ;2.内蒙古大学 土木工程废弃物绿色资源化利用研究自治区高等学校重点实验室, 内蒙古 呼和浩特 010020 ;3.内蒙古师范大学 地理科学学院, 内蒙古 呼和浩特 010022

作者简介:

宝音图(1980-),男(蒙古族),博士,副教授,主要从事地震灾害评估与防震减灾研究。E-mail:baoyintu@imu.edu.cn。

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中图分类号:

TU352.1;X915.5

基金项目:

国家自然科学基金项目(41967056);内蒙古自然科学基金项目(2019ms05082)


Application of site effects and a Bayesian network in seismicresilience assessment of urban road traffic systems
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Affiliation:

1.School of Transportation, Inner Mongolia University, Hohhot 010020 , Inner Mongolia, China ;2.Key Laboratory of Green Resource Utilization of Civil Engineering Waste at Universitiesof Inner Mongolia Autonomous Region, Hohhot 010020 , Inner Mongolia, China ;3.School of Geographical Science, Inner Mongolia Normal University, Hohhot 010022 , Inner Mongolia, China

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    摘要:

    为探讨场地效应在破坏性地震中对建筑损坏的影响,分析临街建筑倒塌对道路网格连通性的影响。首先,介绍由微动的水平与竖向分量频谱比(HVSR)计算场地易破坏程度(K值)的方法;通过收集世界范围内破坏性地震的K值和建筑物震害数据,构建强震后场地易破坏程度(K值)与建筑严重损坏概率的经验关系。其次,将建筑物严重损坏概率转化为道路堵塞概率,推导出K值与强震后道路网格连通性概率的关系,并构建一个包含四个城市抗震功能系统的贝叶斯网络模型,其中道路网格连通性概率作为先验信息。最后,计算单个节点和整个城市道路交通系统的韧性指数。以呼和浩特市赛罕区为例,对该区41条路段开展常时微动观测,由观测记录求出HVSR,计算出各场地的易破坏程度(K值),进而推导出道路堵塞概率;然后,利用贝叶斯网格计算出四个城市抗震功能系统及城市道路交通系统的抗震韧性指数。研究结果表明:救援系统的抗震韧性指数为51.8,聚集区间转运系统为38.6,表明这两个系统具有较高的抗震韧性;医疗救助系统的抗震韧性指数为24.7,物资运输系统为30.3,表明这两个系统的抗震能力相对较弱;城市道路交通系统的整体抗震韧性指数为7.69,表明该区域的整体抗震韧性有待加强。该方法在城市道路网格抗震韧性评估中至关重要,可为提升城市基础设施抗震韧性能力提供重要参考。

    Abstract:

    This study investigates the influence of site effects on damage to buildings during earthquakes and analyzes the impact of collapsed street-front buildings on road network connectivity. First, a method for calculating site vulnerability (K value) using the horizontal-to-vertical spectral ratio (HVSR) of microtremors is introduced. By collecting K values and building damage data from earthquakes worldwide, an empirical relationship between post-earthquake site vulnerability (K value) and the probability of severe damage to buildings is established. Second, the probability of severe damage to buildings is converted into the probability of consequential road blockage, deriving a correlation between the K value and the probability of post-earthquake road network connectivity. A Bayesian network model incorporating four functional systems for urban seismic resilience is constructed, with the probability of road network connectivity serving as prior information. Finally, resilience indices for individual nodes and the entire urban road traffic system are calculated. Taking the Saihan District of Hohhot City as an example, microtremor observations were conducted along 41 road sections. HVSR curves derived from the recordings were used to calculate site vulnerability (K value), from which the probability of road damage was derived. The Bayesian network was then employed to compute the seismic resilience indices of the four functional systems and the overall urban road traffic system. Results indicate that the rescue system exhibits a resilience index of 51.8, and the gathering area transfer system 38.6, reflecting high seismic resilience. In contrast, the medical assistance system has a seismic resilience index of 24.7, and the material transportation system 30.3, which suggests a relatively weaker seismic capacity in these two systems. The overall seismic resilience index of the urban road traffic system is 7.69, which suggests a need for enhancement of regional seismic resilience. This method is crucial for assessing the seismic resilience of urban road networks and can provide important reference points for enhancing the seismic resilience capacity of urban infrastructure.

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宝音图,姚特,徐茂臣,等.场地效应与贝叶斯网络在城市道路交通系统抗震韧性评估中的应用研究[J].地震工程学报,2026,48(1):91-102. DOI:10.20000/j.1000-0844.20250526001

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  • 收稿日期:2025-05-26
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  • 在线发布日期: 2025-12-15
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