现代城市面临着多种自然灾害的威胁。多灾害及其耦合作用对城市工程系统的破坏以及给城市所带来的巨大经济损失，日益引起了人们的高度重视。由密集建筑群、城市高架道路系统、地铁系统和生命线工程系统等子系统组成的城市工程系统在多灾害下的韧性是保障城市基本功能的关键。本课题聚焦于城市工程系统多灾害耦合作用下的灾害链效应分析和韧性评估技术，针对城市工程系统在多灾害耦合作用下的级联失效灾损机理和韧性评价理论研究方面的不足，研究多灾害耦合作用下城市工程系统灾害链的形成机理，建立模拟链式效应的分析模型和级联失效模型，揭示灾害扩散和演变的机理；研究城市区域密集建筑群、城市高架道路系统、地铁系统和生命线工程系统等典型城市工程子系统在灾害链下的损伤和失效机理，构建其灾损脆弱性评估模型，提出其韧性评估方法；以灾后功能损失与恢复为基准，建立城市工程系统在多灾害耦合作用下的韧性评价指标体系和评估方法。本课题的研究对于完善我国的城市多灾害韧性评价理论和方法、有效提升城市的抗灾韧性具有重要的意义。2022年11月至2023年11月期间围绕本课题开展的研究工作汇报于此。Modern cities are facing the threats from various hazards.Damage of urban engineering system caused by multiple hazards and their coupling effects and the consequent huge economic losses to the city have attracted a great deal of attention.The resilience of urban engineering system,which consists of typical subsystems such as dense building cluster,elevated bridge system,subway system,and lifeline engineering system,is the key to ensuring the basic functions of the city subject to multiple hazards.To overcome the current shortcomings of the research on the cascading failure mechanism and resilience assessment theory,this project focuses on the analysis of disaster chain effect and resilience assessment technology for urban engineering system under multi-hazard coupling effect,to study the formation mechanism of disaster chain,to establish the simulation model for disaster chain effect and cascading failure,and to reveal the disaster diffusion and evolution mechanism.Focusing on typical urban engineering subsystems(dense building cluster,elevated bridge system,subway system,and lifeline engineering system),this project will study their damage and failure mechanism under disaster chain,build the vulnerability evaluation model and propose the resilience assessment method.Based on post-disaster functional loss and restoration,the resilience assessment index and assessment methodology for urban engineering systems under multi-hazard coupling effect will be established.This research is of great significance for improving the multi-hazard assessment theory and method and effectively enhancing the city’s resilience against disasters.This report summarizes the work conducted during the period from November 2022 to November 2023.

随着城市化进程的不断推进，确保城市基础设施群具有足够的安全性能以及抗灾韧性变得至关重要。为考虑多灾害及其耦合作用以有效展开城市韧性评价，本研究致力于研究多灾害耦合作用机理、城市基础设施单体的致灾机理、城市工程系统的级联失效机理，并探索多灾害耦合激励下的城市工程系统多尺度多分辨率区域韧性评估框架，力求搭建涵盖不同城市特征的工程系统多灾害韧性智能评估平台。现阶段已开发了人工智能驱动的易损性快速预测模型和物理增强的结构响应预测机器学习模型，构建了城市工程系统的多分辨率韧性评估方法，初步确定了城市工程系统的韧性评估平台架构。具体而言：首先，基于表格数据提出单体基础设施地震概率易损性快速评估模型，并基于时序数据提出了考虑不确定性的单体基础设施非线性时程响应预测方法。考虑到获取高保真数据的成本巨大，提出了多保真数据驱动的基础设施安全状态预测机器学习方法，可有效利用高保真数据精度高、低保真数据易获取的各自优势。其次，考虑多种因素构建了考虑时变效应的单体基础设施抗震韧性量化框架，确定了结构震后损失的主要来源。在区域层次，基于建筑倒塌瓦砾分布、道路交通系统通行效率与可达性、以及消防系统响应覆盖率与响应时间，建立了“建筑群—道路交通—消防”多系统灾害链功能韧性量化分析方法，基于数据驱动实现了区域桥梁群的全寿命周期地震损伤快速评估。最后，确定平台架构的核心为信息感知层、互联网络层、韧性评估层、平台应用层。With the continuous advancement of urbanization,it is crucial to ensure that urban infrastructures are equiped with sufficient safety performance and disaster resilience.To effectively carry out urban resilience evaluation considering multiple disasters and their coupling effects,the coupling mechanism of multiple disasters,the disaster-causing mechanism of individual urban infrastructure,and the cascading failure mechanism of urban engineering systems are researched.Moreover,an intelligent multi-hazard resilience assessment platform for engineering systems covering different urban characteristics will be built after exploring a multi-scale and multi-resolution regional resilience assessment framework for urban engineering systems under the stimulation of coupled multiple disasters.At the current stage,an artificial intelligence-driven vulnerability rapid prediction model and a physics-enhanced structural response prediction machine learning model have been developed.Meanwhile,a multi-resolution resilience assessment method for urban engineering systems has been constructed,and the architecture of resilience assessment platform for urban engineering systems has been initially determined.Specifically,a rapid assessment model for the probabilistic seismic vulnerability of individual infrastructure based on tabular data and a method for predicting the nonlinear time-history response of individual infrastructure considering uncertainty based on time-series data were proposed.Considering the huge burden of obtaining high-fidelity data,a machine learning method for predicting the safety status of infrastructure driven by multi-fidelity data was proposed.Taking into account multiple factors,a seismic resilience quantification framework for individual infrastructure considering time-varying effects was constructed,and the main sources of post-seismic structural loss was determined.At the regional level,a quantitative analysis method for the functional resilience of the"building group-road traffic-fire"multi-system disaster chain was established.Furthermore,a rapid assessment of seismic damage throughout the lifecycle of regional bridge groups based on data-driven methods was achieved.Finally,the information perception layer,the interconnected network layer,the resilience assessment layer,and the platform application layer were determined as core of the platform’s architecture.