Risk-informed Management and Post-disaster Operations of Lifeline Networks by Rapid, Condition-based System Reliability Analysis

社会日益要求生命线网络风险管理背后的科学问责制，如减灾规划、基础设施维护和灾后反应。为了对生命线网络进行快速和基于状态的风险管理，系统可靠性分析（SRA）方法至关重要，该方法可以集成跨物理尺度的分析，并且可以平滑地连接来自多个科学和工程领域的模型和数据，以量化系统级风险。该项目将开发多尺度SRA方法，采用先进的网络聚类算法，对大型网络进行高效、准确和协作的风险评估。该项目还将通过将快速SRA方法与危险警报系统集成，创建一个近实时网络风险警报系统，以促进对危险响应的快速决策支持。此外，还将开发一种有效的时变网络SRA方法，该方法根据网络部件劣化检测结果不断更新网络可靠性，以优化利用有限资源维持网络可靠性。本项目开发的分析方法和数值工具将帮助从业者了解生命线网络的层次结构及其对网络风险和决策的影响，开发针对实际风险管理实践定制的网络风险警报系统，并根据实际恶化进度及其对网络级风险的影响进行状态维护。以教育为重点的研究任务包括开发基于网络理论的交互式网络环境、网络停机虚拟实验、模拟网络流量和连接的交互式计算机软件以及演示基于it的风险管理的手机应用程序。研究成果将纳入复杂基础设施系统风险与可靠性研究生课程。将积极利用已建立的机构奖学金计划，从科学技术领域代表性不足的群体中招收学生。

The society is increasingly demanding scientific accountability behind risk management of lifeline networks such as hazard mitigation planning, infrastructure maintenance and post-disaster responses. For rapid and condition-based risk management of lifeline networks, it is essential to have system reliability analysis (SRA) methods that can integrate analyses across physical scales, and can interface models and data from multiple fields of science and engineering smoothly for quantifying system-level risk. The proposed project will develop multi-scale SRA methods employing advanced network clustering algorithms for efficient, accurate and collaborative risk assessment of large-size networks. The project will also create a near-real-time network risk alert system through integration of a rapid SRA method with a hazard alert system to facilitate rapid decision support on hazard responses. In addition, an efficient time-varying network SRA method will be developed in which network reliability is continuously updated based on inspection results of network component deterioration in order to sustain the network reliability with optimal use of limited resources.The analysis methods and numerical tools developed in this project will help practitioners understand the hierarchical structure of lifeline networks and its impacts on network risk and decision making, develop network risk alert systems customized for actual risk management practice, and perform condition-based maintenance considering actual deterioration progress and its impacts on network-level risk. Education-focused research tasks include the development of interactive cyber-environment on network theory, virtual experiment on network downtime, interactive computer software simulating network flow and connectivity, and mobile phone applications to demonstrate IT-based risk management. The research results will be incorporated into the graduate level courses on risk and reliability of complex infrastructure systems. Active efforts will be made to recruit students from the groups that are underrepresented in science and technology fields using the well-established institutional fellowship programs.