The safety and resilience of civil infrastructure systems are increasingly threatened by compounded risks from various hazard events and structural deterioration due to environmental stressors. This study presents a comprehensive risk-informed, life-cycle optimization framework that extends the Performance-Based Earthquake Engineering (PBEE) and probabilistic seismic loss estimation paradigms by combining hazard uncertainties, nonstationary deterioration, structural damage accumulation, and state-dependent fragility assessments, with optimal, adaptive maintenance strategies in time. The life-cycle cost optimization is formulated in this work as a Markov Decision Process (MDP) problem, utilizing derived, transition matrices reflecting time-variant deterioration effects and hazard risks. To mitigate the curse of dimensionality in system-level optimization, a novel tensor-based method exploiting Kronecker-factored transition dynamics is introduced, reducing complexity from exponential to linear in the number of components while still preserving exact, global dynamic programming solutions. Overall, the framework is general and versatile, able to accommodate various hazard types. A seismic hazard application is, however, demonstrated and explained in detail in this work. The developed methodology eventually provides decision-makers with a practical, data-driven tool toward cost effective risk mitigation of civil infrastructure systems.

翻译：民用基础设施系统的安全性和韧性日益受到多重灾害事件与环境应力导致结构退化的复合风险威胁。本研究提出一个全面的风险知情全生命周期优化框架，通过整合灾害不确定性、非平稳退化、结构损伤累积及状态依赖的易损性评估，结合时变最优自适应维护策略，拓展了基于性能的地震工程（PBEE）与概率地震损失评估范式。本文将全生命周期成本优化建模为马尔可夫决策过程（MDP）问题，利用推导的反映时变退化效应与灾害风险的转移矩阵。为缓解系统级优化中的维度灾难，本文引入一种基于克罗内克分解转移动力学的新型张量方法，将复杂度从指数级降低至组件数量的线性级，同时保留精确的全局动态规划解。总体而言，该框架具有普适性与灵活性，可适配多种灾害类型。本文以地震灾害应用为例进行了详细阐述与说明。所开发的方法最终为决策者提供了面向民用基础设施系统经济高效风险缓释的实用数据驱动工具。