Resilience has emerged as a crucial concept for evaluating structural performance under disasters because of its ability to extend beyond traditional risk assessments, accounting for a system's ability to minimize disruptions and maintain functionality during recovery. To facilitate the holistic understanding of resilience performance in structural systems, a system-reliability-based disaster resilience analysis framework was developed. The framework describes resilience using three criteria: reliability, redundancy, and recoverability, and the system's internal resilience is evaluated by inspecting the characteristics of reliability and redundancy for different possible progressive failure modes. However, the practical application of this framework has been limited to complex structures with numerous sub-components, as it becomes intractable to evaluate the performances for all possible initial disruption scenarios. To bridge the gap between the theory and practical use, especially for evaluating reliability and redundancy, this study centers on the idea that the computational burden can be substantially alleviated by focusing on initial disruption scenarios that are practically significant. To achieve this research goal, we propose three methods to efficiently eliminate insignificant scenarios: the sequential search method, the n-ball sampling method, and the surrogate model-based adaptive sampling algorithm. Three numerical examples, including buildings and a bridge, are introduced to prove the applicability and efficiency of the proposed approaches. The findings of this study are expected to offer practical solutions to the challenges of assessing resilience performance in complex structural systems.

翻译：韧性已成为评估结构在灾害下性能的关键概念，因为它能够超越传统风险评估，考虑系统在恢复期间最小化中断并维持功能的能力。为促进对结构系统韧性性能的全面理解，开发了一种基于系统可靠性的灾害韧性分析框架。该框架使用三个标准描述韧性：可靠性、冗余性和可恢复性，并通过检查不同可能渐进失效模式的可靠性和冗余性特征来评估系统内部韧性。然而，该框架在实际应用中仅限于具有众多子构件的复杂结构，因为评估所有可能的初始破坏场景变得难以处理。为弥合理论与实际应用之间的差距，特别是针对可靠性和冗余性的评估，本研究集中于一个核心思想：通过关注实际重要的初始破坏场景，可以显著减轻计算负担。为实现这一研究目标，我们提出了三种有效消除不重要场景的方法：顺序搜索方法、n球采样方法以及基于替代模型的自适应采样算法。通过引入包括建筑物和桥梁在内的三个数值案例，证明了所提出方法的适用性和效率。本研究的发现有望为评估复杂结构系统韧性性能的挑战提供实际解决方案。