Various simulation-based and analytical methods have been developed to evaluate the seismic fragilities of individual structures. However, a community's seismic safety and resilience are substantially affected by network reliability, determined not only by component fragilities but also by network topology and commodity/information flows. However, seismic reliability analyses of networks often encounter significant challenges due to complex network topologies, interdependencies among ground motions, and low failure probabilities. This paper proposes to overcome these challenges by a variance-reduction method for network fragility analysis using subset simulation. The binary network limit-state function in the subset simulation is reformulated into more informative piecewise continuous functions. The proposed limit-state functions quantify the proximity of each sample to a potential network failure domain, thereby enabling the construction of specialized intermediate failure events, which can be utilized in subset simulation and other sequential Monte Carlo approaches. Moreover, by discovering an implicit connection between intermediate failure events and seismic intensity, we propose a technique to obtain the entire network fragility curve with a single execution of specialized subset simulation. Numerical examples demonstrate that the proposed method can effectively evaluate system-level fragility for large-scale networks.

翻译：各类基于模拟和解析的方法已被广泛用于评估单体结构的地震易损性。然而，社区的地震安全性与恢复力在很大程度上受管网可靠性的影响，这不仅取决于构件的易损性，还与网络拓扑结构及物资/信息流密切相关。然而，由于网络拓扑复杂、地震动之间相互关联以及失效概率较低，管网的地震可靠性分析往往面临重大挑战。本文提出通过一种方差缩减方法克服这些挑战，该方法采用子集模拟进行管网易损性分析。子集模拟中的二元网络极限状态函数被重构为信息量更丰富的分段连续函数。所提出的极限状态函数能够量化每个样本与潜在网络失效域的接近程度，从而构建专门的中间失效事件，这些事件可应用于子集模拟及其他序贯蒙特卡洛方法。此外，通过发现中间失效事件与地震强度之间的隐含联系，我们提出一种技术，仅需执行一次专门的子集模拟即可获得完整的管网易损性曲线。数值算例表明，所提方法能够有效评估大规模管网的系统级易损性。