ABSTRACT
Let f ij denote the jth lateral branching point of the ith main feeder of a radial network, where i = {1, 2, …, I}, j = {1, 2, …, Ji}, I is the number of main feeders in the circuit, and Ji is the number of branching points per main feeder i. Let bij be the number of individual lateral segments
The increasing susceptibility of lifeline systems to failure due to aging and external hazards requires efficient methods to quantify their reliability and related uncertainty. Monte Carlo simulation techniques for network-level reliability and uncertainty assessment accommodate component correlations and topological complexity without high computational demands but at the expense of reduced accuracy. In contrast, available analytical approaches provide accurate reliability assessments but for limited topologies with component correlations at the expense of high computational complexity. This study introduces a recursive closed-form technique to obtain the entire probability distribution of a reliability metric of customer service availability (CSA) for radial lifeline systems with component failure correlations. The flexibility of correlation inclusion is enabled by a novel recursive algorithm that does not perform the recursive operations explicitly, but rather it recursively transfers knowledge about which operations need to be performed. This approach halves the computation time relative to a naïve reliability assessment implementation. In addition, this study demonstrates that correlation inclusion transforms a problem solvable in polynomial time as a function of problem size into a problem only solvable in exponential time, yielding a fundamental insight for computing in civil engineering. Such tool for radial topologies also applies to other systems upon pertinent modifications, including bridges and wind turbines, while providing infrastructure owners an efficient tool to inform operation and maintenance decision making.
