This paper presents a mathematical framework to investigate the relative importance of seismic damage scenarios to the probability of failing to meet target performance measures for spatially-distributed aging bridge networks. The proposed framework relies on a statistical approach adapted from disaggregation procedures typical of probabilistic seismic hazard analysis. The estimate accuracy is enhanced using a novel simulation-based methodology proposed in previous works based on Importance Sampling with Stationary Proposal distributions (SP-IS). The basic random variables involved in risk assessment are efficiently sampled from a near-optimal simulation density based on the minimization of the Kullback- Leibler cross-entropy. A simple road network is investigated to highlight the benefits to computational effort of the proposed SP-IS numerical method and to explore the potentialities of the concept of damage disaggregation in communicating to infrastructure managers and policy makers the large-scale consequences of natural hazards and aid the optimal management and prioritization of essential maintenance interventions.
CITATION STYLE
Capacci, L., Biondini, F., & Kiremidjian, A. S. (2023). Probabilistic resilience assessment of aging bridge networks based on damage disaggregation and stationary proposal importance sampling. In Life-Cycle of Structures and Infrastructure Systems - Proceedings of the 8th International Symposium on Life-Cycle Civil Engineering, IALCCE 2023 (pp. 914–922). CRC Press/Balkema. https://doi.org/10.1201/9781003323020-111
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