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This paper presents a novel method for prioritising bridge retrofits within a regional road network subject to uncertain seismic hazard, using a technique that accounts for network performance while avoiding the combinatoric computational costs of exhaustive searches. Using global variance-based sensitivity analysis, a probabilistic ranking of bridges is determined according to how much their retrofit statuses influence the expected cost of the road network disruption. Bridges’ total-order sensitivity (Sobol’) indices are estimated with respect to the expected cost using the hybrid-point Monte Carlo approximation method. A bridge’s total-order Sobol’ index measures how much its retrofit status influences the variance of the expected cost of the road network performance and accounts for the effect of its interactions with other bridges’ retrofit states. For 71 highway bridges in San Francisco, a retrofit strategy based on bridges’ total-order Sobol’ indices outperforms other heuristic strategies. The proposed method remains computationally tractable while accounting for the probabilistic nature of the seismic hazard, the uniqueness of individual bridges, network effects, and decision-makers’ priorities. Because this method leverages existing risk assessment tools and models without imposing further assumptions, it should be extensible to other types of networks under different types of hazards and to other decision variables.

Using global variance-based sensitivity analysis to prioritise bridge retrofits in a regional road network subject to seismic hazard