Reliability Estimation for Networks of Reinforced Concrete Bridges

Abstract

Transportation networks are critical lifelines and their functionality after an earthquake is of primary importance for life safety and economic recovery of a community, yet they can be severely damaged during earthquakes. Reinforced concrete bridges are particularly vulnerable segments of these networks and have been severely damaged in past earthquakes. Past approaches for estimating traffic disruptions due to earthquakes have relied on computationally expensive simulations and have tended to overestimate postearthquake traffic volumes. This paper makes use of predictive fragility estimates to compute the conditional probability that a bridge in the network attains or exceeds a specified performance level for a given value of the ground motion intensity. The predictive fragilities incorporate the relevant sources of uncertainty inherent in the phenomenon. The focus of the paper is on network connectivity rather than traffic flow. The outcomes of the proposed approach can then be used by traffic models to accurately reflect postdisaster conditions. A block sampling-based simulation technique is used to estimate the network connectivity. This new approach provides a convenient, quick estimation of network reliability that complements computationally expensive traffic models.