Fatigue Reliability Evaluation of Orthotropic Steel Bridge Decks Based on Site-Specific Weigh-in-Motion Measurements

Abstract

The fast-growing traffic loads may become a safety hazard for existing bridges especially in developing countries. One of the problems induced by heavy traffic loads is the fatigue damage accumulation of the welded joints in steel bridge decks. This study utilized a stochastic traffic flow model and a novel computational framework for estimating fatigue reliability of orthotropic steel bridge decks using site-specific traffic data. The stochastic traffic flow is demonstrated as an effective approach for converting the probabilistic characteristics of the site-specific traffic data into the fatigue stress spectrum modeling of steel bridge decks. In addition, the traffic growth and control measures can be considered in the stochastic traffic flow for lifetime fatigue reliability estimation of the bridge deck. The proposed computational framework involves a meta-model approximated by neural networks that can greatly reduce the computational effort. Orthotropic steel bridge decks in a long-span suspension bridge is chosen as prototype to illustrate the effective of the stochastic traffic flow model and the computational framework. Numerical results show the following conclusions: firstly, the efficiency and accuracy of the framework is associated with the number of training samples, where approximately 180 training samples is essential for training the 6-types of meta-models; secondly, a annual growth rate of the vehicle weight of 0.5% leads to the fatigue reliability index of the bridge in the 100th year decrease from 5.94 to 0.92. The numerical result may provide a theoretical basis for how to control overloaded trucks for ensuring the bridge safety.