Abstract
Bridges are considered to be the essential structures and represent a vital part of a transportation network. Their safe operation with minimal maintenance closures is paramount for their efficient operation. The continuous increase in volume and weight of truck traffic directly translates into a higher number of accumulated fatigue load cycles. This study utilizes truck traffic data from a Weigh-in-Motion (WIM) station located on Pakistan's busiest and longest National Highway. An algorithm was developed to simulate vehicle passages over simple analytical bridge models of various span lengths to compute fatigue cycles at critical locations. This was followed by a case study on a reinforced concrete T-beam bridge located under the influence of the selected WIM station to obtain a fatigue stress spectrum for its critical details. This information provides an identification tool for bridges within a stock that are more susceptible to fatigue problems and could form part of a full-bridge management framework.