|dc.description.abstract||Many of the existing bridges in the United States were built during the interstate era and are reaching the end of their life cycle. Traffic-induced loadings are one of the primary factors affecting the service and fatigue life of bridges and could accelerate bridge deterioration, making them structurally deficient or obsolete. According to U.S. DOT’s report to Congress on condition and investment requirements of the nation’s highway and bridges in 2015, 25% of the 607,380 bridges in the U.S. are either structurally or functionally deficient. They projected a cost of $123.1 billion for replacement or rehabilitation of these deficient bridges.
State transportation agencies are interested in knowing the damage caused by overloaded vehicles (permit loads and illegal loads) to bridges for the potential uses in weight limit enforcement, budgeting, maintenance, and planning inspection intervals. The weigh-in-motion (WIM) database is the major source of information about traffic loads. An added benefit of the WIM system is that it can measure detailed vehicle weight information of the vehicles traveling on highways without the knowledge of drivers.
This dissertation first proposes a data-driven decision support tool that: (1) evaluates the quality of WIM traffic data to avoid misinterpretation of traffic load effects, (2) identify permitted and illegally loaded vehicles and (3) develop procedures to quantify the fatigue damage caused by traffic loads to steel bridges. The procedures are demonstrated using traffic data collected in the state of Alabama. Second, the adequacy of the current AASTHO fatigue design truck for the state of Alabama is checked.
The developed quality control procedure can interpret inconsistency in recording due to communication failure, operational problems with the sensor, and drift in the calibration of WIM systems. Two novel techniques are proposed to sort legal, permit, and illegally overloaded vehicles in the accumulated traffic data.
The procedure to quantify fatigue damage allows comparisons of the impacts of truck traffic on various routes and also for a specific fatigue prone detail in a bridge. The results show that approximately 20% of trucks in Alabama that are overloaded create more than 50% of the total damage based on the combined data from all the WIM locations in the state. A typical steel bridge with bottom flange cover plates was evaluated for a heavily traveled route. This analysis shows that the fatigue life of the bridge was consumed at an annual rate consistent with a mean life of 100 years. Computer apps AL_WIM_QC and AL_WIM_DAI were then developed using the developed procedures to check the quality of WIM data and to quantify the fatigue damage accumulated in bridges. Also, the developed procedures may be incorporated into the National Bridge Inventory (NBI) to assess the knowledge of current loads on each bridge, evaluation of current and future conditions of highway infrastructure and budget allocation for maintenance and improvement.||en_US