Development of Degradation Rates for Various Bridge Types in the State of Ohio

The Ohio Department of Transportation (ODOT) maintains a Bridge Management System (BMS) which is responsible for collecting and maintaining historical and longitudinal data by year for all the bridges in Ohio. The BMS aids ODOT in tracking, design, planning maintenance requests on bridges and funds allocation for maintenance. This project applied statistical analysis and modeling of the BMS data to provide insights to the rate of degradation and maintenance requirement of bridges under different environmental, location and other factors. Age resetting algorithms and Markov models were utilized in order to develop Operational Performance Indices (OPIs) forecasting for General Appraisal (GA), Wearing Surface (WS), Floor Condition (FC), and Protective Coating Systems (PCS). The results were validated against the actual values and the results were very positive. An understanding of the behavior of the existing bridges under the effect of different conditions and their future performance is essential for the BMS. Reliable bridge prediction and performance models facilitate inspection scheduling, cost analysis and budget optimization.