| The Ohio Department of Transportation Bridge Management System (BMS) currently uses Organizational Performance Indices (OPI) to track bridge performance each year. Currently, ODOT makes decisions based on four OPI ratings. The goal is to keep bridge deficiency levels below specified levels for OPI ratings, on which the bridge performance is evaluated. First, the historical data from disparate sources is extracted, cleaned and transformed taking into consideration data quality issues. A suitable schema is implemented to construct a data warehouse. Secondly, a stochastic Markov chain model is built to study the effect of geographical location, bridge type material and age on the degradation rate of over 45,000 bridges. The results give an insight into bridge performance issues, ability to study bridge performance with time and degradation rates. Bridges in northern and southern districts and bridges with concrete and steel material have different degradation rates. Three age groups of new, middle and old aged bridges exhibit different degradation rates (three piece-wise stationary) indicating age is an important factor that affects degradation. The bridge prediction and performance model developed will facilitate inspection scheduling, cost analysis and budget optimization. This will aid in management and decision making activities. |
