ABSTRACT
Road bridges are life line structures essential to ensure community mobility. Bridge management agencies currently adopt streamlined and cost-effective approaches to facilitate maintenance of their aging and deteriorating bridge assets. One typical approach is based on different levels of inspection before making a decision on repair or replacement. In such approach, the deterioration level of bridge component is expressed through time-varying discrete condition states (e.g. use of 4 condition states with 1 being good and 4 being poor) which are defined by type and severity of structural deterioration and damages at the time of inspection. In utilizing the inspected condition data, past studies successfully applied the Markov deterioration model to understand and predict the rate of deterioration of bridge components. Based on that, optimal rehabilitation and replacement policies for bridge components have been developed in several past studies. However, one important management problem, which has not been addressed in previous studies of bridge maintenance, is to identify the next inspection time for a bridge component with known current condition that will result in lowest operational cost over a planning horizon. Furthermore, the effect of early intervention on inspection and maintenance cost has not been well investigated. From cost-saving and risk perspective, finding the optimal inspection time and repair intervals, while keeping bridges at a reasonable level of service, is of interest to the bridge management agencies. The model proposed here integrates the Markov deterioration model and a cost rate function through a computational procedure for deriving the lowest-cost inspection time of bridge components with various known condition states. A case study with bridge condition data is presented to demonstrate the benefit of this study.
