A Bridge Management Strategy Based on Future Reliability and Semi-markov Deterioration Models

This paper introduces the outline of a bridge management strategy based on the prediction of future bridge reliability using a semi-Markov deterioration model. This approach applies equally well to single bridges and to a whole network, and is expected to be implemented in the Bridge Management System (BMS) of the Autonomous Province of Trento (APT). More in detail, the model assumes the lifespan of a bridge to be divided into five conventional condition states, and waiting times in each state are random variables with known distributions. Mean waiting times and probability distribution parameters are currently estimated based on the information stored in the APT's BMS. Monte Carlo simulations are used to calculate the cumulative waiting time distributions, from which the semi-Markov transition probability matrices are derived. The transition probabilities are age dependent: older bridges have a higher probability of deteriorating to the next condition state in the given time interval. Once calibrated, the deterioration model allows calculation of the time variant capacity function, in terms of probabilistic initial capacity and degradation function. The prioritization is based on the principle whereby priority is given to those actions that, within a certain budget, will minimize the risk of occurrence of an unacceptable event in the whole network during the considered time interval. Sample results of the prioritization as applied to the APT stock are then discussed.