Selective maintenance planning of a steel truss bridge based on the Markovian approach

This paper proposes the study of strategies of selective maintenance for a steel bridge immersed in an aggressive environment, starting from the simulation of each individual member. Simulation of deterioration is obtained through the application of an appropriate damage law implemented with a Monte Carlo methodology, while the time prediction of occurrence of the deterioration is obtained through the application of a Markovian probabilistic approach. The results of the Markovian approach were the starting point for choosing strategies of selective maintenance, as the Markov process allowed the identification, in probabilistic terms, of the structure members with the highest risk of collapse and the timing for achieving levels of damage related to the possible collapse of compromised members. This timing was used to identify possible intervals of maintenance. Proposed scenarios are compared with each other both in terms of associated risk, and in terms of life-cycle cost effectiveness.