ABSTRACT
Sustainable infrastructure requires pavement maintenance and rehabilitation to be environmentally beneficial and economically efficient. With the ever-depleting natural resources and growing demands for sustainable infrastructure, the use of reclaimed asphalt pavement (RAP) materials has seen a steady increase. This study used Bayesian-based life cycle cost analysis (LCCA) to determine the long-term economic effectiveness of using RAP in rehabilitation. Field observed performance data retrieved from the database of Specific Pavement Study 5 (SPS-5) of the Long-Term Pavement Performance (LTPP) project were used to develop the performance model, which was then employed to determine the service life of the competing alternatives. According to the posterior distributions identified through the Markov chain Monte Carlo (MCMC) simulations, the overlay thickness was best fitted by the log-normal distribution. The LCCA indicated that the use of RAP in rehabilitative projects reduced the life cycle cost around 20%.
