Abstract
The crack progression processes of concrete pavements of airports are characterized by a lot of uncertainty. There lacks the relevant information on the pavement deterioration processes, which becomes the obstacles against the establishment of the efficient asset management systems. In this paper, the statistical models of the pavement deterioration are estimated based upon the sample paths generated by the mechanical models. The paper presents a methodology to revise iteratively the statistical models based upon the newly obtained monitoring data through the Bayesian rules. The applicability of the methodology presented in this paper is examined against the real world data concerning the airport facilities.
