POST EVALUATION OF REPAIR EFFECT BY HIERARCHICAL BAYESIAN METHODS

Abstract

 When a deterioration of infrastructures has proceeded, they are repaired in order to recover their states. Regarding infrastructures, enormous records of repair have already accumulated. However, as a matter of fact, there are few research results of the post quantitative evaluation of repair effects. In this paper, targeting RC slabs, the authors (1) carry out the statistical deterioration prediction using visual inspection data, and (2) propose the method of the post evaluation of repair effects based on the deterioration prediction result. The mixed Markov deterioration hazard model and its hierarchical Bayesian estimation are employed as concrete model and estimation method, and the heterogeneity between deterioration processes before and after the repair in each RC slab is evaluated quantitatively. In addition, through the relative evaluation of deterioration rates between before and after repair, the post evaluation of repair effects is conducted. Furthermore, the proposed method is applied to the visual inspection data and the repair data of RC slabs in order to verify its effectiveness empirically.