A probabilistic-based deterioration model using Ground Penetrating Radar

Infrastructure systems are very essential to every aspect of life on Earth. Existing Infrastructure is subjected to degradation while the demands are growing for a better infrastructure system in response to the high standards of safety, health, population growth, and environmental protection. Bridges play a crucial role in urban transportation networks. In addition to that, they are vulnerable to several deterioration agents such as the variable traffic loading, extreme weather conditions, deferred maintenance, etc. The development of Bridge Management Systems (BMSs) has become a fundamental imperative nowadays especially in the large transportation networks due to the huge variance between the need for maintenance actions, and the available funds to perform such actions. Condition assessment is regarded as one of the most critical and vital components of BMSs. Ground Penetrating Radar (GPR) is one of the non-destructive techniques (NDTs) that are used to evaluate the condition of bridge decks which are subjected to the rebar corrosion. This paper presents a corrosiveness index that is capable of evaluating the extent of severity of corrosion in concrete bridge decks. Different clustering algorithms are compared in order to select the most feasible clustering algorithm. A probabilistic deterioration model is constructed in order to model the future condition rating of bridge decks. Anderson darling test is used to select the most feasible probability density function, and the parameters of the probability density functions are obtained using maximum likelihood estimation. Finally, two case studies are presented to illustrate the capabilities of the proposed model.