Comparison of stochastic prediction models based on visual inspections of bridge decks

Abstract

Due to a considerable amount of information required to support the decision-making processes, an increasing number of infrastructure owners use computerized management systems. Bridges, being complex and having significant impact on society, have often been the foundation for the development of these systems. In order to manage bridges effectively, condition prediction models are incorporated to the core of decision-making processes. Many of developed and applied stochastic prediction models show certain limitations. The impact of these limitations on deterioration pre­dictions cannot be objectively evaluated without direct comparison of prediction results. Hence, several stochastic pre­diction models based on condition ratings obtained from visual inspections of bridge decks are compared in this article. Models are described and implemented on the data of around 1100 reinforced concrete bridge decks from the ‘Infraes­truturas de Portugal’, a state owned Portuguese general concessionaire for roadways and railways. The statistical analy­sis of different models revealed significant deviations, particularly in higher condition ratings. Results indicate limited prediction capability of a simple homogeneous Markov chain model when compared with time- and space-continuous models, such as the gamma process model.