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


Zambon, I.; Vidovic, A.; Strauss, A.; Matos, José C.; Amado, J.

Stochastic prediction models; Markov process; Gamma process; Bridge management system; Condition rating; Visual inspection

Due to a considerable amount of information required to support the decision-making processes, an increasingnumber of infrastructure owners use computerized management systems. Bridges, being complex and having significantimpact on society, have often been the foundation for the development of these systems. In order to manage bridgeseffectively, condition prediction models are incorporated to the core of decision-making processes. Many of developedand applied stochastic prediction models show certain limitations. The impact of these limitations on deterioration predictionscannot be objectively evaluated without direct comparison of prediction results. Hence, several stochastic predictionmodels 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 ‘Infraestruturasde Portugal’, a state owned Portuguese general concessionaire for roadways and railways. The statistical analysisof different models revealed significant deviations, particularly in higher condition ratings. Results indicate limitedprediction capability of a simple homogeneous Markov chain model when compared with time- and space-continuousmodels, such as the gamma process model.