Maintenance decision model for steel bridges: a case in the Netherlands

作者：Attema Thomas^*; Acharige Alex Kosgodagan; Morales Napoles Oswaldo; Maljaars Johan

来源：Structure and Infrastructure Engineering, 2017, 13(2): 242-253.

DOI：10.1080/15732479.2016.1158194

• Fatigue
• bridge deck
• monitoring
• non-parametric Bayesian networks
• linear elastic fracture mechanics

A probabilistic model is developed to investigate the crack growth development in welded details of orthotropic bridge decks. Bridge decks may contain many of these vulnerable details and bridge reliability cannot always be guaranteed upon the attainment of a critical crack. Therefore, insight into the crack growth development is crucial in guaranteeing bridge reliability and scheduling efficient maintenance schemes. The probabilistic nature of the crack growth development model and the dependence of this model on many interdependent random variables result in significant uncertainties regarding model outcome. To reduce some of these uncertainties, the probabilistic model is combined with a monitoring system installed on a part of the bridge. In addition, a Bayesian network is used to determine the dependence structure between the different details (monitored and non-monitored) of the bridge. This dependence structure enables us to make more accurate crack growth predictions for all details of the bridge while monitoring only a limited number of those details and updating the remaining uncertainties.

• 出版日期2017