Predicting bridge bearing demands through a probabilstic framework

The life expectancy of bridge bearings is not well understood or predicted, and bearing replacement is primarily determined through field inspection and engineering judgement. An improved estimate of the timeline for bearing replacement would aid in maintenance scheduling and budgets. As a first step in determining the age for replacement, the annual and lifetime cyclic demands must be estimated. The bearing displacements are largely caused by temperature fluctuation, seismic events, and traffic cycles. In this dissertation a probabilistic framework is presented to quantify the annual cyclic displacement demands on a bearing from these diverse loadings using an archetype continuous concrete girder bridge. The likelihood of occurrence per annum of cycles of increasing amplitudes are presented. In addition, the mean and cycle periods which are related to the loading scenario and cycle amplitude are discussed, and a suggested loading protocol is presented. Three locations across Canada are considered, Quebec City, Toronto and Vancouver, to investigate the influence of location on the bearing demands. The annual expected demands can be used for future work on fatigue testing of bearings to better relate to replacement schedule projections for bridge bearings.

Predicting bridge bearing demands through a probabilstic framework Conferences