Abstract
i Abstract With ever-reducing maintenance budgets and ever-deteriorating bridge infrastructure, the assessment of existing bridges is vital. Reliability analysis techniques are becoming increasingly popular in the structural safety assessment of existing bridge structures. Commonly, a component based approach is used in reliability analysis techniques. Traditional reliability procedures often employ a conservative definition of failure, in that the component is deemed to have failed when the strength capacity has been exceeded at a single cross section. As a result, the component's degree of redundancy and ductility is ignored, giving an often conservative estimate of the load carrying capacity of the bridge component. Therefore, this dissertation is focused on the development of a reliability analysis procedure which accounts for material behaviour for indeterminate beams. The structural safety of a representative group of steel composite bridge beams is examined. The material response of each beam subjected to a combination of both dead load and live load is assessed using a one-dimensional nonlinear finite element analysis (NFEA) model. The Response Surface Method (RSM) is then used to replace the NFEA model with an approximated explicitly-known polynomial function. This allows a First Order Reliability Method (FORM) analysis to be performed. The developed procedure is compared to the traditional approach with regard to three limit states. These limit states are defined as elastic member failure, first formation of a plastic hinge and ultimate failure. Ultimate failure occurs when a collapse mechanism has formed. The live load on each structure consists of annual maximum traffic loading events determined from Monte Carlo Simulation (MCS) of Weighin Motion (WIM) data. The modelling of realistic live loads highlights the practicality of the procedure developed. This procedure may act as a foundation for the development of an evaluation method accounting for material nonlinearity for existing bridge structures.
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