Efficient methodology for the probabilistic safety assessment of high-speed railway bridges

Abstract The efficiency of different probabilistic methodologies for the safety assessment of short span railway bridges is compared in the current paper. Two different simulation methods, namely the Monte Carlo and the Latin Hypercube, are combined with two different procedures to enhance the efficiency of the assessment. One of the methods is a tail modelling approach based on the extreme value theory that uses the Generalized Pareto Distribution to model the tail of the obtained distribution. The other one is an Enhanced Simulation procedure which uses an approximation procedure based on the estimates of the failure probabilities at moderate levels for the prediction of the far tail failure probabilities by extrapolation. A composite bridge with six simply supported spans of 12 m and ballasted track is selected as case study for the crossing of the TGV-double high-speed train. The variability of parameters related to the bridge, the track and the train is taken into account along with the existence of track irregularities. The running safety of trains due to loss of contact between the wheel and the rail and the track instability due to excessive deck vibrations are the two safety criteria analyzed, providing examples of limit state functions with different degrees of complexity. The obtained results are extremely promising and indicate the feasibility of the application of this type of methodology in common practice due to the very reasonable computational costs that are required.