Reliability analysis for the uncertainties in vehicle and high-speed railway bridge system based on an improved response surface method for nonlinear limit states

The paper deals with the reliability analysis for the high-speed railway bridge systems. Although the bridge–vehicle interactive system has much more uncertainties in the resistance and loads of trains moving at very high speed compared with static structural analysis, little concern has been engaged to identify which random variable has to be considered in the probabilistic analysis, or what criteria should be selected to determine the probabilistic safety or serviceability. The considered design parameters thus involve uncertainties in stiffness, moment of inertia, damping ratio of primary suspension in terms of load, geometry of girders and slabs, and the mechanical properties of girders in terms of resistance. The considered limit states embrace the safety of trains and comfort of passengers, and the acceptability criteria are based on UIC code. For evaluating the reliability of the time-dependent nonlinear behavior of complex structures, an improved Response Surface Method (RSM) is developed. An adaptive technique and a weight matrix are utilized as an optimizing technique that accelerates the convergence in the reliability analysis. The results of improved RSM, compared with the basic and adaptive RSM, are verified with the improved convergence to the exact solution. The bridge response is analyzed using a new three-dimensional finite element model of high-speed train–bridge interactions. The track structures are idealized using beam elements with the offset of beam nodes and beams on a two-parameter elastic foundation. The vehicle model developed for a 300 km/h train is employed. The calculated reliabilities for performance of the considered bridges and the passenger comfort on board of high-speed trains are compared to the conventional safety indices. The results of this study allow identifying the quantification of uncertainties that can control quality of the high-speed train service.