Narrow Results

The dynamic interaction of bridge-traffic system is dependent on the stochastic characteristics of various parameters that are random in nature, such as the surface roughness, traffic flow, and so on. It is necessary to include these uncertainties in the analysis. In this paper, the bridge-traffic coupled vibration system is studied considering the stochastic characteristics of traffic flows and surface roughness. The parameters, such as the extrapolation maximal displacement and mean value of the random process, are firstly presented in the probability analysis. Two vehicle models, one with 18 degrees of freedom (DOFs) and the other with 3 DOFs, were adopted in the vehicle simulation. A cellular automaton (CA) model is adopted to simulate the traffic flows and bridge surface roughness. The numerical investigation shows that: (1) the mean value distribution of the bridge vertical and lateral dynamic displacements generally remains stationary; (2) the dynamic responses at different time and under different traffic flows have negligible correlation; and (3) the extrapolation maximal value of the bridge displacement strictly and monotonically increases with the growth of design period.

China’s railway network is wide, and some of them cross the seismic zone, and the ratio of high-speed railway (HSR) bridges is high. Therefore, the safety of trains on the bridge may be endangered in the event of an earthquake. Because the response of track–bridge system is sensitive to the randomness of bridge structural parameters during the earthquake, while the train wheelset is directly in contact with the track system, the running safety of train (RST) may be also sensitive to the randomness of structural parameters. In this paper, the model of train–bridge coupled system (TBCS) under earthquake was established, and the accuracy of the model was verified by test results. To efficiently calculate the safety performance of trains considering the randomness of structural parameters, the point estimation method (PEM) was used in this paper, and the applicability of PEM was proved by comparing with the calculation results of Monte Carlo simulation (MCS). Then, PEM was used to discuss the running safety performance of trains under different ground motion (GM) intensities, different train speeds, and different pier heights. Finally, based on the maximum probability, the GM intensity threshold of a bridge based on running safety is determined.