A Stochastic Model of Stress Range for Heavy-Haul Railway Steel Bridges and Their Probability Characteristics

Fatigue of heavy-haul railway bridges caused by large and frequent cyclic loads has become a serious concern to all stakeholders of the bridges. The dynamics, temporal, and stochastic features of such loads make it very difficult to assess the fatigue performance of the bridges. The aim of this study is to propose a stochastic analysis method of stress range for heavy-haul railway bridges that can capture such features. First, the dynamic stress range response of the bridge is obtained from the coupled train–track–bridge system. Then, the stress range is modeled as a continuous nonstationary stochastic process based on its stochastic characteristics throughout the bridge design life. To describe its probabilistic characteristics, a moment-based method is employed, enabling a flexible representation of its marginal distribution and autocorrelation function. Finally, the method is applied to analyze the stress range of an actual railway steel bridge, demonstrating its practical applicability. It is found in this study that the marginal distribution of the stress range can be approximated as a cubic normal distribution with good accuracy, and that the autocorrelation function indicates the clear time dependency of the stress range. A merit of the proposed method is that it can capture the temporal and random characteristics of dynamic loads on steel bridges. The contribution of this study is the provision of good guidance for engineers and asset managers in the assessment and management of heavy-haul railway bridges under fatigue loads.