Multi-Factor Modeling Method of the Load Sharing Ratio under Moving Train Loads

Abstract

In railway engineering, the load sharing ratio (LSR) is the ratio of the rail seat load (RSL) to the axle load, which is affected by many factors. The LSR can be used in the design and analysis of railway track structures as well as in the research of predicting the dynamic influence of railway tunnels and the environment. The “static loading method” commonly used to study the LSR does not conform to reality; using it, it is difficult to obtain a complete LSR curve, limiting its application. Besides, there is currently a lack of LSR prediction methods considering the impact of multiple factors. Therefore, this paper proposes a “moving loading method” for investigating the LSR under moving train excitation, verified to be rational by comparing with the experimental results. At the same time, a procedure for establishing the LSR multi-factor prediction model is put forward, namely, we (1) determine the LSR function form and the fitting algorithm; (2) perform parameter sensitivity analysis to determine the main influencing parameters of the LSR function; and (3) design a quadratic regression orthogonal test to obtain the prediction formula of the LSR function coefficients. Once establishing the prediction model for a type of train-track system, the LSR of similar systems can be calculated by adjusting the main parameters of the model. Shijiazhuang Metro Line 1 using the A-type vehicle and the monolithic trackbed is taken as a case study to develop a corresponding LSR multi-factor prediction model by the moving loading method and the procedure mentioned above. The results indicate that the proposed method performs well and can be adopted to enhance the accuracy of track design or tunnel and environmental vibration prediction.