An experimental study on the effects of friction modifiers on wheel-rail dynamic interactions with various angles of attack

By modifying friction to the desired level,the application of friction modifiers(FMs)has been considered as a promising emerging tool in the railway engineering for increasing braking/traction force in poor adhesion conditions and mitigating wheel/rail interface deterioration,energy consumption,vibration and noise.Understanding the effectiveness of FMs in wheel–rail dynamic interactions is crucial to their proper applications in practice,which has,however,not been well explained.This study experimentally investigates the effects of two types of top-of-rail FM,i.e.FM-A and FM-B,and their application dosages on wheel–rail dynamic interactions with a range of angles of attack(AoAs)using an innovative well-controlled V-track test rig.The tested FMs have been used to provide intermediate friction for wear and noise reduction.The effectiveness of the FMs is assessed in terms of the wheel–rail adhesion characteristics and friction rolling induced axle box acceleration(ABA).This study provides the following new insights into the study of FM:the applications of the tested FMs can both reduce the wheel–rail adhesion level and change the negative friction characteristic to positive;stick–slip can be generated in the V-Track and eliminated by FM-A but intensified by FM-B,depending on the dosage of the FMs applied;the negative friction characteristic is not a must for stick–slip;the increase in ABA with AoA is insignificant until stick–slip occurs and the ABA can thus be influenced by the applications of FM.

Slip-Stick Vibrations of Wheelsets and Rail Corrugations

A dynamic space coupling model is developed for simulating the vibrations of wheel/rail systems as well as the torsion and bending vibrations of wheelsets. It is found that the slip stick vibrations of wheelsets are mainly caused and controlled by the crossing excitation or self excitation of the vertical vibrations of the whole system and by the bending vibrations and torsion vibrations of the wheelsets. It is found for the first time that the slip stick vibrations may occur in more than one forms, and one or another of the three kinds of vibrations is excited more strongly. Four typical kinds of slip stick vibrations are enumerated and described. The field investigation on rail corrugations shows that the four kinds of slip stick vibrations are most likely to exist and related with different corrugated features.

A Novel Model for Describing Rail Weld Irregularities and Predicting Wheel-Rail Forces Using a Machine Learning Approach

Rail weld irregularities are one of the primary excitation sources for vehicle-track interaction dynamics in modern high-speed railways.They can cause significant wheel-rail dynamic interactions,leading to wheel-rail noise,component damage,and deterioration.Few researchers have employed the vehicle-track interaction dynamic model to study the dynamic interactions between wheel and rail induced by rail weld geometry irregularities.However,the cosine wave model used to simulate rail weld irregularities mainly focuses on the maximum value and neglects the geometric shape.In this study,novel theoretical models were developed for three categories of rail weld irregularities,based on measurements of the high-speed railway from Beijing to Shanghai.The vertical dynamic forces in the time and frequency domains were compared under different running speeds.These forces generated by the rail weld irregularities that were measured and modeled,respectively,were compared to validate the accuracy of the proposed model.Finally,based on the numerical study,the impact force due to rail weld irrregularity is modeled using an Artificial Neural Network(ANN),and the optimum combination of parameters for this model is found.The results showed that the proposed model provided a more accurate wheel/rail dynamic evaluation caused by rail weld irregularities than that established in the literature.The ANN model used in this paper can effectively predict the impact force due to rail weld irrregularity while reducing the computation time.