Validation of a prediction model for tangent rail roughness and noise growth

Railways can inevitably cause railway rolling noise, which is induced by both wheel and rail roughness. Due to the deformation and wear between the wheel/rail at the contact patch, the rail roughness may grow in amplitude after a number of wheelset passages. This results in increasing railway rolling noise. Rail roughness is a common aspect in all transit systems and much research has been pursued to predict and mitigate its growth on track but prediction of resultant noise growth has not been a focus. This paper provides the experimental validation of the modified Railway Rolling Noise Prediction Software (RRNPS) model for the prediction of rail roughness growth and corresponding noise growth. The model is a new framework to enable noise growth predictions due to rail roughness growth mechanics. It is validated by means of several experiments that have been performed along a straight railway line. Through comparisons between predictions and measurements, it is shown that the RRNPS model gives reliable predictions on rail roughness growth and corresponding noise growth. Subsequently this model is used to predict how speed, normal force, wheelset traffic and ballast vertical stiffness affect rail roughness growth and corresponding noise growth.