iNEW method for experimental-numerical locomotive studies focused on rail wear prediction

Locomotive-track interaction is commonly represented by a complex mechanical system which is modelled in numerical studies. Numerical studies alone are not enough to precisely describe the behaviour of this mechanical system due to the various elements that can only be delivered from field and laboratory experimental programs. One such element is wheel-rail wear that has been found to contribute a considerable portion of the total cost of maintaining heavily used railway systems. Simulation studies are typically used for predicting wear of wheels and rails, but the majority of these do not consider in-train forces nor provide detailed modelling of traction and braking events and often rely on historic wear rates for comparable materials, reducing the ac-curacy of the wheel-rail volume loss estimation. This paper proposes a methodology for wear rate experimental measurements that allow improving the accuracy of wear analyses using dynamic simulations. The proposed method considers in-train forces by performing longitudinal train simulations whose results are then implemented on a detailed locomotive vehicle dynamic model with a traction mechatronic system co-simulation approach. The wheel-rail contact stress and slip results are then post-processed into a Dynamic Load Spectrum that contains contact stress and wheel slip occurrences. The Dynamic Load Spectrum was used to measure the wear rates for Australian AS60 head hardened rail steel material operating in combination with Class B wheel steel material. The experimental program delivered more realistic wear rates that correspond to actual industry operational scenarios. The measured wear rates were used to estimate the rail material volume loss for a specific train trip.