Comparison of wear models for simulation of railway wheel polygonization

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This paper presents a comparative study on the applicability of existing popular wear models in simulation of railway wheel polygonization. Four representative wear models developed by BRR (British Rail Research), KTH (Royal Institute of Technology), USFD (University of Sheffield), and Professor Zobory respectively, are selected for the comparison with consideration of global and local methods. All the wear models are converted to calculate the instantaneous wear of one contact patch. Uniform expression of the converted wear functions is derived analytically with the equivalent wear coefficient as a useful index to identify the proportional relationship among the wear models quantitatively. Several scenarios grouped by harmonic excitation and random excitation are adopted to assess the fluctuation of the instantaneous wear depth calculated by different wear models. The evolved polygonal wear around the wheel circumference is also compared among the wear models based on a developed prediction program. Simulation results show that all the wear models being investigated in this paper present a similar ability to reflect the fluctuation of the instantaneous wear under various circumstances. Specifically, all wear models can correctly reflect the frequency characteristics of the excitation in a general sense, and the fluctuation phase of the instantaneous wear is obtained with almost the same result among the wear models. There is a very good consistency of trend for all local wear models to simulate the evolved polygonal wear. The mean value and the fluctuation amplitude of the instantaneous wear, as well as the roughness level of the evolved polygonal wear, are all determined by the original wear coefficients used. Besides, the global method is not suitable for calculating the polygonal wear of railway wheels as some sharp points might be generated by the absolute operation for the global WI (Wear Index).
Original languageEnglish
Article number203010
Early online date18 Aug 2019
Publication statusPublished - 15 Oct 2019


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