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Experimental Validation of Wheel Wear Prediction Using On-Track Tests and Simulations of Railroad Vehicles
Journal article   Peer reviewed

Experimental Validation of Wheel Wear Prediction Using On-Track Tests and Simulations of Railroad Vehicles

Hiroki Yamashita, Yosuke Yamazaki, Takanori Kato, Takahiro Fujimoto, Osamu Kondo and Hiroyuki Sugiyama
Journal of computational and nonlinear dynamics, pp.1-18
02/19/2026
DOI: 10.1115/1.4071178

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Abstract

In this study, wear prediction capability for railroad wheels is validated against on-track vehicle test data. To this end, wear tests are conducted on a loop track using a freight train. The wear rates for the wheel tread and flange on multiple curves are identified using material losses from the measured wheel profiles and the wheel-rail contact information obtained from the multibody vehicle simulation on each curve. The averaged wear rate is then used for the wear prediction model. The worn wheel profiles predicted by the wear simulation agree well with the test data not considered in the wear rate identification process. Furthermore, using the validated wear simulation model for the test vehicle, a procedure for evaluating wheel profile wear with a 1:10 scaled roller test rig is proposed, considering the on-track vehicle test conditions. For this, the angle of attack and derailment coefficients of the first axle are utilized as input for the scale roller test rig. It is shown that incorporating the continuous change in the contact force characteristics caused by wear evolution is critical in replicating the wheel-rail contact behavior in on-track vehicle operations. With this procedure, a wheel wear pattern observed in the vehicle wear test can be reproduced by the scaled roller test rig model, allowing for effective experimental evaluation of wear characteristics and material degradations using a scaled wheelset, considering in-service vehicle operation conditions.

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