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

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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Publication Details

Journal
Journal of Computational and Nonlinear Dynamics
Published
2026-02-19
DOI
https://doi.org/10.1115/1.4071178
Primary Topic
Railway Engineering and Dynamics
Type
article
Field-Weighted Citation Impact
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article

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

Hiroyuki Sugiyama, Osamu Kondo, Takahiro Fujimoto, Takanori Kato et al.
Journal of Computational and Nonlinear Dynamics
Railway Engineering and Dynamics
article

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

Hiroyuki Sugiyama, Osamu Kondo, Takahiro Fujimoto, Takanori Kato, Hiroki Yamashita, Yosuke Yamazaki
article en

Abstract

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.

Journal of Computational and Nonlinear DynamicsVol. 21(6)
University of Iowa (US), Nippon Steel (Japan) (JP), Nippon Steel Chemical and Material (Japan) (JP)
Openalex Percentile: Top 51%
Railway Engineering and Dynamics
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