Wear Prediction and Profile Design for Critical Sections of Heavy-Haul Turnout Frog Zones

Heavy-haul railway turnouts are subjected to high traffic volume. The fixed frog area within the turnout, characterized by its variable cross-section structure, collectively leads to severe wear of the frog. To mitigate frog wear and extend its service life, a novel method for predicting frog wear is proposed. This method forecasts the wear amount of the frog under varying traffic volumes based on factors such as wheel wear, plastic deformation at frog nodes, and wheelset lateral displacement. The accuracy of the method is verified through comparison with measured data. Based on the results of the simulation analysis, a profile design is conducted for the cross-section of the standard frog at the location +0.3 m from the reference point. Results indicate that wheels at the midstage of wear exhibit better compatibility with the frog, leading to reduced wear on the frog under the same traffic volume. A comparison of wear volume is conducted using the measured profiles at +0.1 m and +0.3 m and the predicted profiles. The wear volume of the measured profiles shows minimal discrepancy compared with that of the predicted profiles at a passing tonnage of 75 million tonnes, indicating the satisfactory accuracy of the wear prediction method. The designed frog profile demonstrates a reduction in equivalent stress and a significant decrease in maximum plastic deformation compared with the standard profile, thereby providing a theoretical reference for extending the service life of the frog.

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Publication Details

Journal
Transportation Research Record Journal of the Transportation Research Board
Published
2026-10-30
DOI
https://doi.org/10.1177/03611981261487415
Primary Topic
Railway Engineering and Dynamics
Type
article
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article

Wear Prediction and Profile Design for Critical Sections of Heavy-Haul Turnout Frog Zones

Jun Zhang, Yu Ye, Tongyi Meng, Jinfeng Li
4 links
Transportation Research Record Journal of the Transportation Research Board
Railway Engineering and Dynamics
article

Wear Prediction and Profile Design for Critical Sections of Heavy-Haul Turnout Frog Zones

Jun Zhang, Yu Ye, Tongyi Meng, Jinfeng Li
article en

Abstract

Heavy-haul railway turnouts are subjected to high traffic volume. The fixed frog area within the turnout, characterized by its variable cross-section structure, collectively leads to severe wear of the frog. To mitigate frog wear and extend its service life, a novel method for predicting frog wear is proposed. This method forecasts the wear amount of the frog under varying traffic volumes based on factors such as wheel wear, plastic deformation at frog nodes, and wheelset lateral displacement. The accuracy of the method is verified through comparison with measured data. Based on the results of the simulation analysis, a profile design is conducted for the cross-section of the standard frog at the location +0.3 m from the reference point. Results indicate that wheels at the midstage of wear exhibit better compatibility with the frog, leading to reduced wear on the frog under the same traffic volume. A comparison of wear volume is conducted using the measured profiles at +0.1 m and +0.3 m and the predicted profiles. The wear volume of the measured profiles shows minimal discrepancy compared with that of the predicted profiles at a passing tonnage of 75 million tonnes, indicating the satisfactory accuracy of the wear prediction method. The designed frog profile demonstrates a reduction in equivalent stress and a significant decrease in maximum plastic deformation compared with the standard profile, thereby providing a theoretical reference for extending the service life of the frog.

Transportation Research Record Journal of the Transportation Research Board
Beijing Institute of Graphic Communication (CN), Beijing University of Civil Engineering and Architecture (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 23%
Railway Engineering and Dynamics
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Wear Prediction and Profile Design for Critical Sections of Heavy-Haul Turnout Frog Zones — Jun Zhang, Yu Ye, et al. · Transportation Research Record Journal of the Transportation Research Board (2026) | TGRS Research Map | TGRS