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Machines
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Rolling Contact Fatigue and Wear of Rails and Wheels
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Rolling Contact Fatigue and Wear of Rails and Wheels

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Friction and Tribology".

Deadline for manuscript submissions: 31 July 2026 | Viewed by 6546

Special Issue Editor

Prof. Dr. Makoto Akama

E-Mail Website
Guest Editor
Department of Mechanical Engineering for Transportation, Osaka Sangyo University, Daito, Japan
Interests: computational mechanics; fracture mechanics and tribology; rolling contact fatigue crack and wear

Special Issue Information

Dear Colleagues,

Railway systems involve contact between rolling wheels and the rail. Under a cyclic wheel passage, these lead to the perpetual initiation of cracks known as “rolling contact fatigue” (RCF) and wear in both surfaces, and these are major damages for wheels and rails. In the initiation and early propagation stages of cracks, crack propagation competes with wear. The mechanism that initiates cracks depends on factors such as the geometry of the rail and wheel, properties of their steels, and the type of traffic and lubrication. At the same time, wear changes the shape of both surfaces, thereby altering the wheel–rail contact region and associated contact stresses. When the wear rate is much greater than the crack growth rate, cracks cannot propagate and, in some cases, are effaced. Conversely, very low wear rates have a negligible influence on crack growth.

This Special Issue calls for up-to-date studies on the RCF and wear of rails and wheels, especially the interactions between them. Papers that include on-site measurements are also encouraged.

Prof. Dr. Makoto Akama
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • rail
  • wheel
  • rolling contact fatigue
  • wear
  • simulation
  • experiment

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Published Papers (3 papers)

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Research

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34 pages, 9147 KB  
Article
Support Vector Machine and k-Means Clustering for Advanced Wheel Flat Identification: A Comparison of Supervised and Unsupervised Methods
by Alireza Chegini, Mohammadreza Mohammadi, Araliya Mosleh, Cecilia Vale, Ramin Ghiasi, Ruben Silva, Antonio Guedes, Andreia Meixedo and Abdollah Malekjafarian
Machines 2026, 14(3), 286; https://doi.org/10.3390/machines14030286 - 3 Mar 2026
Viewed by 501
Abstract
Artificial-intelligence-driven wayside monitoring has become a promising solution for early identification of railway wheel flats, enabling safer operations and more efficient maintenance planning. This study introduces a comparative investigation of supervised and unsupervised machine learning strategies for wheel flat identification, with particular emphasis [...] Read more.
Artificial-intelligence-driven wayside monitoring has become a promising solution for early identification of railway wheel flats, enabling safer operations and more efficient maintenance planning. This study introduces a comparative investigation of supervised and unsupervised machine learning strategies for wheel flat identification, with particular emphasis on real-time applicability and sensor cost reduction. Support Vector Machines (SVMs) and k-means clustering are evaluated as representative supervised and unsupervised approaches using vibration data obtained from numerically simulated train–track interactions under realistic operating conditions, including train speeds of 120 km/h and 200 km/h and multiple wheel flat severities. A key contribution of this work is the proposal of a simplified supervised classification framework that directly exploits Auto-Regressive features extracted from rail-mounted accelerometers, eliminating the need for feature normalization and multi-sensor data fusion. This simplification significantly reduces computational effort, making the approach suitable for real-time deployment in operational railway environments. In parallel, a systematic sensitivity analysis is conducted to assess the influence of sensor placement and to identify the minimum sensor configuration required to achieve reliable damage classification. The outputs from the current study show that an SVM emerges with more accurate defect classification than the k-means clustering, allowing a wayside system with fewer sensors. Full article
(This article belongs to the Special Issue Rolling Contact Fatigue and Wear of Rails and Wheels)
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19 pages, 6167 KB  
Article
The Influence of Braking Heat and Thermal Expansion on Tread Crack of Railway Wheels
by Chun Lu, Jie Zhao, Bo Yuan, Zhang Ye, Jiahuan He and José M. Martínez-Esnaola
Machines 2026, 14(2), 173; https://doi.org/10.3390/machines14020173 - 3 Feb 2026
Viewed by 721
Abstract
Combining with the wheel–rail rolling contact models and extended finite element method (XFEM), this study systematically analyses the influence of wheel thermal expansion induced by braking thermal load on the tread cracking behavior of railway freight trains during the emergency braking process. Unlike [...] Read more.
Combining with the wheel–rail rolling contact models and extended finite element method (XFEM), this study systematically analyses the influence of wheel thermal expansion induced by braking thermal load on the tread cracking behavior of railway freight trains during the emergency braking process. Unlike the well-documented effect of material softening at elevated temperatures, the key contribution of this work lies in identifying and elucidating the dominant role of thermally induced geometrical changes in the contact conditions. The results demonstrate that wheel thermal expansion significantly alters the shape of the contact spot and the stress distribution, thereby reconstructing the mechanical driving force at the crack tip. Specifically, thermal expansion effectively suppresses Mode I cracking. Although it slightly reduces the magnitude of ΔKII, the primary and critical outcome is a distinct shift in the location of the maximum ΔKII from the deep interior of the crack to its superficial outer tip, driven by the altered contact geometry. This shift intensifies the crack propagation trend along the length direction near the surface. Therefore, although the nominal contact stress decreases when considering braking heat, the risk of surface-initiated damage increases, which needs to be paid attention to during operations and maintenance. Full article
(This article belongs to the Special Issue Rolling Contact Fatigue and Wear of Rails and Wheels)
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Review

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35 pages, 4244 KB  
Review
Rolling Contact Fatigue and Wear of Rails and Wheels: A Comprehensive Review
by Makoto Akama
Machines 2025, 13(10), 970; https://doi.org/10.3390/machines13100970 - 21 Oct 2025
Cited by 4 | Viewed by 4352
Abstract
Rolling contact fatigue (RCF) and wear are the primary types of damage found in rails and wheels, and these often compete with each other. This paper presents a comprehensive review of studies on RCF and wear of rails and wheels, focusing on their [...] Read more.
Rolling contact fatigue (RCF) and wear are the primary types of damage found in rails and wheels, and these often compete with each other. This paper presents a comprehensive review of studies on RCF and wear of rails and wheels, focusing on their competition. First, RCF and wear in actual rails and wheels are discussed. Next, theory and models for RCF cracks are presented—from crack initiation, through short and long crack growth, to crack branching and branch crack growth. Then, different wear forms, wear regimes, and their theories and models are introduced. Several studies analyzing the competition between RCF and wear are discussed. Finally, current gaps or problems of the studies on RCF and wear of rails and wheels are identified, and recommendations for future work are provided. This review aims to assist researchers who investigate and address the problems associated with RCF and wear of rails and wheels. Full article
(This article belongs to the Special Issue Rolling Contact Fatigue and Wear of Rails and Wheels)
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