A Railway Wheel Wear Prediction Tool Based on a Multibody Software

Joao Pombo, Jorge Ambrósio, Manuel Pereira, Roger Lewis, Rob Dwyer-Joyce, Caterina Ariaudo, Naim Kuka

Research output: Contribution to journalArticlepeer-review

39 Citations (Scopus)


The wheel wear prediction is a key-topic in the field of railway research as it has big impact on economical and safety aspects of trainset design, operation and maintenance. The aim of this work was to implement a flexible and predictive railway wheel wear tool that, starting from a specific vehicle mission, provides the wheel profile evolution as a function of the distance run. The wear estimation tool consists of the use of a sequence of pre and post-processing packages, in which the methodologies now presented are implemented, interfaced with a commercial multibody software that is used to study the railway dynamics. The computational tool is applied here to several simulation scenarios. The purpose is to demonstrate its capabilities on wear prediction by evaluating the influence of trainset design and of track layout on the wheel wear growth. Special attention is also given to study how the wear evolution is affected by the friction conditions between the wheel and rail.

Original languageEnglish
Pages (from-to)751-770
Number of pages20
JournalJournal of Theoretical and Applied Mechanics
Issue number3
Publication statusPublished - 23 Aug 2010
Externally publishedYes


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