New Methodology for Fast Prediction of Wheel Wear Evolution

In railway applications wear prediction in the wheel–rail interface is a fundamental matter in order to study problems such as wheel lifespan and the evolution of vehicle dynamic characteristic with time. However, one of the principal drawbacks of the existing methodologies for calculating the wear evolution is the computational cost. This paper proposes a new wear prediction methodology with a reduced computational cost. This methodology is based on two main steps: the first one is the substitution of the calculations over the whole network by the calculation of the contact conditions in certain characteristic point from whose result the wheel wear evolution can be inferred. The second one is the substitution of the dynamic calculation (time integration calculations) by the quasi-static calculation (the solution of the quasi-static situation of a vehicle at a certain point which is the same that neglecting the acceleration terms in the dynamic equations). These simplifications allow a significant reduction of computational cost to be obtained while maintaining an acceptable level of accuracy (error order of 5–10%). Several case studies are analyzed along the paper with the objective of assessing the proposed methodology. The results obtained in the case studies allow concluding that the proposed methodology is valid for an arbitrary vehicle running through an arbitrary track layout.

• Record URL:
  https://doi.org/10.1080/00423114.2017.1299870
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00423114
• Supplemental Notes:
  • Abstract reprinted with permission of Taylor & Francis.
• Authors:
  • Apezetxea, I S
  • Perez, X
  • Casanueva, C
  • Alonso, A
• Publication Date: 2017-7

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 1071-1097
• Serial:
  • Vehicle System Dynamics
  • Volume: 55
  • Issue Number: 7
  • Publisher: Taylor & Francis
  • ISSN: 0042-3114
  • EISSN: 1744-5159
  • Serial URL: https://www.tandfonline.com/toc/nvsd20/current

Subject/Index Terms

• TRT Terms: Car wheels (Railroads); Case studies; Fatigue (Mechanics); Mathematical prediction; Rolling contact; Vehicle dynamics
• Subject Areas: Railroads; Vehicles and Equipment;

Filing Info

• Accession Number: 01639981
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 28 2017 5:02PM