A robust non-Hertzian contact method for wheel–rail normal contact analysis
A modified Kik–Piotrowski (MKP) model is proposed in this paper for an accurate and robust calculation of wheel–rail normal contact problem. The presented method is able to consider the relationship between the elastic deformation of a line and the normal pressure distribution within the contact patch. A novel shape correction method is put forward to correctly describe the elastic deformation of the contact patch. Taking the results estimated by Kalker’s variational method and Kik–Piotrowski method as references, the proposed method is validated by three contact cases, including the assumed standardised non-Hertzian contact and the two-point contact, as well as the contact behaviours based on three actual wheel–rail profiles. The simulation results indicate that, compared with Kik–Piotrowski method, the proposed MKP method achieves better agreement with Kalker’s variational method. Moreover, the MKP method can avoid the abrupt change of wheel–rail normal force due to the sudden transfer of the contact point, which contributes to a better computational stability.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/00423114
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Supplemental Notes:
- © 2018 Informa UK Limited, trading as Taylor & Francis Group. Abstract republished with permission of Taylor & Francis.
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Authors:
- Sun, Yu
- Zhai, Wanming
- Guo, Yu
- Publication Date: 2018-12
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 1899-1921
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Serial:
- Vehicle System Dynamics
- Volume: 56
- Issue Number: 12
- Publisher: Taylor & Francis
- ISSN: 0042-3114
- EISSN: 1744-5159
- Serial URL: https://www.tandfonline.com/toc/nvsd20/current
Subject/Index Terms
- TRT Terms: Elastic deformation; Railroad rails; Railroad trains; Railroad wheels; Rolling contact; Simulation
- Subject Areas: Railroads; Vehicles and Equipment;
Filing Info
- Accession Number: 01686039
- Record Type: Publication
- Files: TRIS
- Created Date: Nov 20 2018 10:24AM