A new hybrid approach to predict worn wheel profile shapes. Issue 6 (3rd June 2023)
- Record Type:
- Journal Article
- Title:
- A new hybrid approach to predict worn wheel profile shapes. Issue 6 (3rd June 2023)
- Main Title:
- A new hybrid approach to predict worn wheel profile shapes
- Authors:
- Hartwich, Dietmar
Müller, Gabor
Meierhofer, Alexander
Obadic, Danijel
Rosenberger, Martin
Lewis, Roger
Six, Klaus - Abstract:
- Abstract : Wheel maintenance is a complex process whose costs can be reduced with good planning. One of the main difficulties is the prediction of a worn wheel profile shape on a train. With existing modelling approaches, it is possible to predict a worn wheel profile quickly and accurately for a unique operating situation. For varying operating scenarios, it is a more time-consuming process and often less accurate manner because so many, sometimes even unknown, input data are needed. With the new hybrid approach developed in this work, it is possible to combine the advantages of both approaches (fast, accurate, varying operating scenarios). The hybrid approach builds on historical data sets of two trains in combination with multi-body dynamic simulations. In these simulations, two different wear models have been used, one based on the maximum shear stress, the other on the wear number in the contact point. The wear model approach based on the maximum contact shear stress was confirmed as accurate through the application of the hybrid model and validation using real track measurements. This will help to improve the prediction of maintenance intervals and, thus, to reduce the costs.
- Is Part Of:
- Vehicle system dynamics. Volume 61:Issue 6(2023)
- Journal:
- Vehicle system dynamics
- Issue:
- Volume 61:Issue 6(2023)
- Issue Display:
- Volume 61, Issue 6 (2023)
- Year:
- 2023
- Volume:
- 61
- Issue:
- 6
- Issue Sort Value:
- 2023-0061-0006-0000
- Page Start:
- 1548
- Page End:
- 1564
- Publication Date:
- 2023-06-03
- Subjects:
- Wear prediction -- wheel profile prediction -- hybrid approach -- statistical wear prediction
Motor vehicles -- Dynamics -- Periodicals
Electronic journals
629.231 - Journal URLs:
- http://www.tandfonline.com/toc/nvsd20/current ↗
http://www.tandfonline.com/ ↗
http://www.tandf.co.uk/journals/titles/00423114.asp ↗ - DOI:
- 10.1080/00423114.2022.2085585 ↗
- Languages:
- English
- ISSNs:
- 0042-3114
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9153.670000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 27100.xml