204
Views
2
CrossRef citations to date
0
Altmetric
Original Articles

Distribution characteristics of wheel–rail contact under random parameters

, , &
Pages 155-161 | Received 05 Apr 2015, Accepted 20 Feb 2017, Published online: 16 Mar 2017
 

Abstract

The character of wheel–rail contact influences vehicle dynamics performance. Using vehicle–track dynamics theory, we establish a railway vehicle–track dynamics model with a 30t axle load. We analyse the sensitivity of different track and vehicle factors to the wheel–rail force using sensitivity analysis, calculate the sensitivity factors of each parameter and determine the sensitivity parameters. We then perform Monte Carlo simulations to produce random samples of sensitive parameters and analyse the characteristic distributions of wheel–rail contact under random track and vehicle parameters. The results show that: train speed, integral vertical track stiffness, integral lateral track stiffness and the vertical stiffness of each vehicle’s bolster spring are all parameters sensitive to the wheel–rail contact character. Under the condition of random parameters and track irregularity excitation, a random wheel–rail force follows a Gaussian distribution, the maximum wheel–rail force obeys an extreme type I distribution, and the wheel–rail contact position distribution is uniform with two main distribution areas.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 199.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.