Experimental Determination of Crack Growth in Rails Subjected to Long-Term Cyclic Fatigue Loading

It is well known that one of the most significant causes of train derailments within the U.S. is due to rail fracture. Despite this fact, a reliable model for predicting fatigue fracture in rails has not yet been deployed within the U.S. The research team has recently been developing a multiscale computational algorithm for predicting crack evolution in ductile solids subjected to long-term cyclic loading. In this part of the UTCRS the team will perform intricate experiments on rails with internal cracks as a means of both obtaining material properties and validating an advanced computational model under development in their companion proposal entitled Computational Model for Predicting Fracture in Rails Subjected to Long-Term Cyclic Fatigue Loading. Furthermore, with funding provided by MxV, the team has recently completed cyclic crack growth experiments on seven bi-axially loaded rails with internal cracks that had previously been in service. The team is therefore in this research developing the ability to: (a) characterize fracture parameters for deploying their advanced fracture mechanics model; (b) utilize these parameters to predict crack growth due to cyclic fatigue in rails; and (c) utilize experimental results obtained over the previous decade of testing to validate their computational predictive methodology. Should this model development prove to be useful, it is the ultimate intention to utilize this new advanced technology as a tool for determining how long rails in which flaws have been detected can be safely retained in service.

Language

  • English

Project

  • Status: Active
  • Funding: $75232
  • Contract Numbers:

    69A3552348340

  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590

    Texas A&M Transportation Institute

    Texas A&M University System
    3135 TAMU
    College Station, TX  United States  77843-3135
  • Managing Organizations:

    Texas A&M Transportation Institute

    Texas A&M University System
    3135 TAMU
    College Station, TX  United States  77843-3135
  • Project Managers:

    Stearns, Amy

  • Performing Organizations:

    Texas A&M Transportation Institute

    Texas A&M University System
    3135 TAMU
    College Station, TX  United States  77843-3135
  • Principal Investigators:

    Allen, David

    Kim, Yong-Rak

    Dorsett, Garrett

  • Start Date: 20240601
  • Expected Completion Date: 20250531
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01924842
  • Record Type: Research project
  • Source Agency: University Transportation Center for Railway Safety
  • Contract Numbers: 69A3552348340
  • Files: UTC, RIP
  • Created Date: Jul 22 2024 7:34AM