Computational Model for Predicting Fracture 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 an advanced computational algorithm for predicting crack evolution in ductile solids subjected to long-term cyclic loading. In this part of the University Transportation Center for Railway Safety (UTCRS) the team will continue to adapt this model to the prediction of crack growth in rails. Concomitantly, with funding provided by MxV Rail, the team has recently completed a decade-long series of experiments designed to provide data usable for the purpose of developing just such a model. The team therefore possesses the ability to both predict crack growth due to cyclic fatigue in rails, as well as to utilize their previously obtained experimental results to validate their predictive methodology. The team has therefore begun the following rather challenging task of: (1) modifying computational model for predicting crack growth for application to cyclic fatigue in rails; (2) developing an experimental protocol for obtaining the material properties required to deploy their computational fracture model (described in the companion project entitled Experimental Determination of Crack Growth in Rails Subjected to Long-Term Cyclic Fatigue Loading); (3) demonstrate the effectiveness of the model for predicting the effects of long-term cyclic loading on rail fracture; and (4) develop a procedure based on the model for railway engineers to utilize to determine when rails should be inspected and potentially removed from service for cause, thereby increasing rail safety. This project will be carried out with direct interaction and supervision by MxV Rail.

Language

  • English

Project

  • Status: Active
  • Funding: $299739
  • 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

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

Subject/Index Terms

Filing Info

  • Accession Number: 01924824
  • Record Type: Research project
  • Source Agency: University Transportation Center for Railway Safety
  • Contract Numbers: 69A3552348340
  • Files: UTC, RIP
  • Created Date: Jul 21 2024 10:58AM