Development of a 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 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 two-way coupled multiscale computational algorithm for predicting crack evolution in ductile solids subjected to long-term cyclic loading. In this University Transportation Center for Railway Safety (UTCRS) project, the team will adapt this model to the prediction of crack growth in rails. Concomitantly, with funding provided by TTCI (Now MxV), the team has for nearly a decade performed long-term laboratory cyclic crack growth experiments on rails. The team possesses the ability to both predict crack growth due to cyclic fatigue in rails and utilize the experimental results to validate their predictive methodology. It is therefore the team's intention to: (1) modify their multi-scale computational model to predict crack growth due to cyclic fatigue in rails; (2) validate their model against their own previously obtained experimental results; and (3) develop a procedure based on their model for railway engineers to utilize to determine when rails should be inspected and potentially removed from service for cause, thereby enhancing rail safety.

• Record URL:
  https://www.utrgv.edu/railwaysafety/_files/documents/research/exhibit-d_utcrs_tamu_rail_fracture_prediction_2023.pdf
• Supplemental Notes:
  • Project Partners: MxV Rail

Language

• English

Project

• Status: Active
• Funding: $263985
• 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, College Station

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

  Texas A&M Transportation Institute, College Station

  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: 20230601
• Expected Completion Date: 20240831
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Cracking; Cyclic strength; Forecasting; Railroad rails; Railroad safety; Railroad tracks
• Subject Areas: Maintenance and Preservation; Planning and Forecasting; Railroads;

Filing Info

• Accession Number: 01897741
• Record Type: Research project
• Source Agency: University Transportation Center for Railway Safety
• Contract Numbers: 69A3552348340
• Files: UTC, RIP
• Created Date: Oct 28 2023 7:58PM