Ballast and Soil Performance Separation by Using Instrumented Geo-grid & Machine Learning

To study how different combinations of ballast and soil yield the same tie displacement under the same load, a simple FEM track model was built with different combinations of ballast and soil moduli. The results show that it is possible for tracks with different combinations of moduli to have the same overall track displacement under the same load. However, the interface between the ballast and the soil does show very different stress-strain characteristics for different scenarios although the overall vertical track displacement might be similar. There is a clear dividing line between the track with higher subgrade modulus and the one with lower subgrade modulus no matter what the ballast condition might be. In another words, the vertical stress vs. horizontal strain relationship at the interface of ballast and subgrade together with the track modulus measurement might be able to separate the ballast and soil performances. To measure and further study the vertical stress and the horizontal stain at the ballast-soil interface, this research team is proposing to install instrumentations such as stress cells and strain gauges on geogrids, which are typically installed in between the ballast and soil to improve the track bearing capacity. The final objective of this research is to develop ballast and soil performance characterization algorithms based on the instrumented geogrid data (both in the lab and the field) by using supervised machine learning techniques including the Logistic Regressions (LR) and the Supporting Vector Machine (SVM).

Language

• English

Project

• Status: Active
• Funding: $148299
• Contract Numbers:

  69A3551847103

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems (CIAMTIS)

  Pennsylvania State University
  University Park, PA  United States  16802
• Project Managers:

  Donnell, Eric

• Performing Organizations:

  Pennsylvania State University, University Park

  Thomas D. Larson Pennsylvania Transportation Institute
  Research Office Building
  University Park, PA  United States  16802-4710
• Principal Investigators:

  Huang, Hai

• Start Date: 20220201
• Expected Completion Date: 20230831
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Ballast (Railroads); Dislocation (Geology); Geogrids; Machine learning; Railroad tracks
• Subject Areas: Geotechnology; Railroads;

Filing Info

• Accession Number: 01835260
• Record Type: Research project
• Source Agency: Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems (CIAMTIS)
• Contract Numbers: 69A3551847103
• Files: UTC, RIP
• Created Date: Feb 3 2022 6:12PM