Quantification of Railroad Ballast Performance Using Advanced Sensor Network & Big Data

While railroads are aware of the fact that ballast behavior has a profound influence on track performance and that ballast fouling leads to accelerated track-bed deterioration, the methods for determining ideal maintenance (e.g., tamping, ballast cleaning, etc.) have relied heavily on past experience, manual inspection, and often anecdotal information. A technology that will allow railroads to identify an objective threshold by which they can establish a window of opportunity for ideal track maintenance is in great need. This proposed research is expected to satisfy this need by implementing an advanced ballast performance monitoring program based on innovative wireless sensors and Big Data technologies. This project is anticipated to result in a real-time data collection and integrated analysis system which will allow railroad companies to identify the instantaneous condition of their ballast and track-bed more accurately and proactively assign maintenance windows to ensure safe and efficient train operation with the least amount of train delay due to maintenance outages.

Language

• English

Project

• Status: Active
• Funding: $222,002
• 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

  University of Delaware, Newark

  College of Engineering
  Newark, DE  United States  19711
• Principal Investigators:

  Huang, Hai

  Zarembski, Allan

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

Subject/Index Terms

• TRT Terms: Ballast (Railroads); Data collection; Maintenance of way; Sensors
• Subject Areas: Data and Information Technology; Maintenance and Preservation; Railroads;

Filing Info

• Accession Number: 01835263
• 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 8:17PM