Estimating Bridge Span Deflections using Data Streams from Rolling Stock

The research being conducted is Phase II of a process that is envisioned as a complementary enhancement to visual evaluation methods by providing system-wide trending data for human decision makers. The objective is to measure the motions of the bridge and the railcar as it passes over the span. Neural networks, a type of pattern recognition technology, will be used to determine a relationship between the bridge and vehicle behaviors. Once a relationship is established, a new railcar motion can be presented to the network and the corresponding bridge behavior can be predicted using this technology.

Language

  • English

Project

  • Status: Active
  • Funding: $75,000
  • Contract Numbers:

    DTRT13-G-UTC59

  • Sponsor Organizations:

    Research and Innovative Technology Administration

    University Transportation Centers Program
    1200 New Jersey Avenue
    Washington, DC  United States  20590
  • Managing Organizations:

    Texas A&M University, College Station

    Zachry Department of Civil Engineering
    3136 TAMU
    College Station, TX  United States  77843-3136
  • Performing Organizations:

    Texas A&M University, College Station

    Zachry Department of Civil Engineering
    3136 TAMU
    College Station, TX  United States  77843-3136
  • Principal Investigators:

    Fry, Gary

  • Start Date: 20160501
  • Expected Completion Date: 20171231
  • Actual Completion Date: 0
  • USDOT Program: Train Control & Communication

Subject/Index Terms

Filing Info

  • Accession Number: 01601739
  • Record Type: Research project
  • Source Agency: University Transportation Center for Railway Safety
  • Contract Numbers: DTRT13-G-UTC59
  • Files: UTC, RiP
  • Created Date: Jun 8 2016 2:48PM