Pilot Study: Learning Fluid-Structure Interaction via Machine Learning

This proposal addresses the content area, improving mobility of people and goods, particularly ensuring reliable mobility across bridges after tsunami loading. This work also aligns with ongoing interest in tsunami loading on bridges and machine learning applications by the Oregon Department of Transportation and the Pacific Earthquake Engineering Research (PEER) Center. Although implemented herein for the analysis of bridges, the resulting machine learning framework would be applicable to other computationally-expensive simulations and a larger set of data-driven transportation problems, such as evacuation models, active traffic control, analyzing sensor data, etc. Implementing faster models that maintain the efficacy of the original data would result in prompt feedback for analysis and design, increased feasibility for parametric applications, and better fragility functions based on CFD/FSI rather than equivalent static analysis.

Language

• English

Project

• Status: Active
• Funding: $80000
• Contract Numbers:

  69A3551747110

• Sponsor Organizations:

  United States Department of Transportation - FHWA - TTAP

  1200 New Jersey Avenue, SE
  Washington, DC    20590

  Office of the Assistant Secretary for Research and Technology

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

  University of Washington, Seattle

  Civil and Environmental Engineering Department
  201 More Hall, Box 352700
  Seattle, WA  United States  98195-2700
• Performing Organizations:

  Oregon State University, Corvallis

  204 Rogers Hall
  Corvallis, OR  United States  97331
• Principal Investigators:

  Simpson, Barbara

• Start Date: 20190816
• Expected Completion Date: 20210815
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Bridges; Fluid mechanics; Machine learning; Pilot studies; Tsunamis
• Subject Areas: Bridges and other structures; Data and Information Technology; Highways; Hydraulics and Hydrology; Planning and Forecasting;

Filing Info

• Accession Number: 01723940
• Record Type: Research project
• Source Agency: Pacific Northwest Transportation Consortium
• Contract Numbers: 69A3551747110
• Files: UTC, RiP
• Created Date: Nov 27 2019 7:27PM