Rapid Damage Assessment in Infrastructure Systems using Vibration Measurements within a Machine Learning Framework
The primary goal of this proposal is to develop different Machine Learning (ML) algorithms for the rapid identification of damage in bridge structures using the bridge’s dynamic response during regular service operation. These algorithms are in theory applicable to any dynamical system but will be tailored specifically for bridge structures. This research will provide diagnostic tools that can be directly used in real time by bridge owners for rapid damage assessment. By collecting data and analyzing them in near real time, the algorithms should be able to provide information on the conditions of the structure and this could help in (1) controlling the traffic operation on the bridge as well as (2) in prioritizing resources in terms of rehabilitation/maintenance operations. The intended outcome of the project is the development of Machine Learning based tools for rapid damage assessment in bridges which are expected to have tremendous implications in practice and education of modern civil engineers.
Language
- English
Project
- Status: Active
- Funding: $240000
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Contract Numbers:
69A3551847102
CAIT-UTC-REG74
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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 Advanced Infrastructure and Transportation (CAIT)
Rutgers University
100 Brett Road
Piscataway, New Jersey United States 08854-8058 -
Project Managers:
Szary, Patrick
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Performing Organizations:
Columbia University
610 SW Mudd
500W 120th Street
New York, New York United States 10027 -
Principal Investigators:
Betti, Raimondo
Brugger, Adrian
- Start Date: 20220901
- Expected Completion Date: 20230831
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Artificial intelligence; Bridges; Machine learning; Repairing; Structural health monitoring; Vibration
- Subject Areas: Bridges and other structures; Highways; Maintenance and Preservation;
Filing Info
- Accession Number: 01867738
- Record Type: Research project
- Source Agency: Center for Advanced Infrastructure and Transportation (CAIT)
- Contract Numbers: 69A3551847102, CAIT-UTC-REG74
- Files: UTC, RIP
- Created Date: Dec 16 2022 12:23PM