Development of Age and State Dependent Stochastic Model for Improved Bridge Deterioration Prediction
Reliable and accurate assessment and prediction of the condition deterioration of bridges is critical for effective bridge preservation, which can help extend the service life of bridges. Bridge inspection serves as an important task in assessing the current condition of bridges. The inspection data over time can also help establish condition deterioration models to predict bridge conditions in the future. The deterioration models combined with the information on the current condition can help guide inspection, maintenance, repair, and rehabilitation planning, and can also be incorporated for risk and life-cycle analysis. Therefore, it is very important to develop deterioration models that can better predict the condition deterioration of bridges and bridge elements.
Language
- English
Project
- Status: Completed
- Funding: $106000
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Contract Numbers:
69A3551747108
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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:
North Dakota State University
Fargo, ND United States 58108 -
Project Managers:
Tolliver, Denver
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Performing Organizations:
Department of Civil and Environmental Engineering
Campus Delivery 1372
Fort Collins, CO United States 80523 -
Principal Investigators:
Jia, Gaofeng
- Start Date: 20171102
- Expected Completion Date: 20240731
- Actual Completion Date: 20241203
- USDOT Program: University Transportation Centers Program
- Source Data: MPC-536
Subject/Index Terms
- TRT Terms: Bridges; Data mining; Deterioration; Inspection; Maintenance; Markov chains; Mathematical prediction; Stochastic programming
- Subject Areas: Bridges and other structures; Data and Information Technology; Highways; Maintenance and Preservation; Planning and Forecasting;
Filing Info
- Accession Number: 01650583
- Record Type: Research project
- Source Agency: Mountain-Plains Consortium
- Contract Numbers: 69A3551747108
- Files: UTC, RIP
- Created Date: Nov 6 2017 2:55PM