Proactive and Intelligent Risk Management in Complex Civil Infrastructure Project Systems (4.12)
The construction of complex civil infrastructure projects, such as major transportation expansion and rehabilitation, usually faces various types of risks and uncertainties. If not managed properly, these risks and uncertainties bring significant negative impacts on project performance, causing schedule delays and cost overruns, which prevent these projects to enhance the durability and efficiency of our transportation infrastructures. This study proposes a more intelligent and proactive risk management framework, using advanced neural network analysis and simulation techniques. The methodology developed could help project teams deal with project risks and uncertainties in a more intelligent and proactive way, and thus improve project performance.
- Record URL:
Language
- English
Project
- Status: Terminated
- Funding: $149128
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Contract Numbers:
69A3551847101
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Sponsor Organizations:
Transportation Infrastructure Durability Center
University of Maine
Orono, ME United States 04469University of Connecticut, Storrs
Connecticut Advanced Pavement Laboratory
270 Middle Turnpike, Unit 5202
Storrs, CT United States 06269-5202Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
Transportation Infrastructure Durability Center
University of Maine
Orono, ME United States 04469University of Connecticut, Storrs
Connecticut Advanced Pavement Laboratory
270 Middle Turnpike, Unit 5202
Storrs, CT United States 06269-5202Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Project Managers:
Dunn, Denise
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Performing Organizations:
Transportation Infrastructure Durability Center
University of Maine
Orono, ME United States 04469University of Connecticut, Storrs
Connecticut Advanced Pavement Laboratory
270 Middle Turnpike, Unit 5202
Storrs, CT United States 06269-5202 -
Principal Investigators:
Zhu, Jin
- Start Date: 20210715
- Expected Completion Date: 20230930
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Infrastructure; Methodology; Neural networks; Project management; Risk management
- Subject Areas: Administration and Management; Planning and Forecasting; Terminals and Facilities; Transportation (General);
Filing Info
- Accession Number: 01851275
- Record Type: Research project
- Source Agency: Transportation Infrastructure Durability Center
- Contract Numbers: 69A3551847101
- Files: UTC, RIP
- Created Date: Jul 14 2022 10:45AM