Project 4.12 Summary:
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.
Principal Investigator:
Dr. Jin Zhu
Institution:
University of Connecticut
Project Type:
Base-Funded
Start Date:
7/15/2021
Project Cost:
$149,127.97
Project Status:
In Progress
End Date:
09/30/2023
Agency ID:
69A3551847101
Sponsors:
University Transportation Centers Program, Department of Transportation
University of Connecticut
Implementation of Research Outcomes:
This project is in its initial research phase. Implementation of Research outcomes will be reported upon completion of initial research.
Impacts and Benefits of Implementation:
This project is in its initial research phase. Impacts and benefits of the research will be reported after the implementation phase.
Related Links:
Coming Soon
Downloadable Documents
Printable Project Information Sheet
December 2021 Quarterly Progress Report