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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of California-Berkeley |
| Country | United States |
| Start Date | Sep 15, 2023 |
| End Date | Aug 31, 2026 |
| Duration | 1,081 days |
| Number of Grantees | 2 |
| Roles | Principal Investigator; Co-Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2234542 |
The broader impact/commercial potential of this Partnerships for Innovation - Research Partnerships (PFI-RP) project is to significantly enhance the capability in predicting and managing life expectancy of large civil infrastructure . The future infrastructure systems need smart and fast sensors to assess their performance against designed parameters and predictive models.
The project will integrate smarter information gathering sensors that will focus on safety, security, lower life cycle costs, and post-disaster surveys needs in new and current infrastructure. The broader implication will be in realizing the 'smart city' approach for hazard prevention and future city management. This will be achieved by actively monitoring operational conditions using fiber optic sensing technology developed in this project.
Training courses will be offered to develop future leaders in the area of infrastructure engineering. Students from underrepresented minority groups will participate in the research and work closely with the industrial partner organizations bringing together designers, engineers, operators and owners.
The proposed project makes a single low-cost fiber optic cable into thousands of strain gauges, thermocouples, or accelerometers. It utilizes a patented distributed fiber optic sensing system, which provides a very high density of data (every 2 cm) over a very long distance (5-10 km). The system competes with existing technologies primarily based on its low price, high data acquisition speed and delivery of processed engineering data.
The project will produce mass-producible hardware and commercial quality user interface software by (i) developing digitization hardware for a low-cost, mass production system, (ii) integrating a cloud-based data process system for more efficient data acquisition and interpretation, and (iii) demonstrating online digital twin model for real-time engineering analysis. The ultimate goal is that this scalable distributed monitoring system is used for large infrastructure monitoring projects such as bridges, tunnels, foundations, dams, levees, deep wells, and surface or buried pipelines in partnership with an industrial leader and US Army.
The intellectual merit of this technology, coupled with data from other sensing and data analytics tools, is to significantly enhance the capability in predicting and managing large infrastructure's life expectancy by actively monitoring operational processes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
University of California-Berkeley
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