| NSF Org: |
CBET Division of Chemical, Bioengineering, Environmental, and Transport Systems |
| Recipient: |
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| Initial Amendment Date: | November 21, 2022 |
| Latest Amendment Date: | December 12, 2024 |
| Award Number: | 2237537 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Ron Joslin
rjoslin@nsf.gov (703)292-7030 CBET Division of Chemical, Bioengineering, Environmental, and Transport Systems ENG Directorate for Engineering |
| Start Date: | December 1, 2022 |
| End Date: | November 30, 2027 (Estimated) |
| Total Intended Award Amount: | $531,898.00 |
| Total Awarded Amount to Date: | $531,898.00 |
| Funds Obligated to Date: |
FY 2025 = $116,427.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
1109 GEDDES AVE STE 3300 ANN ARBOR MI US 48109-1015 (734)763-6438 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
503 THOMPSON ST ANN ARBOR MI US 48109-1340 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | FD-Fluid Dynamics |
| Primary Program Source: |
01002526DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.041 |
ABSTRACT
Turbulent flows are ubiquitous in science and engineering, and their wide range of spatial and temporal scales make them simultaneously expensive to simulate and challenging to model. Effective reduced-order models that can be used in place of costly simulations are urgently needed to accelerate scientific discovery, engineering design, and control of turbulent flows. This project will fill this need by developing a new class of reduced-order models that, by respecting key aspects of turbulent flow physics, overcome longstanding limitations of previous methods. These new tools will be applicable to a wide range of turbulent flows and can be applied by researchers in academia, government labs, and industry to achieve objectives such as preventing the adverse health effects of excessive noise exposure by mitigating acoustic emissions of jet engines and wind turbines and improving our understanding of climate change by enhancing predictive modeling capabilities of geological flows. The research program is closely integrated with a comprehensive education program, the central component of which is a series of professionally produced videos, each spotlighting a key contributor to the field of fluid dynamics and the impactful problems they work on. By highlighting a diverse set of researchers and focusing on not just the science, but also the scientist, the videos will help empower students to envision themselves as future fluid-dynamics researchers.
The technical goal of the project is to develop a pair of new models tailored for long- and short-time prediction of turbulent flows. The critical observation is that typical reduced-order models based on expansion of the flow state into spatial modes and time-varying coefficients, such as standard Galerkin models and their modern alternatives, violate the intimate physical relationship between spatial and temporal scales of the flow. By working within a nascent space-time modeling framework, in which the flow state is expanded into modes that depend on both space and time, and strategically selecting the temporal basis functions, the proposed approach respects the physical relationship between spatial and temporal scales. Critical tasks to bring this framework to maturation include developing optimal spatial bases, sparsifying triadic nonlinear interactions, and deriving error estimates. To accelerate and streamline their adoption, the methods developed during this project will be incorporated into the open-source platform Pressio maintained by Sandia National Laboratory.
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.
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