This $499,624 National Science Foundation project grant supports research at the University of Pittsburgh to develop physics-guided machine learning methods for turbulent flow simulation. Funded under the NSF's Computer and Information Science and Engineering program (CFDA 47.070), the three-year award aims to advance computational fluid dynamics capabilities. Specifically, the university researchers will create a new deep learning model incorporating physical constraints to reconstruct...
The National Science Foundation (NSF) awarded a $220,000 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to the University of Pittsburgh. The 3-year grant supports research on improving the accuracy, decreasing the complexity, and exploring promising computational algorithms for Unsteady Reynolds Averaged Navier-Stokes turbulence models. This research aims to advance the modeling and numerical simulation of turbulent fluid flows, which is essential for...
The National Science Foundation (NSF) Engineering program (CFDA 47.041) has awarded a $349,999 Project Grant to the University of Texas at Austin to develop reliable Reynolds Averaged Navier-Stokes (RANS) turbulence models that can generalize to complex turbulent flows. The objective is to improve the predictive capabilities of computational fluid dynamics simulations, which have applications in aerospace, automotive, power generation, and wind energy sectors. The approach involves developing...
This $204,884 Project Grant award from the National Science Foundation (NSF) Directorate for Mathematical and Physical Sciences (CFDA 47.049) supports research by Towson University to study various subgrid scale turbulence models and their connections to the Navier-Stokes equations. The research aims to explore the mathematical properties of these turbulence models, apply data assimilation algorithms, and leverage deep learning methods for parameter estimation. Key focus areas include...
The University of Pittsburgh received a $424,546 project grant award from the National Science Foundation Division of Mathematical Sciences on July 15, 2021 to support work on the TIME ACCURATE PREDICTION OF FLUID MOTION project through June 30, 2024. The grant is part of the NSF's Mathematical and Physical Sciences program (CFDA 47.049), which aims to promote progress in these scientific fields and strengthen the nation's scientific enterprise through increasing knowledge and enhancing...
This Project Grant award from the National Science Foundation (NSF) Engineering Directorate (CFDA 47.041) provides $523,552 to the University of Texas at Austin to develop advanced computational models for simulating complex turbulent fluid flows. The research aims to create reliable, broadly applicable turbulence models for use in Large Eddy Simulation (LES) to enable more practical and accurate simulations across fields like aeronautics, propulsion, power generation, and wind energy. In...
The University of Pittsburgh was awarded a three-year $338,526 Project Grant from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) to develop structure-preserving finite element methods for incompressible fluid flow modeling applications. Under the award, set to run from July 2023 through June 2026, the University will conduct research focused on improving existing divergence-conforming finite element methods for solving Navier-Stokes equations...
The National Science Foundation Division of Chemical, Bioengineering, Environmental, and Transport Systems awarded a $362,956 Project Grant to the University of Notre Dame du Lac to develop deep learning closure models and optimization methods for large-eddy simulations of unsteady aerodynamics under the Engineering (47.041) federal grant program. The University of Notre Dame will use the three-year funding period beginning October 1, 2022 to enhance the predictive accuracy of turbulence...
This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to advance the understanding of pulsatile turbulent flows over rough surfaces and develop new predictive tools for these complex flow phenomena. The $154,994 award, which runs from December 1, 2024 to November 30, 2029, will fund high-resolution simulations, novel statistical analyses, and physics-based modeling to characterize the temporal and spatial coherence of turbulent boundary...
The National Science Foundation Division of Atmospheric and Geospace Sciences awarded a $453,861 Project Grant to the University of Pittsburgh to support research titled "Turbulence in the Long-Lived, Very Stable Atmospheric Boundary Layer." The award period is from June 1, 2022 to May 31, 2025. The grant funds research aimed at better understanding turbulence under stable atmospheric conditions, such as those frequently observed at night or during cold seasons, and developing reliable...