Project Grant 2208136
Award Date
9/1/22
Completion Date
8/31/24
Dollars Obligated
$297K
Federal Grant Program
47.041
Assistance Type
Project Grant
Place of Performance
Clemson, SC 29634, USA
Similar Awards
This $445,930 National Science Foundation project grant through the Engineering (47.041) program will fund the development of efficient methods to calibrate models for missing physics in simulations of complex turbulent reacting flows. The University of Notre Dame will optimize turbulence closures and develop an adjoint-based optimization method for canonical flows and a co-optimization framework leveraging adjoint and ensemble Kalman-based optimization for geometrically complex flows. The...
This $354,405 Project Grant awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) to Arizona State University aims to develop a modeling framework for large-eddy simulation of turbulent premixed flame in order to discover closure terms that describe combustion-induced energy backscatter. The research is expected to provide new subgrid-scale models that can accurately capture energy backscatter in turbulent premixed flame, which is critical for improving the...
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...
This $200,000 Project Grant awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports research at the University of Missouri System's Missouri University of Science & Technology to investigate compressibility effects on turbulence production in supersonic flows. The goal is to improve understanding of the mixing process in supersonic combustors for hypersonic flight applications. The project will utilize two-point focused laser differential interferometry to...
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...
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...
This $270,480 National Science Foundation project grant will support the development of adaptive physics-informed machine learning strategies for turbulent combustion modeling at Louisiana State University from June 2022 to May 2025. The university will work to address the excessive computational costs of simulating turbulent combustion by introducing machine learning models within physically derived low-dimensional manifolds. These models will be adaptive, consistent with underlying physical...
This Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $350,000 in funding to Harvard University to develop reliable and predictive computational models for simulating complex turbulent flows. The objective is to create generalized Reynolds Averaged Navier-Stokes (RANS) turbulence models that can accurately predict turbulent flows, which are essential for advancing key technologies in sectors such as aerospace, automotive, and power...
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...
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...