Project Grant 2204226
- The University of Texas at Austin received a $460,698 Project Grant award from the National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation. The award is supporting research from August 1, 2021 through July 31, 2024 under the NSF Engineering Program (CFDA 47.041). Specifically, the University is developing data-driven model reduction and real-time estimation and control techniques for coherent structures in turbulent flows. The NSF Engineering Program seeks to...
- 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 Texas at Austin was awarded a $528,708 project grant from the National Science Foundation to conduct collaborative research on adverse multiphase flow interactions in urban stormwater systems under the NSF's Engineering program (CFDA 47.041). The three-year project beginning September 1, 2021 will fund research by the University of Texas at Austin, as the primary awardee, and its parent institution the University of Texas System to improve understanding of complex fluid flow...
- 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 project grant award of $600,000 from the National Science Foundation's (NSF) Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering (CFDA #47.070) program will support the development of hybrid models that combine deep neural networks and high-fidelity partial differential equation (PDE) solvers. The goal is to create a system that maintains the accuracy of PDE models while leveraging the speed of neural networks to enable accelerated solutions for...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program provides $399,998 to the University of Texas at Austin (UT Austin) to develop innovative numerical algorithms that integrate classical numerical schemes and deep learning techniques. The goal is to address complex scientific computing challenges, such as simulating high-dimensional, fully nonlinear differential equations, long-term Hamiltonian system simulations, and...
- The National Science Foundation Office of Advanced Cyberinfrastructure awarded the University of Texas at Austin a $1.2 million Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070) from September 1, 2022 to August 31, 2025. The grant funds research to develop a rigorous and reliable scientific deep learning framework for forward, inverse, and uncertainty quantification problems in computational science and engineering. Specific objectives include...
- This National Science Foundation Project Grant of $229,021 awarded on August 1, 2022 will support research at the University of Texas at Austin to develop mathematical frameworks in optimal transport applications to probability, machine learning, and kinetic theory through July 31, 2025. Under the Mathematical and Physical Sciences program (CFDA 47.049), the investigator will advance understanding of stochastic modeling, artificial intelligence algorithms, and kinetic theory by exploiting...
- The University of Texas at Arlington (UTA) received a $299,632 Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) to develop a reliable and efficient LIUTEX-based sub-grid model for Large Eddy Simulation (LES) of turbulent flows. The project aims to (1) create a new LIUTEX-based sub-grid model, (2) develop a dynamic LIUTEX-based sub-grid model, (3) test the new models in various computational fluid dynamics cases, and (4) evaluate the performance...
- The University of Texas at Austin received a $398,286 Project Grant award from the National Science Foundation to support research related to stimuli-responsive soft materials. The grant was awarded on September 1, 2021 under the Engineering (CFDA 47.041) program with a completion date of January 31, 2023. Through this funding, the University will deliver research developing soft materials that can change properties in response to external stimuli, advancing innovations at the intersection of...
The University of Texas at Austin was awarded a $405,278 Project Grant from the National Science Foundation Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering program (CFDA 47.070) to develop methods for simulating Stokesian complex fluid flows. The award period is from September 1, 2022 to August 31, 2025. Under this grant, the University will design high-performance computing algorithms that integrate dimension reduction and deep learning methods with integral equation approaches. This is intended to significantly accelerate predictive simulations of Stokesian complex fluid flows involving moving interfaces and microstructure evolution. The University will also create software infrastructure to automate configuration sampling, operator splitting, deep network training and inference for various complex fluids. Finally, the grant supports evaluation of the proposed methodology on problems involving calculation of effective properties, parameter estimation and shape optimization of microfluidic devices.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $405.3k | 5/20/22 |