This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports fundamental research and development at the University of Tulsa to advance the modeling and analysis of CO2 transport in porous media for geological carbon sequestration. The $157,471 award, effective July 1, 2024 through March 31, 2025, aims to develop computationally efficient data-driven models to predict and analyze the complex flow behavior of CO2 in geological formations. The...
The National Science Foundation awarded a $500,000 Project Grant to Texas A&M Engineering Experiment Station to support research titled "CAREER: AN INTEGRATED EXPERIMENTAL-THEORETICAL FRAMEWORK FOR UNDERSTANDING THE MULTISCALE MECHANICAL RESPONSE OF ROCK-REACTIVE BRINE INTERACTIONS." The award was made under the Engineering (47.041) program on February 1, 2021 for a five-year period concluding January 31, 2026. The grant funding will support the development of an integrated...
This $403,966 federal Project Grant award from the National Science Foundation (NSF) Division of Chemical, Bioengineering, Environmental, and Transport Systems under the NSF Engineering program (CFDA 47.041) aims to achieve a transformative understanding of pore-scale transport and chemical reaction in porous media. The goal is to reconcile the long-standing "lab-field discrepancy" in modeling mineral dissolution, which is crucial for accurately predicting carbon dioxide (CO2)...
This $555,274 project grant from the National Science Foundation's Engineering program (CFDA 47.041) supports research into the nanoscale physics of carbon dioxide utilization and storage in tight oil reservoirs. The Colorado School of Mines, in collaboration with Virginia Polytechnic Institute & State University, will investigate how CO2 interacts with oil at pore walls and gradients along walls modulate oil-CO2 transport through nanopores. Researchers will integrate bench-scale...
Oklahoma State University was awarded a $267,000 project grant from the National Science Foundation Division of Mathematical Sciences to support research titled "Stabilizing Phenomenon for Incompressible Fluids" from June 1, 2021 through May 31, 2024. The grant was awarded under the Mathematical and Physical Sciences program (CFDA 47.049), which aims to promote progress in the mathematical and physical sciences and strengthen the nation's scientific enterprise through increasing...
This Project Grant from the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049) provides $210,272 to Penn State University for collaborative research on adaptive mixed-dimensional modeling and simulation of porous media from August 1, 2022 to July 31, 2025. The research aims to develop stable numerical methods for simulating flow in fractured porous media based on mixed-dimensional modeling approaches. Key products include advanced...
Oregon State University was awarded a $350,376 Project Grant from the National Science Foundation Division of Chemical, Bioengineering, Environmental, and Transport Systems under the Engineering program (CFDA 47.041). The three-year award will support research titled "TRANSPORT IN TURBULENT BOUNDARY LAYERS OVER PERMEABLE BEDS: PORE-RESOLVED DIRECT SIMULATIONS AND MACROSCALE CONTINUUM MODELING" from June 2021 through May 2024. The research will involve pore-resolved direct simulations...
This National Science Foundation (NSF) Geosciences Program (CFDA 47.050) Project Grant award totaling $427,296 aims to advance the understanding of solute dispersion in unsaturated porous media, which has critical implications for processes like nutrient and contaminant transport in the vadose zone. The research project, awarded to the Trustees of the Stevens Institute of Technology, will leverage pore-scale numerical simulation, microfluidics, and 3D printing technologies to study how complex...
The University of Oklahoma will provide research services under a $406,062 Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041). Specifically, the university will develop an artificial intelligence and data mining decision support tool to improve flexible reservoir system modeling enabled by subseasonal-to-seasonal hydroclimatological forecasts. Researchers will leverage deep learning models to correct spatial and temporal errors in precipitation forecasts...
This $180,267 federal Project Grant award from the National Science Foundation (NSF) Geosciences Program (CFDA 47.050) aims to investigate the impact of climate change on karst groundwater resources using advanced deep-learning techniques. The research, led by Sam Houston State University, will develop innovative deep-learning models to analyze comprehensive data from U.S. karst aquifers and integrate climate projection data to forecast the future status of these critical groundwater resources...