Project Grant 2438536
- This Project Grant award of $218,701 from the National Science Foundation's (NSF) Geosciences Program (CFDA 47.050) supports collaborative research to better understand the complex behaviors of dense granular media, such as those found in avalanches, volcanic flows, and river sediments. The research team from the Massachusetts Institute of Technology (MIT) will develop new models that combine laboratory experiments, advanced numerical simulations, and artificial intelligence (AI) to capture...
- This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports research to address critical gaps in understanding, modeling, and predicting soil behavior during transitions from solid-like to fluid-like motion, such as during landslides. The $642,143 award, spanning June 1, 2025 to May 31, 2030, will enable the University of Maine System to: 1) measure the statistical characteristics of particle collisions using discrete element modeling, 2)...
- This Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $363,492 to support fundamental research on the behavior of fluid-coupled granular media. The research aims to advance experimental techniques and theoretical understanding of how external loads are transmitted through the network of contact forces, or "force chains," within granular materials such as soils, concrete, and ballast. The research is being conducted by the...
- This Project Grant from the National Science Foundation's Division of Chemical, Bioengineering, Environmental, and Transport Systems provides $255,634 to support research advancing understanding of particle-laden gravity currents under the Engineering program (CFDA 47.041). The Massachusetts Institute of Technology will collaborate with analytical modeling, numerical simulation, laboratory experimentation, and unique field data to develop empirical models predicting transport processes in...
- This National Science Foundation (NSF) Project Grant award, under the Federal Grant Program CFDA 47.041 (Engineering), provides $651,674 to the Trustees of Boston University to conduct fundamental research on the mechanics of elastogranular metamaterials. The research aims to understand how the interplay between localized confinement (such as cohesion, adhesion, and packing geometry) and elastic instabilities in slender structures interacting with granular matter enables the development of...
- This $275,000 Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) will fund collaborative research to investigate the gravity-dependence of dense granular flows. The research team, led by the University of California, Berkeley, will create powder-flow experiments small enough to be conducted on the International Space Station (ISS) and compare those results to experiments performed on Earth. This will allow the development of reliable digital twin...
- This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) is for a collaborative research effort on the behavior of cohesive immersed granular materials. The $330,000 award to the University of California, Santa Barbara will integrate laboratory experiments and particle-resolved numerical simulations to develop a quantitative framework connecting particle-level cohesion to the macroscopic flow and rheology of materials like river/seabed sediments and...
- This Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) in the amount of $558,188 awarded on January 15, 2026 aims to advance scientific understanding of the behavior of dense granular media in geoscience applications. The project brings together researchers from geosciences, computer science, and engineering to develop new models that better capture the complex behaviors of particle-laden flows, such as those found in avalanches, volcanic flows, and...
- The Massachusetts Institute of Technology (MIT) received a $400,000 project grant award from the National Science Foundation (NSF) Division of Information and Intelligent Systems on October 1, 2021. The award is part of the NSF's Computer and Information Science and Engineering program (CFDA 47.070) to support collaborative research on computational design of complex fluidic systems through September 30, 2025. Under the award, MIT researchers will work with NSF to advance development of...
- This Project Grant award of $329,956, provided by the National Science Foundation's Engineering program (CFDA 47.041), supports collaborative research on cohesive immersed granular flows. The project aims to develop a quantitative framework connecting particle-level cohesion to the macroscopic flow and rheology of immersed granular materials, such as river and seabed sediments and industrial slurries. The research will integrate laboratory experiments and particle-resolved numerical...
This Project Grant award, funded by the National Science Foundation's (NSF) Engineering program (CFDA 47.041), supports fundamental research to advance the understanding of fluid-coupled granular media behavior. The $409,405 award, effective September 1, 2025 through August 31, 2028, is provided to the Massachusetts Institute of Technology (MIT) to develop new experimental techniques and associated theory to observe the transmission of external loads on both the single-grain scale and the granular pack scale of fluid-coupled granular media. The research outcomes are intended to provide new knowledge about the organization of contact forces in these complex systems, and help predict their behavior in natural settings like landslides and earthquakes, as well as in engineering applications such as construction materials, infrastructure, and robotics. The research findings will be integrated into MIT's undergraduate and graduate courses, and disseminated through multiple outreach activities.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $409.4k | 8/21/25 |