Project Grant NA24OARX021G0008
Award Date
8/1/24
Completion Date
1/31/25
Dollars Obligated
$350K
Federal Agency
National Oceanic and Atmospheric Administration
Federal Grant Program
11.021
Assistance Type
Project Grant
Place of Performance
Peralta, NM 87042, USA
Similar Awards
This Project Grant award, funded by the National Science Foundation (NSF) under the Geosciences program (CFDA 47.050), supports research to develop new technologies that integrate advanced artificial intelligence (AI) and machine learning (ML) with established geoscientific domain knowledge to enhance understanding of landslide causality. The $674,291 award, effective October 1, 2024 through September 30, 2027, will enable the Research Foundation of the City University of New York (RFCUNY) to:...
This Project Grant award of $500,000.00 from the National Science Foundation's Geosciences Program (CFDA 47.050) is funding the development of a transformative AI-based framework for generating high-fidelity, physically consistent, and uncertainty-calibrated geoscience data. The goal is to overcome limitations in observational infrastructure and computational cost to produce enhanced datasets that can improve decision-making for disaster preparedness, emergency response, and infrastructure...
This Project Grant award of $199,316.00 from the National Science Foundation's (NSF) Geosciences Program (CFDA 47.050) aims to advance the understanding of how extreme weather events, such as heavy rainfall and flooding, may change in response to future climate scenarios. The project, titled "EMBRACE-AGS-SEED: Harnessing the Power of Machine Learning to Generate Ensembles of Regional Climate Projections," will evaluate whether artificial intelligence and machine learning can provide...
This Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) provides $462,400 to the University of California San Diego, Scripps Institution of Oceanography, to develop advanced machine learning techniques for generating realistic, synthetic earthquake ground motion simulations. The goal is to create a faster, more generalizable physics-based model that can efficiently study large, infrequent earthquakes and assess their hazards for California and Nevada....
This $460,515 Civil, Mechanical, and Manufacturing Innovation Project Grant awarded by the National Science Foundation (NSF), under its Engineering program (CFDA 47.041), supports research at the University of Colorado to understand the risk of increased catastrophic landslides due to climate change. The key activities include: Conducting thermal triaxial tests and centrifuge experiments to study how changes in soil temperature affect the stability and failure mechanisms of thermally sensitive...
This Project Grant award of $386,220 from the National Science Foundation's Geosciences Program (CFDA 47.050) will support the development of machine learning techniques to generate realistic, synthetic earthquake ground motion data. The key products of this project include: Physics-based machine learning models, named Operator Inference (OPINF), that can create time-dependent parametric surrogate models of seismic ground motions by fusing simulated wavefields with observed earthquake records....
This Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) provides $353,178 to the University of Florida to develop a transformative AI-based framework for generating high-fidelity, physically consistent, and uncertainty-calibrated geoscience data. The goal is to overcome limitations in observational infrastructure and computational cost to produce enhanced datasets that will support better decision-making in disaster preparedness, emergency response,...
This Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) provides $650,000 over a 3-year period to the University of Southern California to develop an AI model that can better understand fault dynamics and earthquake hazards in heavily faulted geologic basins. The project builds a multiphysics fault network model to discover reduced-order governing equations for the evolution of stress in complex fault systems, using the Southern Permian Basin in the...
This Project Grant award of $458,784 from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program supports a research project at Lehigh University focused on enhancing disaster response and recovery capabilities. The project aims to develop advanced, physics-informed machine learning models that integrate autonomous systems and numerical hazard models to improve real-time damage assessment and decision-making for natural disasters such as...
This $225,351 Project Grant award, funded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), will support the development of AI emulator tools for improving the estimation of statistics for rare and extreme climate events, such as heat waves and cold spells. The project, led by New York University (NYU), will focus on creating novel methods to leverage AI techniques to better model and predict the impacts of these...