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...
This Project Grant award from the National Science Foundation (NSF) Geosciences Program (CFDA 47.050) provides $299,539 to Georgia Tech Research Corporation (Georgia Tech) to develop novel machine learning approaches to decode high-resolution earthquake catalogs and improve earthquake forecasting. The project aims to advance scientific understanding of earthquake dynamics by integrating advanced statistical models, machine learning techniques, and high-resolution seismic data. Key strategies...
This federal Project Grant award of $650,000 from the National Science Foundation's Geosciences Program (CFDA 47.050) supports a collaborative research project to develop an AI model that better understands fault dynamics and stress transfer mechanisms within complex fault networks. Led by the University of Southern California, the project aims to build a multiphysics fault network model that can discover reduced-order governing equations for the evolution of stress in these systems. This work...
This Project Grant, awarded by the National Science Foundation (NSF) under the Geosciences program (CFDA 47.050), is funding a $175,000 collaborative research project to develop an AI model that can better understand fault dynamics and the evolution of stress within complex fault networks. The project, led by the California Institute of Technology (Caltech), aims to build a multiphysics fault network model that can discover reduced-order governing equations to assess regional earthquake and...
The National Science Foundation (NSF) awarded a $198,564 Project Grant under the Geosciences Program (CFDA 47.050) to the University of Southern California (USC) for the establishment of the Center for CO2 Storage Modeling, Analytics, and Risk Reduction Technologies (CO2-SMART). This five-year research center is a partnership between USC and Pennsylvania State University, and aims to accelerate the safe and cost-effective sequestration of carbon dioxide (CO2) in deep geological formations. Key...
This three-year $767,724 Project Grant from the National Science Foundation's Division of Ocean Sciences, under the Geosciences program (CFDA 47.050), will fund research to quantify biological productivity and ocean carbon uptake in the northeastern Subarctic Pacific. The awardee, Georgia Tech Research Corporation, will integrate in-vitro, in-situ and satellite observations with high-performance modeling. Fieldwork in June 2024 will include incubation experiments and underway measurements at...
This $398,984 Project Grant award, provided by the National Science Foundation's Geosciences Program (CFDA 47.050), supports research to quantify the biophysical, physiological, and phenological impacts of increasing carbon dioxide (CO2) levels on vegetation and their effects on future climate change. The research utilizes the Community Earth System Model to examine the direct impacts of CO2 fertilization and stomatal closure, as well as the indirect effects of a longer growing season, on...
This Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) provides $299,809 to the University of Memphis to investigate how faults respond to rapid changes in stress in geothermal reservoirs. The project aims to deploy seismometers, analyze earthquake data using machine learning, and develop computational models to understand the link between operational changes and induced seismic activity. The researchers will examine this phenomenon at the Blue Mountain...
The National Science Foundation awarded a $675,271 Project Grant to the Georgia Tech Research Corporation from October 1, 2021 to September 30, 2024 under the Computer and Information Science and Engineering program (CFDA 47.070). The grant supports collaborative research on principled uncertainty quantification in deep learning models for time series analysis. The Computer and Information Science and Engineering program aims to advance computing and informatics research. This award will further...
This $126,270 federal Project Grant award was provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to the University of Pittsburgh. The project aims to develop new artificial intelligence (AI) capabilities to significantly enhance the monitoring and understanding of forest carbon dynamics in the Earth system. Key products and services to be delivered include: Cross-platform and cross-region learning frameworks to enable...