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PREDICTIVE SCIENCE ACADEMIC ALLIANCE PROGRAM IV
The NNSA Academic Programs and Community Support, Office of Advanced Simulation and Computing (ASC) and Institutional Research and Development Programs (NA-114), Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory (LANL) and Sandia National Laboratories (SNL), are initiating
the next phase of its academic program, called Predictive Science Academic Alliance Program IV (PSAAP IV).
PSAAP IV will add an additional focus, on the development and application of artificial intelligence (AI) and machine learning (ML) technologies to improve quantified predictive capabilities.
The DOE NNSA Academic Programs and Community Support PSAAP IV Notice of Funding Opportunity (NOFO), DE-FOA-NA0003284, and succeeding awarded agreements, are made possible from NNSA’s statutory authority, and are managed by applicable guidance, regulations, and laws.
Predictive Science Academic Alliance Program IV (PSAAP IV) will support leading U. S. institutions of higher education, with doctoral programs, engaging in five major focus areas:
1. Discipline-focused research to further predictive science and enabled by effective exascale computing and data science technologies; 2. Mathematics and computer science (CS) technologies and methodologies to support effective exascale computing in the context of science/engineering applications (development and demonstration); 3. State-of-the-art machine learning (ML) and data science technologies for predictive science and engineering (utilization and advancement); 4. Predictive science based on verification, validation, and uncertainty quantification (VVUQ) for large-scale simulations; and 5. Workforce development of the next-generation computational scientists.
PSAAP IV will create a program consisting of two types of Centers:
Predictive Simulation Centers (PSCs) and Focused Investigatory Centers (FICs).
1. Predictive Simulation Centers (PSCs) will be required to focus their research on scalable application simulations, targeting either large-scale, integrated multidisciplinary problems or a broad single science/engineering discipline, to be carried out on ASC’s unclassified high-performance computing (HPC) systems that will be made available to the funded PSAAP IV Centers.
A PSC must (1) develop and demonstrate computer and/or data science technologies and methodologies that will advance exascale computing, and (2) demonstrate a verified and validated predictive simulation (or simulation-driven workflow) with uncertainty quantification.
Both (1) and (2) must be demonstrated within the context of the proposed application.
It is expected that a PSC will demonstrate a compelling and significant advance in predictive science, in the context of their application.
The overall goal should require the integration of state-of-the-art techniques and advances in physical science, scientific machine learning, and exascale-enabled computer/computational science to demonstrate improved predictive capability.
This should be manifested as predictions of a wider range of phenomena, with improved predictive accuracy and reduced uncertainty, in comparison to existing capabilities at the beginning of the project.
Integrated system simulation (or simulation-driven workflow) results for a single demonstration problem must be produced each year, beginning in the second year of the program.
All research efforts within a PSC must contribute towards advancing this predictive capability and be integrated no later than the year 4 demonstration.
It is anticipated that PSCs will be 5-year awards at $ 1. 5- 3. 5M per year, with the larger-award sizes for Centers targeting multidisciplinary problems and advancing both CS and ML technologies.
2. Focused Investigatory Centers (FICs) will be required to be tightly focused on a specific research topic either in one of the disciplines or one or more of the exascale-enabling CS, ML, or VVUQ technologies listed below.
FICs will not necessarily have a tie to an application or be required to demonstrate a verified, validated predictive simulation with uncertainty quantification.
Successful FIC will demonstrate a compelling and significant scientific advance in the single discipline or enabling technology.
The technical advance should represent a qualitative step up in the discipline, as opposed to incremental progress.
It is anticipated that FIC awards will be up to 5-year awards, at $ 0. 5- 1. 0M per year.
DOE/NNSA will award cooperative agreements under this NOFO.
DOE/NNSA will consider funding multi-institution teams submitted as a prime and subaward model with one application submitted by the lead institution (prime applicant).
Approximately $20,000,000 annually is anticipated to be available for awards under this NOFO.
Funding for all awards and future budget periods are contingent upon the availability of funds appropriated by Congress for the purpose of this program and the availability of future-year budget authority.
Grants.gov Questions Direct questions relating to the Grants.gov registration process, system requirements, application form, or the submittal process must be directed to Grants.gov at 1-800-518-4726 or support@Grants.gov.
DOE/NNSA staff are unable to answer Grants.gov questions.
NOFO Program and Technical Questions Direct specific program and technical questions to NNSA’s Alliance Strategy Team at Psaap4-questions@lanl.gov (preferred) or via FedConnect at www.FedConnect.net.
NOFO Financial and Administrative Questions Direct specific financial and administrative questions to NNSA grants specialist at Kristin.Wegner@nnsa.doe.gov or via FedConnect at www.FedConnect.net.
PSAAP IV will add an additional focus, on the development and application of artificial intelligence (AI) and machine learning (ML) technologies to improve quantified predictive capabilities.
The DOE NNSA Academic Programs and Community Support PSAAP IV Notice of Funding Opportunity (NOFO), DE-FOA-NA0003284, and succeeding awarded agreements, are made possible from NNSA’s statutory authority, and are managed by applicable guidance, regulations, and laws.
Predictive Science Academic Alliance Program IV (PSAAP IV) will support leading U. S. institutions of higher education, with doctoral programs, engaging in five major focus areas:
1. Discipline-focused research to further predictive science and enabled by effective exascale computing and data science technologies; 2. Mathematics and computer science (CS) technologies and methodologies to support effective exascale computing in the context of science/engineering applications (development and demonstration); 3. State-of-the-art machine learning (ML) and data science technologies for predictive science and engineering (utilization and advancement); 4. Predictive science based on verification, validation, and uncertainty quantification (VVUQ) for large-scale simulations; and 5. Workforce development of the next-generation computational scientists.
PSAAP IV will create a program consisting of two types of Centers:
Predictive Simulation Centers (PSCs) and Focused Investigatory Centers (FICs).
1. Predictive Simulation Centers (PSCs) will be required to focus their research on scalable application simulations, targeting either large-scale, integrated multidisciplinary problems or a broad single science/engineering discipline, to be carried out on ASC’s unclassified high-performance computing (HPC) systems that will be made available to the funded PSAAP IV Centers.
A PSC must (1) develop and demonstrate computer and/or data science technologies and methodologies that will advance exascale computing, and (2) demonstrate a verified and validated predictive simulation (or simulation-driven workflow) with uncertainty quantification.
Both (1) and (2) must be demonstrated within the context of the proposed application.
It is expected that a PSC will demonstrate a compelling and significant advance in predictive science, in the context of their application.
The overall goal should require the integration of state-of-the-art techniques and advances in physical science, scientific machine learning, and exascale-enabled computer/computational science to demonstrate improved predictive capability.
This should be manifested as predictions of a wider range of phenomena, with improved predictive accuracy and reduced uncertainty, in comparison to existing capabilities at the beginning of the project.
Integrated system simulation (or simulation-driven workflow) results for a single demonstration problem must be produced each year, beginning in the second year of the program.
All research efforts within a PSC must contribute towards advancing this predictive capability and be integrated no later than the year 4 demonstration.
It is anticipated that PSCs will be 5-year awards at $ 1. 5- 3. 5M per year, with the larger-award sizes for Centers targeting multidisciplinary problems and advancing both CS and ML technologies.
2. Focused Investigatory Centers (FICs) will be required to be tightly focused on a specific research topic either in one of the disciplines or one or more of the exascale-enabling CS, ML, or VVUQ technologies listed below.
FICs will not necessarily have a tie to an application or be required to demonstrate a verified, validated predictive simulation with uncertainty quantification.
Successful FIC will demonstrate a compelling and significant scientific advance in the single discipline or enabling technology.
The technical advance should represent a qualitative step up in the discipline, as opposed to incremental progress.
It is anticipated that FIC awards will be up to 5-year awards, at $ 0. 5- 1. 0M per year.
DOE/NNSA will award cooperative agreements under this NOFO.
DOE/NNSA will consider funding multi-institution teams submitted as a prime and subaward model with one application submitted by the lead institution (prime applicant).
Approximately $20,000,000 annually is anticipated to be available for awards under this NOFO.
Funding for all awards and future budget periods are contingent upon the availability of funds appropriated by Congress for the purpose of this program and the availability of future-year budget authority.
Grants.gov Questions Direct questions relating to the Grants.gov registration process, system requirements, application form, or the submittal process must be directed to Grants.gov at 1-800-518-4726 or support@Grants.gov.
DOE/NNSA staff are unable to answer Grants.gov questions.
NOFO Program and Technical Questions Direct specific program and technical questions to NNSA’s Alliance Strategy Team at Psaap4-questions@lanl.gov (preferred) or via FedConnect at www.FedConnect.net.
NOFO Financial and Administrative Questions Direct specific financial and administrative questions to NNSA grants specialist at Kristin.Wegner@nnsa.doe.gov or via FedConnect at www.FedConnect.net.
Obtain Full Opportunity Text:
Link to Opportunity in MyGrants
Additional Information of Eligibility:
DRL welcomes applications from U.S.-based and foreign-based non-profit organizations/nongovernmental organizations (NGO) and public international organizations; private, public, or state institutions of higher education; and for-profit organizations or businesses.
DRL’s preference is to work with non-profit entities; however, there may be some occasions when a for-profit entity is best suited.
Full Opportunity Web Address:
https://mygrants.servicenowservices.com/mygrants?id=mygrants_form&table=x_g_usd4_d_grant_funding_opportunity&sys_id=3172edb9931a0e10d114b7986cba10e4&view=Default
Contact:
Agency Email Description:
Grant Administration Contact
Agency Email:
Date Posted:
2024-05-22
Application Due Date:
Archive Date:
2024-10-31
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