Predictive Science Academic Alliance Program

(1) To focus on development and demonstration of modeling/simulation technologies and methodologies through the structure of Multidisciplinary Simulation Centers, Single-Disciplinary Centers, and Focus Investigatory Centers to solve open science and

The Predictive Science Academic Alliance Program (PSAAP) engages with leading U.S. universities, focusing on the development and demonstration of technologies and methodologies to solve open science and engineering application problems. The research performed by the universities in this program is discipline-focused to further predictive science and enabled by effective use of high-performance computing. Predictive science is the aim of this program and is based on verification and validation and uncertainty quantification methodologies for large-scale simulations.

Applicants (either prime or sub applicant) must be an institution of higher education in any state, federal district, or United States territory. Prime applicants must provide an educational program for which the institution awards a professional doctoral degree (e.g. Doctor of Philosophy or PhD).

Only institutions of higher education in any state, federal district, or United States territory.

Financial support in whole or in part may be provided for such purposes as salaries, materials and supplies, equipment, travel, publication costs, training costs, and services required for conducting research, training, NNSA laboratory internships, and advanced technology projects or assessments. Funding is provided for applied research in the field of computational science in support of the NNSA Stockpile Stewardship program. Restrictions on use of funds depend on grant provisions. Funding is provided for the purpose of exploring a research idea that does not unnecessarily duplicate work already in progress or contemplated by DOE, is not already known to DOE, or has previously unrecognized merit.

The NNSA cooperative award assistance is available for total of 5 project-year time window, subject to approval of annual renewals. The annual funding should be expended within the allocated timeframe, with at least 10% allowed for carryover to the next fiscal year.

A Request for Information (RFI) for PSAAP III was initiated by the National Nuclear Security Administration (NNSA) Office of Advanced Simulation and Computing (ASC) and Institutional Research and Development Programs, Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory (LANL) and Sandia National Laboratories (SNL). An RFI was issued on June 29, 2018 with a deadline of August 3, 2018 for eligible institutions to submit a preliminary application in accordance with the guidelines stated in the PSAAP III RFI document. We released a Funding Opportunity Announcement in mid FY19. The selected PSAAP III Centers began during FY20. During FY24, 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), initiated 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 PSAAP IV Notice of Funding Opportunity was posted on May 22, 2024.

Applications should be submitted as specified in the notice of funding opportunity posted at http://www.grants.gov.

(1) Alignment with the areas of technical scope called forth in the call for application; (2) Scientific/technical merit of the project; (3) Expected impact on the proposed area of research activity; (4) Consistency with the objective of this academic alliances program to focus on advanced computational science investigations; (5) Qualifications of the Applicant's personnel and adequacy of proposed resources; (6) Feasibility of plans for carrying out the proposed research, considering such factors as: appropriateness of the technical method and approach, facility compatibility, other commitments, competition and timing; (7) Level of interaction with NNSA laboratory personnel and the potential to train students in scientific areas defined by the technical scope in order to build a long-term recruiting pool for the NNSA laboratory complex; (8) Leverage provided by cost sharing by applicant and with other funding sources.

Proposals will be screened for ASC programmatic relevance and then reviewed for scientific and technical merit by qualified individuals. Recommendations for award are made by the ASC office, Defense Programs, NNSA, and selected proposals will be forwarded to NNSA Partnership Acquisition Services, for grant development and award.

See individual opportunity announcements at http://www.grants.gov for deadlines for each specific announcement.

Applications for annual renewal are subject to review and acceptance by the NNSA Office of Advanced Simulation and Computing and Institutional Research & Development.