PREDICTIVE SCIENCE ACADEMIC ALLIANCE PROGRAM IV | DE FOA NA0003284

Opportunity Information: Apply for DE FOA NA0003284

The Predictive Science Academic Alliance Program IV (PSAAP IV) is a U.S. Department of Energy National Nuclear Security Administration (DOE/NNSA) funding opportunity (NOFO DE-FOA-NA0003284) aimed at strengthening the nations academic research capacity in high-end computational science while building a pipeline of next-generation computational scientists. Led by NNSAs Office of Advanced Simulation and Computing (ASC) and Institutional Research and Development Programs (NA-114), in coordination with Lawrence Livermore, Los Alamos, and Sandia National Laboratories, the program supports university-based centers that push the state of the art in predictive simulation, exascale computing, and now explicitly artificial intelligence and machine learning methods that improve quantified predictive capabilities. Awards will be made as cooperative agreements, meaning the government is expected to have substantial involvement during the performance of the work.

PSAAP IV is built around five major technical and programmatic focus areas. First, it supports discipline-focused research that advances predictive science and is enabled by effective exascale computing and modern data science. Second, it emphasizes new mathematics and computer science technologies and methods that make exascale computing effective for real science and engineering applications, with an expectation of development and demonstration rather than purely theoretical work. Third, it adds a strong emphasis on state-of-the-art machine learning and data science for predictive science and engineering, both in terms of using ML and in advancing ML methods suitable for these settings. Fourth, it prioritizes rigorous verification, validation, and uncertainty quantification (VVUQ) for large-scale simulations, reinforcing that predictive capability is not just about producing answers but about demonstrating credibility and quantifying uncertainty. Fifth, it places workforce development on equal footing with technical progress, with the intent to train doctoral-level researchers who can operate at the intersection of physics, computation, and data-driven methods.

The program will fund two types of centers, each with a distinct purpose and set of expectations. Predictive Simulation Centers (PSCs) are the larger, application-driven centers. A PSC must focus on scalable simulations tied to either an integrated, multidisciplinary problem or a broad single discipline, and the work must be carried out using NNSAs unclassified ASC high-performance computing systems that will be made available to funded centers. PSCs have two required demonstration outcomes within the context of their chosen application: (1) they must develop and demonstrate computer science and/or data science technologies and methods that advance exascale computing, and (2) they must demonstrate a verified and validated predictive simulation (or simulation-driven workflow) that includes uncertainty quantification. PSCs are expected to show a compelling step forward in predictive science by integrating advances in physical science, scientific machine learning, and exascale-enabled computational methods, with the practical result being predictions that cover more phenomena with better accuracy and lower uncertainty than what existed at the start of the project. Starting in the second year, PSCs must produce integrated system simulation (or simulation-workflow) results for a single demonstration problem each year, and all center research must feed into that integrated predictive capability, with full integration required no later than the year 4 demonstration milestone. PSC awards are anticipated to run for five years at roughly $1.5 million to $3.5 million per year, with the upper end associated with more complex multidisciplinary applications and centers advancing both computer science and machine learning.

Focused Investigatory Centers (FICs) are smaller and more tightly scoped. They are intended to concentrate effort on a specific research topic, either within a particular discipline or within enabling technologies such as exascale-oriented computer science, machine learning, or VVUQ. Unlike PSCs, FICs do not necessarily need to be tied to a specific end-to-end application, and they are not necessarily required to deliver a full verified, validated, uncertainty-quantified predictive simulation demonstration. Instead, the core expectation is a compelling and significant scientific or technical advance in the focused topic area, described as a qualitative step change rather than incremental progress. FICs are anticipated to be up to five-year awards in the range of $0.5 million to $1.0 million per year.

Eligibility is limited to U.S. institutions of higher education (both public/state-controlled and private) that have doctoral programs, and DOE/NNSA is open to multi-institutional teams using a prime-and-subaward structure with a single lead applicant submitting the application. The funding instrument is discretionary, under CFDA 81.124, and the overall anticipated funding level is about $20 million per year across all awards, subject to congressional appropriations and future-year budget authority. The NOFO anticipates roughly nine total awards, with an award ceiling listed at $3.5 million. The original closing date provided is October 1, 2024.

For applicant support, Grants.gov procedural questions (registration, submission mechanics, and platform troubleshooting) must go directly to Grants.gov support, not to NNSA staff. Program and technical questions are directed to the NNSA Alliance Strategy Team at psaap4-questions@lanl.gov (or via FedConnect), while financial and administrative questions go to the NNSA grants specialist (Kristin.Wegner@nnsa.doe.gov) or via FedConnect.

• The NNSA in the energy, science and technology and other research and development sector is offering a public funding opportunity titled "PREDICTIVE SCIENCE ACADEMIC ALLIANCE PROGRAM IV" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 81.124.
• This funding opportunity was created on 2024-05-22.
• Applicants must submit their applications by 2024-10-01. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
• Each selected applicant is eligible to receive up to $3,500,000.00 in funding.
• The number of recipients for this funding is limited to 9 candidate(s).
• Eligible applicants include: Public and State controlled institutions of higher education, Private institutions of higher education.

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