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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

HHH whitepaper

Abstract We here report on the progress of the HHH Workshop, that took place in Dubrovnik in July 2023. After the discovery of a particle that complies with the properties of the Higgs boson of the Standard Model, all Standard Model (SM) parameters are in principle determined. However, in order to verify or falsify the model, the full form of the potential has to be determined. This includes the measurement of the triple and quartic scalar couplings. We here report on ongoing progress of measurements for multi-scalar final states, with an emphasis on three SM-like scalar bosons at 125$$\,\text {Ge}\hspace{-.08em}\text {V}$$ Ge V , but also mentioning other options. We discuss both experimental progress and challenges as well as theoretical studies and models that can enhance such rates with respect to the SM predictions.

Physics↗
DOE OSTI2025

t -channel dark matter models – a whitepaper

This report, summarising work achieved in the context of the LHC Dark Matter Working Group, investigates the phenomenology of t -channel dark matter models, spanning minimal setups with a single dark matter candidate and mediator to more complex constructions closer to UV-complete models. For each considered class of models, we examine collider, cosmological and astrophysical implications. In addition, we explore scenarios with either promptly decaying or long-lived particles, as well as featuring diverse dark matter production mechanisms in the early universe. By providing a unified analysis framework, numerical tools and guidelines, this work aims to support future experimental and theoretical efforts in exploring t -channel dark matter models at colliders and in cosmology.

Arina, Chiara [Universite Catholique de Louvain, L↗
DOE OSTI2024

The Digital Assurance for High Consequence Systems (DAHCS) Mission Campaign Whitepaper

The DAHCS (pronounced “Dax”) MC is a 7-year, $\$$45 million research portfolio within Sandia’s Laboratory Directed Research and Development program. The DAHCS MC arose in response to a great need: to ensure that the use of digital technologies does not weaken our nation’s high consequence systems. Digital technologies offer many benefits in speed, cost, and flexibility, and we seek to reap those benefits without introducing new system failures. However, digital technologies cannot be evaluated the same way as analog technologies. Initiatives across the nation highlight the capability gap that prevents efficient, effective digital assurance. The Challenge Today’s digital assurance tools, techniques, and methods are inadequate to confidently characterize, assess, and manage digital risk; they are ad hoc, slow, costly, and rarely scalable to increasingly complex digital technologies. The rapidly evolving cyber threat landscape exacerbates this problem because digital assurance now must secure against digital risks now and in the future, including those introduced by rapidly evolving technologies, adversaries, and systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Whitepaper: Optimal Control from a Fluid Dynamics Perspective

An optimal control problem described by the Hamilton-Jacobi-Bellman equation can be developed into a problem that can be solved by general computational fluid dynamics packages. We describe how this formulation would allow a classical problem in optimal control, Zermelo’s problem, to be treated as a multi-fluid problem. This approach has the advantage of allowing optimal navigation problems to be conducted over large areas, as well as to include moderately larger numbers of ships. We draw comparisons between this approach and the field of fluid control for fluid animations in movies.

42 ENGINEERING↗
DOE OSTI2024

Enhancing Cloud Cybersecurity: Prescriptive Controls for Operational Technology

This whitepaper provides strategic insights and recommendations into security cloud-based solutions for electric utilities, encompassing operational technology (OT), virtual power plants (VPP), distributed energy resources (DERs), applications, networks, and data storage as they transition to and leverage cloud infrastructure through managed service providers (MSPs) and cloud service providers (CSPs). Principles derived from established frameworks serve as a foundation for best practices across cybersecurity projects and remove the constraints of settling on a single framework. For organizations that prefer not to integrate a specific framework altogether, elements of the proposed approach could be adopted or tailored to best fit defined requirements and expected functionalities. The Cirrus assessment, a utility cloud feasibility tool, and the roadmap it provides serve as a precursor to this paper, which seeks to be a valuable resource for defining next steps following cloud technology integration feasibility appraisal. With its comprehensive approach to adoption, the Cirrus framework offers strategic guidance on responsibly preparing for or deploying a utility cloud solution. The previously published whitepaper, “Use Case-Informed Framework for Utility Cloud Migration,” details the guiding strategy, research, and deployment of cloud solutions within electric and interconnected grid systems. Before implementing the controls suggested in this document, it is recommended that stakeholders complete Cirrus's cloud integration assessment and pair the results with their unique cybersecurity controls to form a comprehensive cloud-based utility cybersecurity plan. The Cirrus outcome will consider a series of future architectures for the grid before and after the energy transition and evaluate the arguments for and against cloud applications for each electric and interconnected grid layer. This document is a companion to the original whitepaper, "Use Case-Informed Framework for Utility Cloud Migration" to further identify and recommend security controls based on Cirrus’s cloud integration assessment output. The following whitepaper outlines the cybersecurity controls that secure cloud-service models pertinent to the electric sector using the predefined categories identify, protect, detect, and respond and recover. The objective is to outline prescriptive security controls based on the type of architecture and data stored in the cloud. The focus includes dissecting the shared responsibility model and elucidating what on-premises Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) entail. A pivotal consideration in this context is allocating responsibility for foundational cybersecurity aspects—having used Cirrus for the cloud integration assessment. The ensuing controls detailed herein also represent a checklist of controls necessary for a secure cloud transition, equipping utilities with the knowledge to navigate this digital transformation with confidence and strategic foresight in a safe and responsible manner.

42 ENGINEERING↗
DOE OSTI2024

Generative AI for Power Grid Operations

Generative artificial intelligence (AI) has captured into the mainstream, demonstrating capabilities that once belonged solely to the realm of human cognition. From defeating world champions in complex games to generating human-quality text and images, Generative AI has proven its potential to revolutionize countless industries. The electric power grid is no exception. Generative AI's ability to process vast amounts of data rapidly, assist decision support and identify patterns could significantly enhance power grid operations. For example, Generative AI could improve state estimation where measurements are not available or integrate renewable energy sources more efficiently with probabilistic forecasting. The key contributions of this whitepaper are outlined below: (1) Comprehensive overview of Generative AI's applications in power grid operations: It highlights the opportunities in areas such as forecasting, state estimation, and demonstrating the potential for enhancing efficiency, reliability, and resilience. (2) Expanding Generative AI's impact through synergies with emerging technologies: The paper introduce NREL developed eGridGPT and explores how AI orchestration, multi-agent systems, and Digital Twins can collaborate to optimize grid operations, addressing the complexities of a decarbonized and electrified future. (3) In-depth analysis of challenges in implementing Generative AI: This includes considerations like data availability and quality, model validation, certification, and ethical concerns, ensuring responsible AI deployment. (4) Emphasizing human-AI collaboration: The whitepaper underscores the importance of trustworthy, transparency, and explainability in AI systems to promote seamless interaction between human operators and AI, ultimately improving decision-making. (5) Exploring future research and development: It identifies critical areas for further advancement to fully realize Generative AI's potential in power grid operations. This whitepaper serves as a valuable resource for researchers, practitioners, and policymakers looking to harness Generative AI for a more reliable, stable, and cost-effective power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

The Compelling Need for a Mid-Scale Stellarator Facility

In the pursuit of the goal of commercial fusion as an abundant and safe source of energy, the stellarator is a leading concept with compelling attractiveness and demonstrated performance. In this white paper we, as a community of US researchers from Universities, National Laboratories, and Private Industry, involved in studying the stellarator concept, lay out the programmatic and technical motivation for a new mid-size stellarator research facility in the US. This contribution is complementary to several other whitepapers authored by members of our community which address different mid-scale stellarator aspects. A community based technical facility proposal has been prepared by F. Parra, et al: Flexible Stellarator Physics Facility. Two private stellarator companies have submitted proposals supporting the development of a mid-scale stellarator: Thea Energy (C.P.S. Swanson, et al.), Type One Energy (W. Guttenfelder, et al.).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

The Updated Case for a National Stellarator Program

The stellarator concept provides a compelling path to a Fusion Pilot Plant that features steady state, disruption free operation with low recirculating power. The need for a national stellarator program and a new stellarator experiment have been highlighted previously in the FESAC Long-Range Plan (LRP) and the APS Community Planning Process (CPP). There have been many advances in the stellarator field since those reports were drafted, both theoretically and experimentally, that provide an even stronger motivation for an expanded stellarator program within the US. In addition, in recent years a number of private companies have been founded (and funded) to pursue the stellarator concept, two of which are FES Milestone Program award recipients. An expanded stellarator program is needed to fully support these companies and their goals. This whitepaper aims to briefly provide an updated outlook on the need for a national stellator program including benefits to private industry and opportunities for Public Private Partnerships (PPP).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision

Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape cosmic evolution. This whitepaper presents a vision for how Artificial Intelligence (AI) can accelerate discovery in this field. We outline grand challenges that must be addressed to enable transformative breakthroughs and describe how current and planned experimental facilities can implement this vision to advance our understanding of the vast and complex physical world from the smallest to the largest scales. We show how facilities currently under construction, such as the HL-LHC, DUNE and soon EIC, can both benefit from and serve as proving grounds for this vision, while also enabling a longer-term goal for how future experiments -- like FCC-ee at CERN, IceCube-Gen2, a Muon Collider in the U.S., and smaller to mid-scale projects -- can be fully AI-native. We describe how a truly national-scale collaboration, jointly managed across large funding partners, and involving both DOE laboratories and universities, can make this happen.

Aarrestad, Thea Klaeboe [ETH, Zurich (main)]↗
DOE OSTI2025

White Paper: Research & Development for the Time at Temperature Approach

Recent advancements in nuclear power research are greatly improving reactor safety and performance through the development of Accident Tolerant Fuel (ATF) and Low-Enriched Uranium Plus (LEU+). These innovations can address Departure from Nucleate Boiling (DNB) margins, which are vital for reactor safety. DNB happens when the coolant switches to film boiling, significantly decreasing heat transfer and posing a risk of fuel cladding failure. The U.S. Nuclear Regulatory Commission (NRC) employs conservative DNB criteria, which can potentially restrict the operational flexibility and efficiency of reactors. The Time at Temperature (TaT) approach could provide a more detailed and adaptable operational guideline by establishing acceptable time-temperature limits, accounting for the duration a material can withstand elevated temperatures without losing its integrity. This method allows reactors to operate more efficiently and safely, offering additional operational margins, faster power adjustments, and improved fuel cycle economics. TaT criteria allow for higher power levels and more flexible responses to operational transients, particularly applicable for anticipated operational occurrences (AOOs) that result in short durations of post-DNB conditions. It enhances plant operational flexibility, allows faster startup times, and enables quicker power level adjustments, optimizing fuel loading patterns and improving fuel cycle economics. Implementing TaT limits reduces core design constraints, lowers fuel usage, and reduces costs, essential for the long-term sustainability of Light Water Reactors (LWRs). TaT maximizes the use of advanced fuel technologies like ATF and LEU+, further enhancing their economic and environmental benefits. To apply the TaT approach in existing LWRs, collaborative research activities among various DOE-sponsored programs are essential. These efforts should incorporate fuel experiments, physics-based high-fidelity modeling, ML-based surrogate modeling, and optimization techniques. This whitepaper proposes four research and development areas: 1) Investigation of the feasibility of new operations of LWR with updated safety limits; 2) Assessment of reactor operation limits through uncertainty reduction; 3) Evaluation of power uprate in virtual environment; and 4) Lattice and reactor core design for power uprate. Each area includes why this research is in need and a suggested scope of work. These comprehensive research areas ensure practical and beneficial advancements for existing reactors, translating innovations in nuclear fuel and cladding technology into improved reactor performance and safety.

42 - ENGINEERING↗