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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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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Transforming Energy Through Computational Excellence: Bringing Low Mach Number Reactive Flow Simulations at the Exascale

PeleLMeX's unique capabilities are allowing for reactive flow modeling at unprecedented scales and a reasonable time and cost. The code is currently being extended to tackle more practical, design-oriented simulations by implementing Large Eddy Simulation and data-driven chemical models, providing a fast but accurate tool for engineers considering the emergence of GPU-accelerated platforms. These extensions are critical for enabling the physical insight required to design the next generation of combustion devices as a key component of a renewable energy future.

MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A fast quantum route to random numbers

Here, using a quantum computer to speed up one step in a textbook approach to generating random numbers proves to be a savvy strategy, and one that could make good use of quantum computers that will be available in the near future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Scientific Computing Strategic Plan for the Idaho National Laboratory

Scientific computing is a critical foundation of modern science. Without innovations in the field of computational science, the essential missions of the Department of Energy (DOE) would go unrealized. Taking a leadership role in such innovations is Idaho National Laboratory’s (INL’s) challenge and charge, and is central to INL’s ongoing success. Computing is an essential part of INL’s future. DOE science and technology missions rely firmly on computing capabilities in various forms. Modeling and simulation, fueled by innovations in computational science and validated through experiment, are a critical foundation of science and engineering. Big data analytics from an increasing number of widely varied sources is opening new windows of insight and discovery. Computing is a critical tool in education, science, engineering, and experiments. Advanced computing capabilities in the form of people, tools, computers, and facilities, will position INL competitively to deliver results and solutions on important national science and engineering challenges. A computing strategy must include much more than simply computers. The foundational enabling component of computing at many DOE national laboratories is the combination of a showcase like data center facility coupled with a very capable supercomputer. In addition, network connectivity, disk storage systems, and visualization hardware are critical and generally tightly coupled to the computer system and co located in the same facility. The existence of these resources in a single data center facility opens the doors to many opportunities that would not otherwise be possible.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Superconductor/Ferromagnet Heterostructures: A Platform for Superconducting Spintronics and Quantum Computation

The interplay between superconductivity and ferromagnetism in the superconductor/ferromagnet (SC/FM) heterostructures generates many interesting physical phenomena, including spin-triplet superconductivity, superconducting order parameter oscillation, and topological superconductivity. The unique physical properties make the SC/FM heterostructure as promising platforms for future superconducting spintronics and quantum computation applications. In this article, important research progress of SC/FM heterostructures from superconducting spintronics to quantum computation is reviewed, and it is organized as follows. First, the progress of spin current carriers in SC/FM heterostructures including Bogoliubov quasiparticles, superconducting vortex, and spin-triplet Cooper pairs which might be used for long-range spin transport is discussed. Then, the π Josephson junctions and their application for constructing π qubits are described. Finally, experimental signatures of Majorana states in the SC/FM heterostructures and the theoretically proposed manipulation are briefly reviewed, which could be useful to realize fault-tolerant topological quantum computing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Data Storage for HEP Experiments in the Era of High-Performance Computing

As particle physics experiments push their limits on both the energy and the intensity frontiers, the amount and complexity of the produced data are also expected to increase accordingly. With such large data volumes, next-generation efforts like the HL-LHC and DUNE will rely even more on both high-throughput (HTC) and high-performance (HPC) computing clusters. Full utilization of HPC resources requires scalable and efficient data-handling and I/O. For the last few decades, ROOT has been used by most HEP experiments to store data. However, other storage technologies like HDF5 may perform better in HPC environments. Initial explorations with HDF5 have begun using ATLAS, CMS and DUNE data; the DUNE experiment has also adopted HDF5 for its data-acquisition system. This paper presents the future outlook of the HEP computing and the role of HPC, and a summary of ongoing and future works to use HDF5 as a possible data storage technology for the HEP experiments to use in HPC environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Design methodologies and engineering applications for ecosystem biomimicry: an interdisciplinary review spanning cyber, physical, and cyber-physical systems

Abstract Ecosystem biomimicry is a promising pathway for sustainable development. However, while typical form- and process-level biomimicry is prevalent, system-level ecosystem biomimicry remains a nascent practice in numerous engineering fields. This critical review takes an interdisciplinary approach to synthesize trends across case studies, evaluate design methodologies, and identify future opportunities when applying ecosystem biomimicry to engineering practices, including cyber systems (CS), physical systems (PS), and cyber-physical systems (CPS). After systematically sourcing publications from major databases, the papers were first analyzed at a meta level for their bibliographic context and for statistical correlations among categorical variables. Then, we investigated deeper into the engineering applications and design methodologies. Results indicate that CPS most frequently mimic organisms and ecosystems, while CS and PS frequently mimic populations-communities and molecules-tissues-organ systems, respectively (statistically highly significant). An indirect approach is most often used for mimicry at organizational levels from populations to ecosystems, while a direct approach frequently suits levels from molecules to organisms (highly significant). Dominant themes across engineering applications include symbiotic organism search algorithms for CS and ecological network analysis for CPS, while PS are highly diverse. For design methodologies, this work summarizes and details ten well-documented biomimetic process models among literature, which addresses an outdated concern for a lack of systematic methods for ecosystem biomimicry. In addition to the Biomimetics Standard ISO 18458, these methods include the Natural Step and Techno-Ecological Synergy framework, among others. Further, the analyses revealed future opportunities from less utilized design methods (e.g. interdisciplinary teams tackling indirect, ecosystem-level projects) to well-established engineering concepts ready for technological advancement (e.g. implementing membrane computing for physical applications). For future studies, this review provides a comprehensive reference for ecosystem biomimetic design practices and application opportunities across multiple engineering domains.

42 ENGINEERING↗
DOE OSTI2025

Bridging paradigms: Designing for HPC-Quantum convergence

Here, this paper presents a comprehensive software stack architecture for integrating quantum computing (QC) capabilities with High-Performance Computing (HPC) environments. While quantum computers show promise as specialized accelerators for scientific computing, their effective integration with classical HPC systems presents significant technical challenges. We propose a hardware-agnostic software framework that supports both current noisy intermediate-scale quantum devices and future fault-tolerant quantum computers, while maintaining compatibility with existing HPC workflows. The architecture includes a quantum gateway interface, standardized APIs for resource management, and robust scheduling mechanisms to handle both simultaneous and interleaved quantum–classical workloads. Key innovations include: (1) a unified resource management system that efficiently coordinates quantum and classical resources, (2) a flexible quantum programming interface that abstracts hardware-specific details, (3) A Quantum Platform Manager API that simplifies the integration of various quantum hardware systems, and (4) a comprehensive tool chain for quantum circuit optimization and execution. We demonstrate our architecture through implementation of quantum–classical algorithms, including the variational quantum linear solver, showcasing the framework’s ability to handle complex hybrid workflows while maximizing resource utilization. This work provides a foundational blueprint for integrating QC capabilities into existing HPC infrastructures, addressing critical challenges in resource management, job scheduling, and efficient data movement between classical and quantum resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection

The US Western Interconnection is facing unprecedented challenges in the form of less predictable peak demand, increasingly diverse generating resources, and fast-growing loads due to the onset of artificial intelligence, hyperscale computing, and electrification. Projecting where future generation may be developed is critical to maintaining a robust and resilient electric grid under this mounting uncertainty and variability. Using an integrated multisectoral, multiscale modeling framework that links a human-Earth systems model, an hourly load model, a geospatial power plant siting model, and an hourly grid operations model, we evaluate the power plant landscape evolution under eight alternative futures between 2020 and 2055. These futures represent a wide but plausible range of atmospheric conditions, emissions constraints, and economic, technological, and population growth assumptions. We find that local-level development can vary substantially both by generation type and capacity buildout across these futures. Specific regions of the Western Interconnection are projected to see large amounts of capacity development regardless of the future scenario. We additionally determine that projected power plant locations are more heavily influenced by the cost to interconnect to the electric grid than the locational energy value.

Mongird, Kendall↗
DOE OSTI2025

Computational tools and data integration to accelerate vaccine development: challenges, opportunities, and future directions

The development of effective vaccines is crucial for combating current and emerging pathogens. Despite significant advances in the field of vaccine development there remain numerous challenges including the lack of standardized data reporting and curation practices, making it difficult to determine correlates of protection from experimental and clinical studies. Significant gaps in data and knowledge integration can hinder vaccine development which relies on a comprehensive understanding of the interplay between pathogens and the host immune system. In this review, we explore the current landscape of vaccine development, highlighting the computational challenges, limitations, and opportunities associated with integrating diverse data types for leveraging artificial intelligence (AI) and machine learning (ML) techniques in vaccine design. We discuss the role of natural language processing, semantic integration, and causal inference in extracting valuable insights from published literature and unstructured data sources, as well as the computational modeling of immune responses. Furthermore, we highlight specific challenges associated with uncertainty quantification in vaccine development and emphasize the importance of establishing standardized data formats and ontologies to facilitate the integration and analysis of heterogeneous data. Through data harmonization and integration, the development of safe and effective vaccines can be accelerated to improve public health outcomes. Looking to the future, we highlight the need for collaborative efforts among researchers, data scientists, and public health experts to realize the full potential of AI-assisted vaccine design and streamline the vaccine development process.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Integration of the Nek5000 Computational Fluid Dynamics Code with the NEAMS Workbench

The mission of the US Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program is to develop, apply, deploy, and support state-of-the-art predictive modeling and simulation tools for the design and analysis of current and future nuclear energy systems using computing architectures ranging from laptops to leadership-class facilities. NEAMS is organized into three product lines: the Fuels Product Line (FPL),the Reactors Product Line (RPL), and the Integration Product Line (IPL). The FPL and RPL focus on the development of high-fidelity tools such as the MOOSE-based applications BISON and MARMOT [3, 9] at Idaho National Laboratory, and the PROTEUS neutronics code and the NEK5000 computational fluid dynamics code from the Simulation-based High-efficiency Advanced Reactor Prototyping (SHARP) framework [10]. The NEAMS IPL will enable users to apply high-fidelity simulations to inform lower order models for the design, analysis, and licensing of advanced nuclear systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Data-Driven Unit Commitment Refinement - a Scalable Approach for Complex Modern Power Grids

Integration of renewable generation, which is often intermittent and decentralized, substantially increases the stochasticity and complexity of power grid operations. Future power systems planning will require significant computational capability to evaluate balance between demand and supply under varying conditions, both temporally and spatially. The standard approach for generation unit commitment is to use mixed-integer linear programming to find the optimal generation schedule considering ramping and generator constraints. In the future grid this poses computational scalability challenges because generation and demand are not known with certainty due to stochasticity in weather and complexity of the grid. To address this challenge, we present a data-driven unit commitment approach that can efficiently include stochastic weather impacts and contingency considerations to improve unit commitment. Our approach uses graph-based data analytics techniques on solutions to the security constrained (and possibly stochastic) economic dispatch problem to identify potential improvements to a given unit commitment. Recent breakthroughs in fully-parallel stochastic economic dispatch software allow this approach to be scalably deployed. Simulations on synthetic South Carolina and Texas grids show this method can improve grid reliability with security constraints over a set of contingencies, while also meaningfully lowering total generation cost.

Holt, Timothy↗
DOE OSTI2012

Pathway Controlled Penetration (PcP) [Slides]

The technical approach employs advanced computational simulation tools to demonstrate how current assets can destroy RWK-RFI-12-0001's HDBT, a tunnel complex with two portals built into the base of a granite mountain. The granite over layer is assumed to be 60 meters thick over both portals and 80 meters over the facility's mission space. Key S&T is the completed development of a highly innovative viscoplastic fracture material model, 3D parallel gas-fracture capabilities into FDEM, and a stochastic handling of the material properties. Phase I - Develop and validate code simulation tools: (1) develop, incorporate and validate AZ-Frac material model for granite; and (2) Develop and incorporate gas-driven-fracture modeling into LANL's FDEM MUNROU code; (3) Develop and incorporate stochastic features into FDEM modeling. Phase II - Conduct PcP analysis on above HDBT: (1) Acquire HDBT design data, develop simulation model; and (2) Evaluate and select most promising defeat alternative. Phase III - Deliver code, train Service target analysts, and conduct simulations against real world HDBTs. PcP uses advanced computer simulations to enhance HDBT functional defeat efforts. Newly developed material models that account for fractural energy coupled with the finite discrete element methodology (FDEM) will provide targeting packages that will create penetration avenues for current or future lethality options. This novel computational approach requires full 3D geologic and structure characterization as well as significant high performance computing capabilities. The goal is to distinctively alter the targeting paradigm by leveraging critical DoD assets along with insitu geologic strata. In other words, assets will utilize underground rock structure to their benefit by creating rubbilization zones that will allow pathway controlled penetration.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Benchmark for two-dimensional large scale coherent structures in partially magnetized E × B plasmas—community collaboration & lessons learned

Low-temperature plasmas (LTPs) are essential to both fundamental scientific research and critical industrial applications. As in many areas of science, numerical simulations have become a vital tool for uncovering new physical phenomena and guiding technological development. Code benchmarking remains crucial for verifying implementations and evaluating performance. This work continues the Landmark benchmark initiative, a series specifically designed to support the verification of LTP codes. In this study, seventeen simulation codes from a collaborative community of nineteen international institutions modeled a partially magnetized E × B Penning discharge. The emergence of large scale coherent structures, or rotating plasma spokes, endows this configuration with an enormous range of time scales, making it particularly challenging to simulate. The codes showed excellent agreement on the rotation frequency of the spoke as well as key plasma properties, including time-averaged ion density, plasma potential, and electron temperature profiles. Achieving this level of agreement came with challenges, and we share lessons learned on how to conduct future benchmarking campaigns. Comparing code implementations, computational hardware, and simulation runtimes also revealed interesting trends, which are summarized with the aim of guiding future plasma simulation software development.

benchmarking↗
DOE OSTI2025

Computational Modeling to Advance Novel Medical Isotopes for Radiotheranostics: A DOE-NIH Joint Workshop Executive Summary

The DOE-NIH Joint Workshop on Computational Modeling to Advance Novel Medical Isotopes for Radiotheranostics, held on September 27, 2024, brought together experts from government, academia, and industry to address critical challenges in radionuclide production and clinical translation. Here, the workshop emphasized interdisciplinary collaboration, particularly between the Department of Energy (DOE) and the National Institutes of Health (NIH), to strengthen the domestic isotope supply, streamline regulatory pathways, and further integrate computational tools into radiopharmaceutical therapy (RPT). Key discussions explored the role of AI-driven modeling, machine learning, and digital twin technologies in optimizing dosimetry, dynamically personalizing treatments, and reducing time to clinical adoption. Advances in predictive computational modeling were highlighted as essential for improving radionuclide yield, purity, and synthesis efficiency. Regulatory considerations and equitable access were central themes, with participants advocating for harmonized global standards, adaptive trial designs, and expanded infrastructure for clinical implementation. DOE computational and production infrastructure was emphasized. Future priorities identified include increased investment in radionuclide production infrastructure, expanded workforce development in radiopharmaceutical sciences and computational modeling, and the creation of robust public-private partnerships. The workshop concluded that continued strategic collaboration and sustained resources will be vital for advancing next-generation radiotheranostics, ensuring safe and effective therapies accessible to all patients.

digital twins↗
DOE OSTI2016

WHITE DWARF MERGERS ON ADAPTIVE MESHES. I. METHODOLOGY AND CODE VERIFICATION

The Type Ia supernova (SN Ia) progenitor problem is one of the most perplexing and exciting problems in astrophysics, requiring detailed numerical modeling to complement observations of these explosions. One possible progenitor that has merited recent theoretical attention is the white dwarf (WD) merger scenario, which has the potential to naturally explain many of the observed characteristics of SNe Ia. To date there have been relatively few self-consistent simulations of merging WD systems using mesh-based hydrodynamics. This is the first paper in a series describing simulations of these systems using a hydrodynamics code with adaptive mesh refinement. In this paper we describe our numerical methodology and discuss our implementation in the compressible hydrodynamics code CASTRO, which solves the Euler equations, and the Poisson equation for self-gravity, and couples the gravitational and rotation forces to the hydrodynamics. Standard techniques for coupling gravitation and rotation forces to the hydrodynamics do not adequately conserve the total energy of the system for our problem, but recent advances in the literature allow progress and we discuss our implementation here. We present a set of test problems demonstrating the extent to which our software sufficiently models a system where large amounts of mass are advected on the computational domain over long timescales. Future papers in this series will describe our treatment of the initial conditions of these systems and will examine the early phases of the merger to determine its viability for triggering a thermonuclear detonation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

An S N Algorithm for Modern Architectures

LANL discrete ordinates transport packages are required to perform large, computationally intensive time-dependent calculations on massively parallel architectures, where even a single such calculation may need many months to complete. While KBA methods scale out well to very large numbers of compute nodes, we are limited by practical constraints on the number of such nodes we can actually apply to any given calculation. Instead, we describe a modified KBA algorithm that allows realization of the reductions in solution time offered by both the current, and future, architectural changes within a compute node.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Data Movement Dominates: Advanced Memory Technology to Address the Real Exascale Power Problem

Energy is the fundamental barrier to Exascale supercomputing and is dominated by the cost of moving data from one point to another, not computation. Similarly, performance is dominated by data movement, not computation. The solution to this problem requires three critical technologies: 3D integration, optical chip-to-chip communication, and a new communication model. The central goal of the Sandia led "Data Movement Dominates" project aimed to develop memory systems and new architectures based on these technologies that have the potential to lower the cost of local memory accesses by orders of magnitude and provide substantially more bandwidth. Only through these transformational advances can future systems reach the goals of Exascale computing with a manageable power budgets. The Sandia led team included co-PIs from Columbia University, Lawrence Berkeley Lab, and the University of Maryland. The Columbia effort of Data Movement Dominates focused on developing a physically accurate simulation environment and experimental verification for optically-connected memory (OCM) systems that can enable continued performance scaling through high-bandwidth capacity, energy-efficient bit-rate transparency, and time-of-flight latency. With OCM, memory device parallelism and total capacity can scale to match future high-performance computing requirements without sacrificing data-movement efficiency. When we consider systems with integrated photonics, links to memory can be seamlessly integrated with the interconnection network-in a sense, memory becomes a primary aspect of the interconnection network. At the core of the Columbia effort, toward expanding our understanding of OCM enabled computing we have created an integrated modeling and simulation environment that uniquely integrates the physical behavior of the optical layer. The PhoenxSim suite of design and software tools developed under this effort has enabled the co-design of and performance evaluation photonics-enabled OCM architectures on Exascale computing systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Efficient use of quantum computers for collider physics

Most observables at particle colliders involve physics at a wide variety of distance scales. Due to asymptotic freedom of the strong interaction, the physics at short distances can be calculated reliably using perturbative techniques, while long distance physics is non-perturbative in nature. Factorization theorems separate the contributions from different scales, allowing to identify the pieces that can be determined perturbatively from those that require non-perturbative information, and if the non-perturbative pieces can be reliably determined, one can use experimental measurements to extract the short distance effects, sensitive to possible new physics. Without the ability to compute the non-perturbative ingredients from first principles one typically identifies observables for which the non-perturbative information is universal in the sense that it can be extracted from some experimental observables and then used to predict other observables. In this paper we argue that the future ability to use quantum computers to calculate non-perturbative matrix elements from first principles will allow to make predictions for observables with non-universal non-perturbative long-distance physics.

Algorithms and Theoretical Developments↗