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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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DOE OSTI2024

Providing a Flexible and Comprehensive Software Stack Via Spack, an Extreme-Scale Scientific Software Stack, and Software Development Kits

To manage the complex demands of modern high-performance computing (HPC), software applications increasingly depend on software developed by other teams, often at other institutions. An HPC software ecosystem approach is required to support dependencies on third-party scientific software. An ecosystem approach provides layers of activity above the individual software product level that promote interoperability, quality improvement, porting, testing, and deployment. The U.S. Exascale Computing Project (ECP) developed its HPC software ecosystem using a three-pronged approach. First, the ECP adopted and invested in Spack, a package manager designed to handle complex HPC package dependencies. Second, the ECP created the Extreme Scale Scientific Software Stack, an effort that supports developing, deploying, and running scientific applications on HPC platforms. Third, the ECP supported software product communities, or software development kits, to develop and promote best practices, improve software interoperability, and other collaborative efforts. This article describes ECP contributions to HPC software ecosystem challenges.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Research Software Engineering: Introducing a New Computing in Science & Engineering Department

Here, this article introduces the new Research Software Engineering (RSEng) department at Computing in Science & Engineering. Through a conversation with the department coeditors, we highlight why RSEng matters, how it differs from industrial software engineering, what it means to be an RSE, and the scholarly and practical questions that lie ahead. Along the way, we draw on emerging literature, case studies, and community perspectives to frame the profession and practice of RSEng within computational science and engineering.

Lamprecht, Anna-Lena [Univ. of Potsdam (Germany)] ↗
DOE OSTI2024

Regulators’ Financial Toolbox: Leveraging Software as a Service, Cloud Computing, and Artificial Intelligence in Electric Utilities

The rapid evolution of Software as a Service (SaaS), cloud computing, and artificial intelligence (AI) is transforming the electric utility industry, reshaping operations, customer engagement, and financial models. This webinar introduced how utilities can deploy advanced software solutions and AI-driven analytics to improve grid efficiency, optimize asset management, and accurately forecast demand.

Bartlett, Phillip↗
DOE OSTI2025

Adaptive Computing (AC) [SWR-24-106]

The Adaptive Computing (AC) software stack supports goal-based computing, for which a simulation workload is created on the fly adapting to the results of calculations. Application-specific code defines an objective, which may be to solve an optimization problem or to train a surrogate model with minimal uncertainty. Then, the AC driver decides where in the design parameter space to run simulations to best achieve that objective. This process is iterative and online; as new data is returned from simulations, the AC driver chooses new simulations to run. The AC driver can strategically run simulations on distributed hardware resources (including high performance computing machines, cloud resources, and edge devices) to maximize throughput and obey resource constraints.

Griffin, Kevin [National Renewable Energy Laborato↗
DOE OSTI2026

Adaptive Computing (AC) (Open Source) [SWR-24-106]

The Adaptive Computing (AC) software stack supports goal-based computing, for which a simulation workload is created on the fly, adapting to the results of calculations. Application-specific code defines an objective, which may be to solve an optimization problem or to train a surrogate model with minimal uncertainty. Then, the AC driver decides where in the design parameter space to run simulations to best achieve that objective. This process is iterative and online; as new data is returned from simulations, the AC driver chooses new simulations to run. The AC driver can strategically run simulations on distributed hardware resources (including high performance computing machines, cloud resources, and edge devices) to maximize throughput and obey resource constraints.

Griffin, Kevin [National Laboratory of the Rockies↗
DOE OSTI2024

Machine learning and TDDFT software for stopping power computation

(SF-24-012) Stopping power describes the rate that a material slows radiation particles passing through it and is useful in designing many technologies. Few organizations can perform new measurements, which require significant resources and rare equipment, and all others rely on coarse approximations rendered from pre-existing data. Methods for computing stopping power in new materials, such as time-dependent density functional theory (TD-DFT), have only recently (circa-2015) become available but are too computationally costly to use frequently enough to have a pronounced impact. We have created a method that opens a pathway to computing stopping power without any need for experimental data by combining electronic structure computations and machine learning.

Ward, Logan↗
DOE OSTI2026

Enhanced climate reproducibility testing with false discovery rate correction

Simulating the Earth's climate is an important and complex problem, thus climate models are similarly complex, comprised of millions of lines of code. In order to appropriately utilize the latest computational and software infrastructure advancements in Earth system models running on modern hybrid computing architectures to improve their performance, precision, accuracy, or all three; it is important to ensure that model simulations are repeatable and robust. This introduces the need for establishing statistical or non-bit-for-bit reproducibility, since bit-for-bit reproducibility may not always be achievable. Here, we propose a short-simulation ensemble-based test for an atmosphere model to evaluate the null hypothesis that modified model results are statistically equivalent to that of the original model. We implement this test in version 2 of the US Department of Energy's Energy Exascale Earth System Model (E3SM). The test evaluates a standard set of output variables across the two simulation ensembles and uses a false discovery rate correction to account for multiple testing. The false positive rates of the test are examined using re-sampling techniques on large simulation ensembles and are found to be lower than the currently implemented bootstrapping-based testing approach in E3SM. We also evaluate the statistical power of the test using perturbed simulation ensemble suites, each with a progressively larger magnitude of change to a tuning parameter. The new test is generally found to exhibit more statistical power than the current approach, being able to detect smaller changes in parameter values with higher confidence.

Kelleher, Michael E. [Oak Ridge National Laborator↗
DOE OSTI2024

Simulations, Modeling and Data Analysis of Parity Violating Electron Scattering Experiments

In the Standard Model (SM) of nuclear and particle physics, parity violation is incorporated through the representation of the weak interaction as a chiral gauge interaction. Only the left-handed components of particles and right-handed components of antiparticles participate in weak interactions in the Standard Model. This implies that parity is asymmetric for the weak interaction. Parity violating electron scattering (PVES) experiments are designed to probe the physics parameters related to the SM, with the possibility to discover physics beyond the SM (BSM) by measuring the parity violating asymmetry ¿¿¿ of longitudinally polarized electrons scattered off unpolarized targets with high precision. This dissertation will be focused on two PVES experiments, the next 208Pb Lead Radius Experiment (PREX-II), and the Measurement of a Lepton-Lepton Electroweak Reaction (MOLLER) experiment, as well as in some small sections, the Calcium Radius Experiment (CREX) and P2 experiment which are also PVES experiments). PREX-II and CREX experiments, performed in Hall A at the Thomas Jefferson National Accelerator Facility (Jefferson Lab), measured ¿¿¿ in the elastic scattering of longitudinally polarized electrons from 208Pb and 48Ca targets to provide a precise model independent determination of the neutron skin thickness of 208Pb and 48Ca nuclei, respectively. The MOLLER experiment, proposed to start in 2027 and also to be performed in Hall A at Jefferson Lab, is to measure ¿¿¿ of longitudinally polarized electrons scattered off unpolarized electrons (Møller scattering) to determine the weak charge of electrons ¿¿¿ and the weak mixing angle ¿¿ with high precision. As for the P2 experiment, which will be performed at the upcoming MESA accelerator in Mainz Germany, it is to measure the weak charge of proton ¿¿¿ using ¿¿¿ in the elastic electron-proton scattering of polarized electrons off unpolarized protons. The final results from the PREX-II experiment are presented as ¿¿¿=550±16 (¿¿¿¿)±8 (¿¿¿¿) parts-per-billion (ppb). Combining the PREX-I and PREX-II results, the neutron skin thickness from PREX experiments is determined as ¿¿-¿¿=0.283±0.071 ¿¿ in 208Pb. This thesis lists the software and computational contribution of the author to these PVES experiments, including writing scripts and software to help with the PREX-II/CREX experiments, analyzing data to provide useful information and systematic uncertainty for the PREX-II experiment, modeling and simulations for the MOLLER, and providing an alternative design of an electronic equipment for the P2 experiment.

Chen, Yufan↗
DOE OSTI2024

Simulations, Modeling and Data Analysis of Parity Violating Electron Scattering Experiments

In the Standard Model (SM) of nuclear and particle physics, parity violation is incorporated through the representation of the weak interaction as a chiral gauge interaction. Only the left-handed components of particles and right-handed components of antiparticles participate in weak interactions in the Standard Model. This implies that parity is asymmetric for the weak interaction. Parity violating electron scattering (PVES) experiments are designed to probe the physics parameters related to the SM, with the possibility to discover physics beyond the SM (BSM) by measuring the parity violating asymmetry ¿¿¿ of longitudinally polarized electrons scattered off unpolarized targets with high precision. This dissertation will be focused on two PVES experiments, the next 208Pb Lead Radius Experiment (PREX-II), and the Measurement of a Lepton-Lepton Electroweak Reaction (MOLLER) experiment, as well as in some small sections, the Calcium Radius Experiment (CREX) and P2 experiment which are also PVES experiments). PREX-II and CREX experiments, performed in Hall A at the Thomas Jefferson National Accelerator Facility (Jefferson Lab), measured ¿¿¿ in the elastic scattering of longitudinally polarized electrons from 208Pb and 48Ca targets to provide a precise model independent determination of the neutron skin thickness of 208Pb and 48Ca nuclei, respectively. The MOLLER experiment, proposed to start in 2027 and also to be performed in Hall A at Jefferson Lab, is to measure ¿¿¿ of longitudinally polarized electrons scattered off unpolarized electrons (Møller scattering) to determine the weak charge of electrons ¿¿¿ and the weak mixing angle ¿¿ with high precision. As for the P2 experiment, which will be performed at the upcoming MESA accelerator in Mainz Germany, it is to measure the weak charge of proton ¿¿¿ using ¿¿¿ in the elastic electron-proton scattering of polarized electrons off unpolarized protons. The final results from the PREX-II experiment are presented as ¿¿¿=550±16 (¿¿¿¿)±8 (¿¿¿¿) parts-per-billion (ppb). Combining the PREX-I and PREX-II results, the neutron skin thickness from PREX experiments is determined as ¿¿-¿¿=0.283±0.071 ¿¿ in 208Pb. This thesis lists the software and computational contribution of the author to these PVES experiments, including writing scripts and software to help with the PREX-II/CREX experiments, analyzing data to provide useful information and systematic uncertainty for the PREX-II experiment, modeling and simulations for the MOLLER, and providing an alternative design of an electronic equipment for the P2 experiment.

Chen, Yufan↗
DOE OSTI2025

Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions

We discuss the challenges and propose research directions for using AI to revolutionize the development of high-performance computing (HPC) software. AI technologies, in particular large language models, have transformed every aspect of software development. For its part, HPC software is recognized as a highly specialized scientific field of its own. We discuss the challenges associated with leveraging state-of-the-art AI technologies to develop such a unique and niche class of software and outline our research directions in the two US Department of Energy–funded projects for advancing HPC Software via AI: Ellora and Durban.

Teranishi, Keita [ORNL] (ORCID:0000000166472690)↗
DOE OSTI2024

HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware

In order to characterize and benchmark computational hardware, software, and algorithms, it is essential to have many problem instances on-hand. This is no less true for quantum computation, where a large collection of real-world problem instances would allow for benchmarking studies that in turn help to improve both algorithms and hardware designs. To this end, here we present a large dataset of qubit-based quantum Hamiltonians. The dataset, called HamLib (for Hamiltonian Library), is freely available online and contains problem sizes ranging from 2 to 1000 qubits. HamLib includes problem instances of the Heisenberg model, Fermi-Hubbard model, Bose-Hubbard model, molecular electronic structure, molecular vibrational structure, MaxCut, Max- k -SAT, Max- k -Cut, QMaxCut, and the traveling salesperson problem. The goals of this effort are (a) to save researchers time by eliminating the need to prepare problem instances and map them to qubit representations, (b) to allow for more thorough tests of new algorithms and hardware, and (c) to allow for reproducibility and standardization across research studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Flexible Pilot Jobs Framework for Distributed High Throughput Computing

Experimental particle physics has been at the forefront of analyzing the world’s largest datasets for decades. The high-energy physics (HEP) community was among the first to develop suitable software and computing tools for this purpose. GlideinWMS is a Glidein-based workload management system whose purpose is to provide experiments like CMS at CERN, DUNE at Fermilab, and others, a way to access and efficiently use vast amounts of computing resources. This system wants to provide a simple way to submit jobs to a set of computing resources, that will be provided to users behind the scenes. Glideins are the pilot jobs executed on the worker nodes at the grid sites, performing operations such as hardware detection, environment setup, and error handling. After all these operations, they will launch the actual user job. Many grid sites are supported, such as shared clusters, Google CE, and AWS. My internship aimed to design and code a flexible pilot jobs framework that will replace the one used by GlideinWMS, developing a modular and flexible skeleton of the Glidein and adding further functionalities. My project also focused on the application of machine learning techniques as support to this management system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

NWChem

NWChem is a computational chemistry software package which includes quantum chemical and molecular dynamics functionality. It aims to be scalable both in its ability to treat large problems efficiently, and in its usage of available parallel computing resources.

Apra, Edoardo [Pacific Northwest National Laborato↗
DOE OSTI2024

Roadmap on methods and software for electronic structure based simulations in chemistry and materials

This Roadmap article provides a succinct, comprehensive overview of the state of electronic structure methods and software for molecular and materials simulations. Seventeen distinct sections collect insights by 51 leading scientists in the field. Each contribution addresses the status of a particular area, as well as current challenges and anticipated future advances, with a particular eye towards software related aspects and providing key references for further reading. Foundational sections cover density functional theory and its implementation in real-world simulation frameworks, Green's function based many-body perturbation theory, wave-function based and stochastic electronic structure approaches, relativistic effects and semiempirical electronic structure theory approaches. Subsequent sections cover nuclear quantum effects, real-time propagation of the electronic structure, challenges for computational spectroscopy simulations, and exploration of complex potential energy surfaces. The final sections summarize practical aspects, including computational workflows for complex simulation tasks, the impact of current and future high-performance computing architectures, software engineering practices, education and training to maintain and broaden the community, as well as the status of and needs for electronic structure based modeling from the vantage point of industry environments. Overall, the field of electronic structure software and method development continues to unlock immense opportunities for future scientific discovery, based on the growing ability of computations to reveal complex phenomena, processes and properties that are determined by the make-up of matter at the atomic scale, with high precision.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Accelerated data-driven materials science with the Materials Project

The Materials Project was launched formally in 2011 to drive materials discovery forwards through high-throughput computation and open data. More than a decade later, the Materials Project has become an indispensable tool used by more than 600,000 materials researchers around the world. This Perspective describes how the Materials Project, as a data platform and a software ecosystem, has helped to shape research in data-driven materials science. We cover how sustainable software and computational methods have accelerated materials design while becoming more open source and collaborative in nature. Next, we present cases where the Materials Project was used to understand and discover functional materials. We then describe our efforts to meet the needs of an expanding user base, through technical infrastructure updates ranging from data architecture and cloud resources to interactive web applications. Finally, we discuss opportunities to better aid the research community, with the vision that more accessible and easy-to-understand materials data will result in democratized materials knowledge and an increasingly collaborative community.

Horton, Matthew K↗
DOE OSTI2024

Computing within the 2021 Snowmass process

We present different elements of the 2021–2022 Computational Frontier (CompF) effort within the Snowmass process, including organization, events, and highlights of the final report. With focus in the next 10–15 years, we analyze the impact of newly established and emerging technologies, identify challenges within theoretical, experimental and observational research programs, and present the report recommendations. We emphasize the main recommendation, which is the formation of a Coordinating Panel for Software and Computing (CPSC).

97 MATHEMATICS AND COMPUTING↗