When Computers Come First
Ruth Pordes was at Fermilab when computing equipment was first being moved into the laboratory offices. The elevated status of computers at the laboratory was made evident on move-in day.
97 MATHEMATICS AND COMPUTING↗
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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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Scientific Grand Challenges: Crosscutting Technologies for Computing at the Exascale - February 2-4, 2010, Washington, D.C.
The goal of the "Scientific Grand Challenges - Crosscutting Technologies for Computing at the Exascale" workshop in February 2010, jointly sponsored by the U.S. Department of Energy’s Office of Advanced Scientific Computing Research and the National Nuclear Security Administration, was to identify the elements of a research and development agenda that will address these challenges and create a comprehensive exascale computing environment. This exascale computing environment will enable the science applications identified in the eight previously held Scientific Grand Challenges Workshop Series.
computational science↗
How the Geothermal Community Upped the Game for Computer Codes
The Geothermal Technologies Office Code Comparison Study brought 11 research institutions together to collaborate on coupled thermal, hydrologic, geomechanical, and geochemical numerical simulators. These codes have the potential to help facilitate widespread geothermal energy development.
15 GEOTHERMAL ENERGY↗
Quantum Computing for Biomedical Computational and Data Sciences: A Joint DOE-NIH Roundtable
The overlap of quantum computing and biomedical research, while less explored, presents significant near-term opportunities. The Department of Energy (DOE) and the National Institutes of Health (NIH) are interested in exploiting the DOE community’s capabilities and expertise in quantum computing to potentially advance biomedical research, targeting fundamental studies of biological and molecular structures, understanding of human health as well as mental and physical disorders and diseases, and deriving insights from clinical data. NIH’s approach to quantum computing is guided by its Strategic Plan for Data Science, emphasizing the importance of findable, accessible, interoperable, and reusable (FAIR) data assets, security and privacy of data, and efficient computing and storage. DOE’s Office of Science (SC), and more specifically the Advanced Scientific Computing Research (ASCR) program, supports quantum information science (QIS) research, contributing to a unique portfolio of quantum computing and communications expertise. This roundtable was assembled to consider the opportunities and challenges in the near-, medium-, and long-term at the intersection of quantum computing, data science, and biomedical research and how these could be addressed through inter-agency collaboration and multi-disciplinary partnerships.
59 BASIC BIOLOGICAL SCIENCES↗
Molecular Level Understanding of the Free Energy Landscape in Early Stages of Metal-Organic Framework Nucleation
The assembly mechanism of hierarchical materials controlled by the choice of solvent and presence of spectator ions. In this paper, we use enhanced sampling molecular dynamics methods to investigate these effects on the configurational landscape of metal-linker interactions in the early stages of synthesis, using MIL-101(Cr) as a prototypical example. Microsecond-long well-tempered metadynamics (WTmetaD) uncover a complex free energy structural landscape, with distinct crystal (C) and non-crystal (NC) like configurations and their equilibrium population. In presence of ions (Na+, F-), we observe a complex effect on the crystallinity of secondary building units (SBUs), by encouraging/suppressing salt bridges between C configurations and consequently controlling the percentage of defects. Solvent effects are assessed by introducing N, N-dimethylformamide (DMF) instead of water, where SBU adducts are appreciably more stable and compact. These results shed light on how solvent nature and ionic strength impact the free energy of nucleation phenomena that ultimately control materials synthesis and defect formation. The work described in this publication was supported by the US Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences and performed at Pacific Northwest National Laboratory (PNNL). The authors acknowledge the use of the UCL Legion High Performance Computing Facility (Legion @ UCL) and associated support services in the completion of this work. This research used resources of the National Energy Research Scientific Computing Centre, a DOE Office of Science User Facility. Battelle operates PNNL for DOE under Contract DE-AC05-76RL01830.
Kollias, Loukas↗
Computational Requirements in Clean Energy and Manufacturing: Summary report of the virtual workshop held on June 28-29, 2021
On June 28–29, 2021, the US Department of Energy’s (DOE’s) Advanced Scientific Computing Research (ASCR) program in the Office of Science convened a workshop with the Energy Efficiency and Renew able Energy (EERE) program offices to assess the future need for advanced computing resources in the areas of clean energy and advanced manufacturing. In part, this discussion served as an update to earlier workshops and townhalls. ASCR is guided by DOE mission needs as it develops research programs, computers, and networks at the leading edge of technologies. As the exascale computing era dawns, technology changes are creating new opportunities for those who must use high-performance computing (HPC) and data systems effectively. The ASCR computing facilities are augmenting their strategy to adapt to changing science needs and emerging technologies and to leverage the utility of exascale computing across the federal government.
97 MATHEMATICS AND COMPUTING↗
Computational Materials Science and Chemistry: Accelerating Discovery and Innovation through Simulation-Based Engineering and Science
This report is based on a SC Workshop on Computational Materials Science and Chemistry for Innovation on July 26-27, 2010, to assess the potential of state-of-the-art computer simulations to accelerate understanding and discovery in materials science and chemistry, with a focus on potential impacts in energy technologies and innovation. The urgent demand for new energy technologies has greatly exceeded the capabilities of today's materials and chemical processes. To convert sunlight to fuel, efficiently store energy, or enable a new generation of energy production and utilization technologies requires the development of new materials and processes of unprecedented functionality and performance. New materials and processes are critical pacing elements for progress in advanced energy systems and virtually all industrial technologies. Over the past two decades, the United States has developed and deployed the world's most powerful collection of tools for the synthesis, processing, characterization, and simulation and modeling of materials and chemical systems at the nanoscale, dimensions of a few atoms to a few hundred atoms across. These tools, which include world-leading x-ray and neutron sources, nanoscale science facilities, and high-performance computers, provide an unprecedented view of the atomic-scale structure and dynamics of materials and the molecular-scale basis of chemical processes. For the first time in history, we are able to synthesize, characterize, and model materials and chemical behavior at the length scale where this behavior is controlled. This ability is transformational for the discovery process and, as a result, confers a significant competitive advantage. Perhaps the most spectacular increase in capability has been demonstrated in high performance computing. Over the past decade, computational power has increased by a factor of a million due to advances in hardware and software. This rate of improvement, which shows no sign of abating, has enabled the development of computer simulations and models of unprecedented fidelity. We are at the threshold of a new era where the integrated synthesis, characterization, and modeling of complex materials and chemical processes will transform our ability to understand and design new materials and chemistries with predictive power. In turn, this predictive capability will transform technological innovation by accelerating the development and deployment of new materials and processes in products and manufacturing. Harnessing the potential of computational science and engineering for the discovery and development of materials and chemical processes is essential to maintaining leadership in these foundational fields that underpin energy technologies and industrial competitiveness. Capitalizing on the opportunities presented by simulation-based engineering and science in materials and chemistry will require an integration of experimental capabilities with theoretical and computational modeling; the development of a robust and sustainable infrastructure to support the development and deployment of advanced computational models; and the assembly of a community of scientists and engineers to implement this integration and infrastructure. This community must extend to industry, where incorporating predictive materials science and chemistry into design tools can accelerate the product development cycle and drive economic competitiveness. The confluence of new theories, new materials synthesis capabilities, and new computer platforms has created an unprecedented opportunity to implement a "materials-by-design" paradigm with wide-ranging benefits in technological innovation and scientific discovery. The Workshop on Computational Materials Science and Chemistry for Innovation was convened in Bethesda, Maryland, on July 26-27, 2010. Sponsored by the Department of Energy (DOE) Offices of Advanced Scientific Computing Research and Basic Energy Sciences, the workshop brought together 160 experts in materials science, chemistry, and computational science representing more than 65 universities, laboratories, and industries, and four agencies. The workshop examined seven foundational challenge areas in materials science and chemistry: materials for extreme conditions, self-assembly, light harvesting, chemical reactions, designer fluids, thin films and interfaces, and electronic structure. Each of these challenge areas is critical to the development of advanced energy systems, and each can be accelerated by the integrated application of predictive capability with theory and experiment. The workshop concluded that emerging capabilities in predictive modeling and simulation have the potential to revolutionize the development of new materials and chemical processes. Coupled with world-leading materials characterization and nanoscale science facilities, this predictive capability provides the foundation for an innovation ecosystem that can accelerate the discovery, development, and deployment of new technologies, including advanced energy systems. Delivering on the promise of this innovation ecosystem requires the following: Integration of synthesis, processing, characterization, theory, and simulation and modeling. Many of the newly established Energy Frontier Research Centers and Energy Hubs are exploiting this integration. Achieving/strengthening predictive capability in foundational challenge areas. Predictive capability in the seven foundational challenge areas described in this report is critical to the development of advanced energy technologies. Developing validated computational approaches that span vast differences in time and length scales. This fundamental computational challenge crosscuts all of the foundational challenge areas. Similarly challenging is coupling of analytical data from multiple instruments and techniques that are required to link these length and time scales. Experimental validation and quantification of uncertainty in simulation and modeling. Uncertainty quantification becomes increasingly challenging as simulations become more complex. Robust and sustainable computational infrastructure, including software and applications. For modeling and simulation, software equals infrastructure. To validate the computational tools, software is critical infrastructure that effectively translates huge arrays of experimental data into useful scientific understanding. An integrated approach for managing this infrastructure is essential. Efficient transfer and incorporation of simulation-based engineering and science in industry. Strategies for bridging the gap between research and industrial applications and for widespread industry adoption of integrated computational materials engineering are needed.
36 MATERIALS SCIENCE↗
Final Report: Performance Engineering Research Institute
This document is a final report about the work performed for cooperative agreement DE-FC02-06ER25764, the Rice University effort of Performance Engineering Research Institute (PERI). PERI was an Enabling Technologies Institute of the Scientific Discovery through Advanced Computing (SciDAC-2) program supported by the Department of Energy's Office of Science Advanced Scientific Computing Research (ASCR) program. The PERI effort at Rice University focused on (1) research and development of tools for measurement and analysis of application program performance, and (2) engagement with SciDAC-2 application teams.
97 MATHEMATICS AND COMPUTING↗
Cloud Computing Option for Modeling the Debris Environment
NASA’s Digital Transformation Initiative aims to promote the agency’s adoption of current and evolving digital technologies. Through agency-wide collaboration with other NASA teams, the Office of Safety and Mission Assurance (OSMA) has directed the Orbital Debris Program Office and the Meteoroid Environment Office to integrate cloud computing technologies in their publicly released software models: the Orbital Debris Engineering Model (ORDEM) and the Meteoroid Engineering Model (MEM). Decoupling the user interface from the backend processor was key for the software packages to run on a cloud computing framework. Benefits to this design include horizontal scaling of computing resources, user authentication and authorization, and automated deployment. Both models are hosted on a cloud computing platform supported by the NASA authorized IT security and compliance framework. This paper focuses on the new ORDEM web application, which includes the current features of the publicly released ORDEM software with an upgraded frontend design. The underlying ORDEM processor is run on a cloud container, allowing the user to run multiple spacecraft and telescope/radar mode simulations. Featuresexclusive to the ORDEM web application, such as importing multiple TLEs, auto-generated plotting, and the ability to check runtime progress are discussed. Comparisons between the current ORDEM software and the web application are summarized.
Andrew Vavrin↗
Cloud Computing Option for Modeling the Debris Environment
NASA’s Digital Transformation Initiative aims to promote the agency’s adoption of current and evolving digital technologies. Through agency-wide collaboration with other NASA teams, the Office of Safety and Mission Assurance (OSMA) has directed the Orbital Debris Program Office and the Meteoroid Environment Office to integrate cloud computing technologies into their publicly released software models: the Orbital Debris Engineering Model (ORDEM) and the Meteoroid Engineering Model (MEM). Decoupling the user interface from the backend processor was key for the software packages to run on a cloud computing framework. Benefits to this design include horizontal scaling of computing resources, user authentication and authorization, and automated deployment. Both models are hosted on a cloud computing platform supported by the NASA authorized IT security and compliance framework. This paper focuses on the new ORDEM web application, which includes the current features of the publicly released ORDEM software with an upgraded frontend design, although parallels between ORDEM and MEM are also discussed. The underlying ORDEM processor is run on a cloud container, allowing the user to run multiple spacecraft and telescope/radar mode simulations. Features exclusive to the ORDEM web application, such as importing multiple TLEs, auto-generated plotting, and the ability to check runtime progress are discussed. Comparisons between the current ORDEM software and the web application are summarized.
Andrew Vavrin↗
Report for the DOE Office of Science Workshop on Envisioning Frontiers in AI and Computing for Biological Research
Artificial intelligence (AI), machine learning (ML), and high-performance computing (HPC) are poised to transform biological research, spurring innovation in biotechnology and biosystems design. "is transformation will bring an explosion of new capabilities to control the expression of genomic information in living organisms and harness that information to invent new biobased technologies (Jinek et al. 2012; NASEM 2025).
59 BASIC BIOLOGICAL SCIENCES↗
Advancing Understanding of Fission Gas Behavior in Nuclear Fuel through Leadership Class Computing
This report describes the outcome of the pilot SciDAC project jointly funded by the DOE Office of Nuclear Energy and the DOE Office of Science, Advanced Scientific Computing Research to advance understanding of fission gas behavior in nuclear fuel. The computational approach involved utilizing both a bottom up and top down multiscale materials modeling to evaluate the processes of xenon fission gas diffusion, xenon clustering and precipitation and the mechanisms of fission gas resolution by energetic fission fragments in uranium dioxide nuclear fuel. The computer science and applied mathematics research activities were focused on optimizing the uranium – oxygen – xenon interatomic potential implementation in the LAMMPS molecular dynamics code for large-scale simulations of fission gas resolution, in addition to improvements in visualization of accelerated molecular dynamics simulations and performance optimization of the Xolotl continuum cluster dynamics with a new grouping scheme to reduce the computational cost of modeling very large fission gas bubbles containing more than 10,000 xenon atoms. The most impactful result from this project stems from a systematic series of atomistic molecular dynamics to evaluate fission gas resolution from xenon bubbles that, combined with the fission product yields and consideration of electron-phonon coupling, informed a first principles model that predicts the magnitude of fission gas resolution in good agreement with empirical estimates.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Impact of Weak Agostic Interactions in Nickel Electrocatalysts for Hydrogen Oxidation
To understand how H2 binding and oxidation is influenced by [Ni(PR2NR'2)2]2+ PR2NR'2 catalysts with H2 binding energies close to thermoneutral, two [Ni(PPh2NR'2)2]2+ (R = Me or C14H29) complexes with phenyl substituents on phosphorous and varying alkyl chain lengths on the pendant amine were studied. In the solid state, [Ni(PPh2NMe2)2]2+ exhibits an anagostic interaction between the Ni(II) center and the a-CH3 of the pendant amine, and DFT and variable-temperature 31P NMR experiments suggest than the anagostic interaction persists in solution. The equilibrium constants for H2 addition to these complexes was measured by 31P NMR spectroscopy, affording free energies of H2 addition (?G°H2) of –0.8 kcal mol–1 in benzonitrile and –1.6 to –2.3 kcal mol–1 in THF. The anagostic interaction contributes to the low driving force for H2 binding by stabilizing the four-coordinate Ni(II) species prior to binding of H2. The pseudo-first order rate constants for H2 addition at 1 atm were measured by variable scan rate cyclic voltammetry, and were found to be similar for both complexes, less than 0.2 s–1 in benzonitrile and 3 –6 s–1 in THF. In the presence of exogenous base and H2 , turnover frequencies of electrocatalytic H2 oxidation were measured to be less than 0.2 s–1 in benzonitrile and 4 –9 s–1 in THF. These complexes are slower electrocatalysts for H2 oxidation than previously studied [Ni(PR2NR'2)2]2+ complexes due to a competition between H2 binding and formation of the anagostic interaction. However, the decrease in catalytic rate is accompanied by a beneficial 130 mV decrease in overpotential. This research was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences. Computational resources were provided at the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory. Mass spectrometry experiments were performed in the William R. Wiley Environmental Molecular Sciences Laboratory, a DOE national scientific user facility sponsored by the DOE’s Office of Biological and Environmental Research and located and the Pacific Northwest National Laboratory (PNNL). The authors thank Dr. Rosalie Chu for mass spectroscopy analysis. PNNL is operated by Battelle for DOE.
Klug, Christina↗
A survey of software implementations used by application codes in the Exascale Computing Project
The US Department of Energy Office of Science and the National Nuclear Security Administration initiated the Exascale Computing Project (ECP) in 2016 to prepare mission-relevant applications and scientific software for the delivery of the exascale computers starting in 2023. The ECP currently supports 24 efforts directed at specific applications and six supporting co-design projects. These 24 application projects contain 62 application codes that are implemented in three high-level languages—C, C++, and Fortran—and use 22 combinations of graphical processing unit programming models. The most common implementation language is C++, which is used in 53 different application codes. The most common programming models across ECP applications are CUDA and Kokkos, which are employed in 15 and 14 applications, respectively. This article provides a survey of the programming languages and models used in the ECP applications codebase that will be used to achieve performance on the future exascale hardware platforms.
97 MATHEMATICS AND COMPUTING↗
Extreme Heterogeneity 2018 - Productive Computational Science in the Era of Extreme Heterogeneity: Report for DOE ASCR Workshop on Extreme Heterogeneity
The 2018 Basic Research Needs Workshop on Extreme Heterogeneity identified five Priority Research Directions for realizing the capabilities needed to address the challenges posed in this era of rapid technological change. This report captures the outcomes of that workshop. In the context of extreme heterogeneity, it defines basic research needs and opportunities in computer science research to develop smart and trainable operating and runtime systems, programming environments, and predictive tools that will make future systems easier to adapt to scientists’ computing needs and easier for facilities to deploy securely.
97 MATHEMATICS AND COMPUTING↗
Basic Research Needs in Quantum Computing and Networking
Employing quantum mechanical resources in computing, information processing, and networking opens the door to potential exponential advantages over classical counterparts. However, quantifying and realizing such advantages poses extensive scientific and engineering challenges. Department of Energy (DOE) investments have driven steady progress in addressing such challenges. Recently developed quantum algorithms offer asymptotic exponential advantages in speed or accuracy for fundamental scientific problems. These problems include simulating physical systems, solving systems of linear equations, differential equations, and optimization problems. Empirical demonstrations on nascent quantum hardware suggest better performance on contrived computational tasks than classical analogs. However, the requirements for a quantum computer or network to demonstrate an end-to-end rigorously quantifiable performance improvement over classical analogs remains a grand challenge, especially for problems of practical value. In particular, what will be required for quantum technology to ultimately exhibit scalable, rigorous, and transformative performance advantages for practical applications? In July 2023, DOE’s Advanced Scientific Computing Research program in the Office of Science convened the Workshop on Basic Research Needs in Quantum Computing and Networking, where major opportunities and grand challenges were identified. The following five priority research directions (PRDs) were identified as a result of the workshop.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Report for the ASCR Workshop on Visualization for Scientific Discovery, Decision-Making, and Communication
Visualization—the use of visual elements to explore data, form hypotheses, or convey conclusions—is an integral part of the scientific process. Starting from an initial exploration of new data to illustrating outcomes for the general public, visualization is one of the most intuitive and powerful modes of communication. With the explosion of new data sources and types, unprecedented volumes of data, and new technologies, such as virtual reality (VR) and artificial intelligence (AI), visualization has become increasingly essential but also ever more challenging. The Department of Energy’s (DOE) Office of Advanced Scientific Computing Research (ASCR) sponsored a Basic Research Needs workshop in January 2022 to understand the major opportunities and grand challenges in visualization tools and technologies for scientific computing as well as for DOE-relevant applications and goals in general. The workshop identified five priority research directions (PRDs) for visualization to support scientific discovery, decision making, and communication. The first three PRDs describe interconnected research themes addressing the need for new techniques to deal with complex data, uncertainty, and interpretability (PRD 1); the need for scalable and interoperable software stacks (PRD 2); and the challenges and opportunities inherent in new technologies, such as VR, cloud, or exascale computing (PRD 3). The remaining two PRDs describe foundational research themes that recognize the potential of visualizations to provide equitable access to information and to strengthen the scientific discourse (PRD 4); and the need to consider human factors when designing visualizations (PRD 5). Collectively, these PRDs form the pillars for a coherent, long-term research and development strategy in Visualization for Scientific Discovery, Decision-Making, and Communication in the context of the Office of Science’s mission scope.
97 MATHEMATICS AND COMPUTING↗
Structural Analysis and Design Software
Collier Research and Development Corporation received a one-of-a-kind computer code for designing exotic hypersonic aircraft called ST-SIZE in the first ever Langley Research Center software copyright license agreement. Collier transformed the NASA computer code into a commercial software package called HyperSizer, which integrates with other Finite Element Modeling and Finite Analysis private-sector structural analysis program. ST-SIZE was chiefly conceived as a means to improve and speed the structural design of a future aerospace plane for Langley Hypersonic Vehicles Office. Including the NASA computer code into HyperSizer has enabled the company to also apply the software to applications other than aerospace, including improved design and construction for offices, marine structures, cargo containers, commercial and military aircraft, rail cars, and a host of everyday consumer products.
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