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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Enabling opportunistic resources for CMS Computing Operations

With the increased pressure on computing brought by the higher energy and luminosity from the LHC in Run 2, CMS Computing Operations expects to require the ability to utilize opportunistic resources resources not owned by, or a priori configured for CMS to meet peak demands. In addition to our dedicated resources we look to add computing resources from non CMS grids, cloud resources, and national supercomputing centers. CMS uses the HTCondor/glideinWMS job submission infrastructure for all its batch processing, so such resources will need to be transparently integrated into its glideinWMS pool. Bosco and parrot wrappers are used to enable access and bring the CMS environment into these non CMS resources. Finally, we describe our strategy to supplement our native capabilities with opportunistic resources and our experience so far using them.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing

Neuromorphic computers could overcome efficiency bottlenecks inherent to conventional computing through parallel programming and readout of artificial neural network weights in a crossbar memory array. However, selective and linear weight updates and <10-nanoampere read currents are required for learning that surpasses conventional computing efficiency. We introduce an ionic floating-gate memory array based on a polymer redox transistor connected to a conductive-bridge memory (CBM). Selective and linear programming of a redox transistor array is executed in parallel by overcoming the bridging threshold voltage of the CBMs. Synaptic weight readout with currents <10 nanoamperes is achieved by diluting the conductive polymer with an insulator to decrease the conductance. The redox transistors endure >1 billion write-read operations and support >1-megahertz write-read frequencies.

bio-inspired, energy storage (including batteries ↗
DOE OSTI2023

Understanding the Computing and Analysis Needs for Resiliency of Power Systems from Severe Weather Impacts

As the frequency and intensity of severe weather has increased, its effect on the electric grid has manifested in the form of significantly more and larger outages in the United States. This has become especially true for regions that were previously isolated from weather extremes. In this paper, we analyze the weather impacts on the electric power grid across a variety of weather conditions, draw correlations, and provide practical insights into the operational state of these systems. High resolution computational modeling of specific meteorological variables, computational approaches to solving power system models under these conditions, and the types of resiliency needs are highlighted as goal-oriented computing approaches are being built to address grid resiliency needs. An example analysis correlating outages to 1km day-ahead weather from two historical winter storms, calculated on a large cluster using a combination of interpolated and extrapolated inputs from multiple instrumented sites to workflows that produce primary meteorological outputs, is shown as initial proof of concept.

analysis↗
DOE OSTI2021

COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

High Performance Computing Facility Operational Assessment 2016 - Oak Ridge Leadership Computing Facility

Oak Ridge National Laboratory’s (ORNL’s) Leadership Computing Facility (OLCF) continues to surpass its operational target goals: supporting users; delivering fast, reliable systems; creating innovative solutions for high-performance computing (HPC) needs; and managing risks, safety, and security associated with operating one of the most powerful computers in the world. The results can be seen in the cutting-edge science delivered by users and the praise from the research community. Calendar year (CY) 2016 was filled with outstanding operational results and accomplishments: a very high rating from users on overall satisfaction for the third year in a row; the greatest number of core hours delivered to research projects; the largest number of research publications for the life of Titan; and success in delivering on the allocation of 60%, 30%, and 10% of core hours offered for the Innovative and Novel Computational Impact on Theory and Experiment (INCITE), Advanced Scientific Computing Research Leadership Computing Challenge (ALCC), and Director’s Discretionary (DD) programs, respectively. These accomplishments, coupled with the extremely high utilization rate, represent the fulfillment of the promise of Titan: maximum use by maximum-size simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Toward a Compatible Reproducibility Taxonomy for Computational and Computing Sciences

Reproducibility is an essential ingredient of the scientific enterprise. The ability to reproduce results builds trust that we can rely on the results as foundations for future scientific exploration. Presently, the fields of computational and computing sciences provide two opposing definitions of reproducible and replicable. In computational sciences, reproducible research means authors provide all necessary data and computer codes to run analyses again, so others can re-obtain the results (J. Claerbout et al., 1992). The concept was adopted and extended by several communities, where it was distinguished from replication: collecting new data to address the same question, and arriving at consistent findings (Peng et al. 2006). The Association of Computing Machinery (ACM), representing computer science and industry professionals, recently established a reproducibility initiative, adopting essentially opposite definitions. The purpose of this report is to raise awareness of the opposite definitions and propose a path to a compatible taxonomy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Quantum Computing Technology Roadmaps and Capability Assessment for Scientific Computing - An analysis of use cases from the NERSC workload

The National Energy Research Scientific Computing Center (NERSC), as the high-performance computing (HPC) facility for the Department of Energy’s Office of Science, recognizes the essential role of quantum computing in its future mission. In this report, we analyze the NERSC workload and identify materials science, quantum chemistry, and high-energy physics as the science domains and application areas that stand to benefit most from quantum computers. These domains jointly make up over 50% of the current NERSC production workload, which is illustrative of the impact quantum computing could have on NERSC’s mission going forward. We perform an extensive literature review and determine the quantum resources required to solve classically intractable problems within these science domains. This review also shows that the quantum resources required have consistently decreased over time due to algorithmic improvements and a deeper understanding of the problems. At the same time, public technology roadmaps from a collection of ten quantum computing companies predict a dramatic increase in capabilities over the next five to ten years. Our analysis reveals a significant overlap emerging in this time frame between the technological capabilities and the algorithmic requirements in these three scientific domains. We anticipate that the execution time of large-scale quantum workflows will become a major performance parameter and propose a simple metric, the Sustained Quantum System Performance (SQSP), to compare system-level performance and throughput for a heterogeneous workload.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Controlling data transfers from an origin compute node to a target compute node

Methods, apparatus, and products are disclosed for controlling data transfers from an origin compute node to a target compute node that include: receiving, by an application messaging module on the target compute node, an indication of a data transfer from an origin compute node to the target compute node; and administering, by the application messaging module on the target compute node, the data transfer using one or more messaging primitives of a system messaging module in dependence upon the indication.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Transforming Energy through Computational Science: Computing for Clean Energy

This fact sheet discusses the opportunity space for NREL's computational science capabilities to address national clean energy objectives. Achieving a carbon-free power sector by 2035 as a step towards a decarbonized U.S. energy economy in 2050 will require major advances in power generation, autonomous energy systems, transportation, and buildings/communities. Development of integrated modeling approaches for complex energy systems will be essential for deployment. Success requires developments in optimization and control theory, complemented by machine learning (ML) and artificial intelligence (AI), all of which in turn need targeted investments in breadth and scale of computing. This document defines an opportunity space where: embracing computing can link established research and development (R&D) to a decarbonization agenda; pursuing emerging approaches can accelerate the pace of technology advancement across the portfolio; and leading by example could reduce the carbon footprint of computing worldwide.

advanced computing↗
DOE OSTI2018

25 Mg NMR and Computational Modeling Studies of the Solvation Structures and Molecular Dynamics in Magnesium Based Liquid Electrolytes

There is increasing evidence that the solvation structure of the active components in a liquid electrolyte solution strongly impacts the performance in electrochemical applications. In this work, the nanoscale solvation structures and dynamics of Mg(BH 4 ) 2 and Mg(TFSI) 2 dissolved in diglyme (DGM) at various concentrations and ratios of Mg(BH 4 ) 2 /Mg(TFSI) 2 were investigated using a combination of natural abundance 25 Mg NMR, quantum chemistry calculations of 25 Mg NMR chemical shifts, classical molecular dynamics (MD) calculations, and electrochemical performance tests. By mixing two competing Mg salts, we were able to reduce the strong covalent interactions between Mg 2+ and BH 4 – anions. A small increase is observed in the coordination number of Mg-TFSI and a significant increase in the interaction of Mg 2+ ions with glymes. Through a combination of NMR, DFT and MD simulations, various stable species around 1 nm in size were detected in the mixed salt solution, which play key roles in the enhanced electrochemical performance of the mixed electrolyte. It is established that for the neat Mg(TFSI) 2 in DGM electrolyte at dilute concentrations the TFSI - is fully dissociated from Mg 2+ . At higher concentrations, Mg 2+ and TFSI - are only partially dissociated as contact ion pairs are formed. In contrast, at 0.01 M Mg(BH 4 ) 2 (saturated concentration) in DGM, the first solvation shell of a Mg 2+ ion contains two BH 4 - anions and one DGM molecule, while the second solvation shell consists of five to six DGM molecules. An exchange mechanism between the solvation structures in the combined electrolyte containing both Mg(BH 4 ) 2 and Mg(TFSI) 2 in DGM was found to result in the observation of a single 25 Mg NMR peak. This exchange is responsible for an increase in uncoordinated anions, as well as improved stability and ionic conductivity as compared to single anion solution. Solvent molecule rearrangement and direct Mg-ion exchange between the basic solvation structures are hypothesized as likely reasons for the exchange. We elucidate that the solvent rearrangement is energetically much more favorable than direct Mg-ion hopping and is thus suggested as the dominant exchange mechanism.

Magnesium battery, electrolytes, Mg(BH4)2, Mg(TFSI↗
DOE OSTI2012

Obtaining Mixed Ionic/Electronic Conductivity in Perovskite Oxides in a Reducing Environment: A Computational Prediction for Doped SrTiO3

The electronic conductivity and thermodynamic stability of mixed p- and n-doped SrTiO3 perovskites have been investigated under anodic solid oxide fuel cell conditions using density functional theory (DFT). In particular, constrained ab initio thermodynamic calculations have been performed to evaluate the phase stability of various Ga- and La-doped SrTiO3 at synthesized and anodic SOFC conditions. The density of states (DOS) of these materials was analyzed to determine the number of charge carriers and the degree of electronic conductivity. We find that a mixed ionic/electronic conductor can be obtained when doping SrTiO3 perovskite oxide with both p-type and n-type dopants. Calculations show that 10% Ga- and 20% La-doped SrTiO3 exhibit mixed ionic/electronic conductivity at high temperature and low oxygen partial pressure whereas doping with higher concentrations of Ga, e.g., 20%, diminishes the electronic conductivity of the material. Furthermore, changing the n-dopant from La (A-site) to Nb (B-site) does not significantly affect the reducibility and number of charge carriers in p- and n-doped SrTiO3. However, a higher degree of oxygen vacancy clustering is observed for the La-doped material which reduces the oxygen ion diffusion rate and traps electrons. Nevertheless, our findings suggest that independent of doping site, mixed ionic/ electronic conductivity can be obtained in SrTiO3 perovskite oxides under reducing conditions and high temperatures when using a mixed p- and n-type doping strategy that uses a p-dopant concentration smaller than the n-dopant concentration.

Environmental Molecular Sciences Laboratory↗