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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

Scientific Computation Application Partnerships in Materials and Chemical Sciences, Charge Transfer and Charge Transport in Photoactivated Systems, Developing Electron-Correlated Methods for Excited State Structure and Dynamics in the NWChem Software Suite

Charge transfer and charge transport in photoactivated systems are fundamental processes that underlie solar energy capture, solar energy conversion, and photoactivated catalysis, both organometallic and enzymatic. We developed methods, algorithms, and software tools needed for reliable treatment of the underlying physics for charge transfer and charge transport, an undertaking with broad applicability to the goals of the fundamental-interaction component of the Department of Energy Office of Basic Energy Sciences and the exascale initiative of the Office of Advanced Scientific Computing Research.

14 SOLAR ENERGY↗

ASCR Report on a Quantum Computing Testbed for Science

This report details the findings of the Quantum Testbed Stakeholder Workshop sponsored by the Department of Energy’s Advanced Scientific Computing Research Program to identify opportunities and challenges in establishing a quantum testbed to advance quantum computing hardware and software systems that will enable science investigations. The workshop was help on February 14 – 16, 2017 in Washington DC and served as a forum for individual stakeholders from academia, industry, national laboratories, and government to provide their perspectives and ideas on the overarching goals and objectives of a quantum testbed, technical considerations, and how a quantum testbed program would be synergistic with other nascent quantum computing efforts in the US and worldwide. This report summarizes discussions on best practices for management of various types of collaborative research activities, including topics such as workforce training and building strong relationships with the research community. It also reviews specific technologies that have been identified by the ASCR Program as being important for the success of a quantum testbed whose overall goal is advancing quantum computing for scientific applications in the next five years.

97 MATHEMATICS AND COMPUTING↗

Virtual Infrastructure Twins: Software Testing Platforms for Computing-Instrument Ecosystems

Science ecosystems are being built by federating computing systems and instruments located at geographically distributed sites over wide-area networks. These computing-instrument ecosystems are expected to support complex workflows that incorporate remote, automated AI-driven science experiments. Their realization, however, requires various designs to be explored and software components to be developed, in order to support the orchestration of distributed computations and experiments. It is often too expensive, infeasible, or disruptive for the entire ecosystem to be available during the typically long software development and testing periods. We propose a Virtual Infrastructure Twin (VIT) of the ecosystem that emulates its network and computing components, and incorporates its instrument software simulators. It provides a software environment nearly identical to the ecosystem to support early development and testing, and design space exploration. We present a brief overview of previous digital infrastructure twins that culminated in the VIT concept, including (i) the virtual science network environment for developing software-defined networking solutions, and (ii) the virtual federated science instrument environment for testing the federation software stack and remote instrument control software. We briefly describe VITs for Nion microscope steering and access to GPU systems.

Rao, Nageswara↗

Virtual Infrastructure Twins: Software Testing Platforms for Computing-Instrument Ecosystems

Science ecosystems are being built by federating computing systems and instruments located at geographically distributed sites over wide-area networks. These computing-instrument ecosystems are expected to support complex workflows that incorporate remote, automated AI-driven science experiments. Their realization, however, requires various designs to be explored and software components to be developed, in order to support the orchestration of distributed computations and experiments. It is often too expensive, infeasible, or disruptive for the entire ecosystem to be available during the typically long software development and testing periods. We propose a Virtual Infrastructure Twin (VIT) of the ecosystem that emulates its network and computing components, and incorporates its instrument software simulators. It provides a software environment nearly identical to the ecosystem to support early development and testing, and design space exploration. We present a brief overview of previous digital infrastructure twins that culminated in the VIT concept, including (i) the virtual science network environment for developing software-defined networking solutions, and (ii) the virtual federated science instrument environment for testing the federation software stack and remote instrument control software. We briefly describe VITs for Nion microscope steering and access to GPU systems.

Rao, Nageswara↗

Investigating Deformation and Failure Mechanisms in Nanoscale Multilayer Metallic Composites

Over the history of materials science there are many examples of materials discoveries that have made superlative materials; the strongest, lightest, or toughest material is almost always a goal when we invent new materials. However, often these have been a result of enormous trial and error approaches. A new methodology, one in which researchers design, from the atoms up, new ultra-strong materials for use in energy applications, is taking hold within the science and engineering community. This project focused on one particular new classification of materials; nanolaminate metallic composites. These materials, where two metallic materials are intimately bonded and layered over and over to form sheets or coatings, have been shown over the past decade to reach strengths over 10 times that of their constituents. However, they are not yet widely used in part because while extremely strong (they don’t permanently bend), they are also not particularly tough (they break relatively easily when notched). Our program took a coupled approach to investigating new materials systems within the laminate field. We used computational materials science to explore ways to institute new deformation mechanisms that occurred when a tri-layer, rather than the more common bi-layer system was created. Our predictions suggested that copper-nickel or copper-niobium composites (two very common bi-layer systems) with layer thicknesses on the order of 20 nm and then layered 100’s of times, would be less tough than a copper-nickel-niobium metallic composite of similar thicknesses. In particular, a particular mode of permanent deformation, cross-slip, could be activated only in the tri-layer system; the crystal structure of the other bi-layers would prohibit this particular mode of deformation. We then experimentally validated this predication using a wide range of tools. We utilized a DOE user facility, the Center for Integrated Nanotechnology (CINT), to fabricate, for the first time, these tri-layer composites. CINT formed nanolaminate composites were tested in tension, with bulge testing, using nanoindentation, and using micro-compression testing to demonstrate that the tri-layer films were indeed tougher and hardened more during deformation (they got stronger as we deformed them) than equivalent bi-layers. The seven graduate students, 4 post-docs and research faculty, and the two faculty co-PI’s were able to create a collaborated computational prediction and experimental validation team to demonstrate the benefits of this class of materials to the community. The computational work crossed from atomistic to bulk simulations, and the experiments coupled form nm-scale to the mm scale; closely matching the simulations. The simulations provided viable mechanisms that explained the observed results, and new experimental results were used to push the boundaries of the simulation tools. Over the life of the 7 years of this program we proved that tri-layer nanolaminate metallic composite systems exceeded the mechanical performance of bi-layer systems if the right materials were chosen, and that the mechanism responsible for this was tied to the cross slip of dislocations. With 30 journal publications resulting from this work we have broadly disseminated this family of results to the scientific community.

36 MATERIALS SCIENCE↗

Early Science on Theta

At the Argonne Leadership Computing Facility, the process for standing up a new system is paired with The Early Science Program. This competitive program prepares a select group of applications science teams to use the new machine very readily by providing them staff support and early access to preproduction system hardware and software. As a result, this column describes three Theta Early Science projects: two science applications and one code development effort.

97 MATHEMATICS AND COMPUTING↗

Women in Science: Fermilab cybersecurity analyst Jeny Teheran

With 11 February marking the International Day of Women and Girls in Science, female physicists, engineers and computer scientists from CERN and from Fermilab share their experiences of building a career in science. Jeny Teheran is a security analyst and cybersecurity researcher at Fermi National Accelerator Laboratory. That means keeping up with and taking care of hardware and software vulnerabilities so that the experiments can carry out their science in a secure manner. It's a fast-paced job where you have to come with the best solution you can put in place, right in the moment. "I would recommend this job because it challenges you. It pushes you to be on top of your game. You have to improve your analytical skills; you have to react fast; you have to communicate better." - Jeny says. Jeny came to Fermilab from the Caribbean coast of Colombia. She grew up in a house with few toys but lots of books, and says she has always felt close to science. With a degree in systems and computing engineering, she arrived at Fermilab four years ago as an intern to work on the offline production team for neutrino experiments. A year later, she was hired as a security analyst. "And I'm loving it," she says. Credits: Video production - Fermilab Creative Services Music Copyright: Universal Production Music Astral Light Chevalier Idea originally conceived by Tanya Levshina, Fermilab and Maria Dimou, CERN.

99 GENERAL AND MISCELLANEOUS↗

Position Papers for the 2024 ASCR Workshop on Energy-Efficient Computing for Science

On behalf of the Advanced Scientific Computing Research (ASCR) program in the US Department of Energy (DOE) Office of Science, we are organizing a Workshop on Energy-Efficient Computing for Science (EECS). Energy efficiency involves coordination across all the interoperating components of a computing system—in particular, applications, algorithms, system software, programming models, data management, and the hardware on which they run. Looking 10-15 years into the future, the goal is to dramatically lower the energy costs of the computational platforms (from the data center to the edge) serving DOE science while expanding the capabilities of these systems, broadening their applicability to science challenges of interest to DOE and the nation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Analyzing a Five-Year Failure Record of a Leadership-Class Supercomputer

Extreme-scale computing systems are required to solve some of the grand challenges in science and technology. From astrophysics to molecular biology, supercomputers are an essential tool to accelerate scientific discovery. However, large computing systems are prone to failures due to their complexity. It is crucial to develop an understanding of how these systems fail to design reliable supercomputing platforms for the future. This paper examines a five-year failure and workload record of a leadership-class supercomputer. To the best of our knowledge, five years represents the vast majority of the lifespan of a supercomputer. This is the first time such analysis is performed on a top 10 modern supercomputer. We performed a failure categorization and found out that: i) most errors are GPU-related, with roughly 37% of them being double-bit errors on the cards; ii) failures are not evenly spread across the physical machine, with room temperature presumably playing a major role; and iii) software errors of the system bring down several nodes concurrently. Our failure rate analysis unveils that: i) the system consistently degrades, being at least twice as reliable at the beginning, compared to the end of the period; ii) Weibull distribution closely fits the mean-time-between-failure data; and iii) hardware and software errors show a markedly different pattern. Finally, we correlated failure and workload records to reveal that: i) failure and workload records are weakly correlated, except for certain types of failures when segmented by the hours of the day; ii) several categories of failures make jobs crash within the first minutes of execution; and iii) a significant fraction of failed jobs exhaust the requested time with a disregard of when the failure occurred during execution.

Rojas, Elvis↗

Circular Economy - A challenge and an opportunity for Process Systems Engineering

Rising populations put huge stresses on natural resources. Extraction and depletion of raw materials and waste created throughout the supply chain of products have enormous environmental and socioeconomic impacts. One way to reduce these impacts is through the move towards the circular economy (CE). CE aims to solve resource, waste, and emission challenges confronting society by creating a production-to-consumption total supply chain that is restorative, regenerative, and environmentally benign. This article highlights research challenges and identifies process systems engineering (PSE) research opportunities to assist in the understanding, analysis and optimization of CE supply chains. A motivating example on the supply chain of coffee is introduced to illustrate the challenges of the transition towards a CE and to propose PSE research opportunities.

42 ENGINEERING↗

Recovery of Damaged Information and the Out-of-Time-Ordered Correlators

The evolution with a complex Hamiltonian generally leads to information scrambling. A time-reversed dynamics unwinds this scrambling and thus leads to the original information recovery. In this work, we show that if the scrambled information is, in addition, partially damaged by a local measurement, then such a damage can still be treated by application of the time-reversed protocol. This information recovery is described by the long-time saturation value of a certain out-of-time-ordered correlator of local variables. We also propose a simple test that distinguishes between quantum and reversible classical chaotic information scrambling.

97 MATHEMATICS AND COMPUTING↗

Version [OpenIPSL 2.0.0] - [iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations]

This paper describes Open-Instance Power System Library (OpenIPSL) version 2.0.0 and its most recent enhancements. This new version brings upgrades that include more robust models that are better documented, and example systems that illustrate certain functionalities to users. Repository and library documentations have been enhanced and expanded, and the library is now released under a new license. Changes are meant to foster user and developer communities, while providing more attractive frameworks for collaborative work to be carried out with the library.

97 MATHEMATICS AND COMPUTING↗

Center for Technology for Advanced Scientific Component Software (TASCS) (Final Technical Report)

This is a final technical report for the University of Maryland work in the SciDAC Center for Technology for Advanced Scientific Component Software (TASCS). The Maryland work focused on software tools for coupling parallel software components built using the Common Component Architecture (CCA) APIs. Those tools are based on the Maryland InterComm software framework that has been used in multiple computational science applications to build large-scale simulations of complex physical systems that employ multiple separately developed codes.

97 MATHEMATICS AND COMPUTING↗

Elucidating and predicting the dynamic evolution of water and land systems due to natural and energy-related forcings

Focal Area(s): 3. Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI; & 1. Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, unsupervised learning (including deep learning), and hardware-related efforts involving AI (e.g., edge computing). Science Challenge: Interactions between water, land, and energy systems are complex and occur on a variety of scales, ranging from local to basinal to regional. Accurately predicting the behavior of ground water and surface water systems for 5-10 years and beyond requires an understanding of the current system and the ability to model both the natural system at scale and human-induced forcings related to energy and other activities. Artificial intelligence and machine learning (AI/ML) combined with modern compilation and integration efforts for U.S. groundwater and surface water systems present potential solutions to bolstering detailed physics-based models of these systems. Big data tied with ML and physics-based modeling can drive breakthroughs in understanding the earth system, but research is often impeded by data access (e.g., privacy issues), quality, formats, gaps, multi-source, multi-scale, integration, and spatiotemporal challenges. Effective integration of real data and simulated (synthetic) data that fill gaps is critical. Overcoming these complex data and model integration challenges will enable a transformational approach to acquiring enhanced understanding of environmental systems.

54 ENVIRONMENTAL SCIENCES↗

Multi-omic data integration enables discovery of hidden biological regularities

Rapid growth in size and complexity of biological data sets has led to the ‘Big Data to Knowledge’ challenge. We develop advanced data integration methods for multi-level analysis of genomic, transcriptomic, ribosomal profiling, proteomic and fluxomic data. First, we show that pairwise integration of primary omics data reveals regularities that tie cellular processes together in Escherichia coli: the number of protein molecules made per mRNA transcript and the number of ribosomes required per translated protein molecule. Second, we show that genome-scale models, based on genomic and bibliomic data, enable quantitative synchronization of disparate data types. Integrating omics data with models enabled the discovery of two novel regularities: condition invariant in vivo turnover rates of enzymes and the correlation of protein structural motifs and translational pausing. These regularities can be formally represented in a computable format allowing for coherent interpretation and prediction of fitness and selection that underlies cellular physiology.

59 BASIC BIOLOGICAL SCIENCES↗