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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 253 records · Page 14

2016 Final Reports from the Los Alamos National Laboratory Computational Physics Student Summer Workshop

The two primary purposes of LANL’s Computational Physics Student Summer Workshop are (1) To educate graduate and exceptional undergraduate students in the challenges and applications of computational physics of interest to LANL, and (2) Entice their interest toward those challenges. Computational physics is emerging as a discipline in its own right, combining expertise in mathematics, physics, and computer science. The mathematical aspects focus on numerical methods for solving equations on the computer as well as developing test problems with analytical solutions. The physics aspects are very broad, ranging from low-temperature material modeling to extremely high temperature plasma physics, radiation transport and neutron transport. The computer science issues are concerned with matching numerical algorithms to emerging architectures and maintaining the quality of extremely large codes built to perform multi-physics calculations. Although graduate programs associated with computational physics are emerging, it is apparent that the pool of U.S. citizens in this multi-disciplinary field is relatively small and is typically not focused on the aspects that are of primary interest to LANL. Furthermore, more structured foundations for LANL interaction with universities in computational physics is needed; historically interactions rely heavily on individuals’ personalities and personal contacts. Thus a tertiary purpose of the Summer Workshop is to build an educational network of LANL researchers, university professors, and emerging students to advance the field and LANL’s involvement in it.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Real-Time Automated Health Information Technology Hazard Detection

The objective of this project is to develop an automated surveillance tool that will help the US Department of Veterans Affairs (VA) to detect potential hazards in health information technology (HIT) systems. To achieve this objective, Oak Ridge National Laboratory (ORNL) researchers have developed computational methods and a surveillance tool that will detect safety concerns and identify opportunities to improve HIT and safety within the VA system using Corporate Data Warehouse (CDW) data. This work is limited to the safe operation and safe use of HIT. It does not address the use of HIT to make health care safer. This project leveraged ORNL expertise in computational sciences and its computing resources accordingly.This report documents the FY 2019 accomplishments on this project. There were three major tasks. The first task developed data extraction approaches, which helped provide a better overall understanding of the important data elements in CDW. The outputs of this task served as inputs into the second task, which is the hazard detection and characterization task. This second task involved development of three methods that can be categorized into probabilistic model, event-based hazards detection, and system-based reliability performance evaluation. The third task dealt with the design, development, and demonstration of the automated surveillance tool. The tool currently resides in ORNL’s Private Health Information enclave at Oak Ridge, Tennessee, and operates on the VA’s CDW data. The developed capabilities and tool have been tested on CDW data from different clinical domains including Consult, Radiology, Laboratory, and Medication.

97 MATHEMATICS AND COMPUTING↗

Earth observations and global change decision making: A special bibliography, 1991

The first section of the bibliography contains 294 bibliographic citations and abstracts of relevant reports, articles, and documents announced in 'Scientific and Technical Aerospace Reports (STAR)' and 'International Aerospace Abstracts (IAA)'. These abstracts are categorized by the following major subject divisions: aeronautics, astronautics, chemistry and materials, engineering, geosciences, life sciences, mathematical and computer sciences, physics, social sciences, space sciences and general. Following the abstract section, seven indexes are provided for further assistance.

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NASA aerospace database subject scope: An overview

Outlined here is the subject scope of the NASA Aerospace Database, a publicly available subset of the NASA Scientific and Technical (STI) Database. Topics of interest to NASA are outlined and placed within the framework of the following broad aerospace subject categories: aeronautics, astronautics, chemistry and materials, engineering, geosciences, life sciences, mathematical and computer sciences, physics, social sciences, space sciences, and general. A brief discussion of the subject scope is given for each broad area, followed by a similar explanation of each of the narrower subject fields that follow. The subject category code is listed for each entry.

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Commonwealth of Independent States aerospace science and technology, 1992: A bibliography with indexes

This bibliography contains 1237 annotated references to reports and journal articles of Commonwealth of Independent States (CIS) intellectual origin entered into the NASA Scientific and Technical Information System during 1992. Representative subject areas include the following: aeronautics, astronautics, chemistry and materials, engineering, geosciences, life sciences, mathematical and computer sciences, physics, social sciences, and space sciences.

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The Technical Information Library: TIB

The Technische Informationsbibliothek Hannover (TIB) is the German national central library for all areas of technology and related sciences, especially chemistry, computer science, mathematics, and physics. The TIB acquires and makes available a comprehensive collection of conventional and non-conventional literature, especially foreign material, with particular emphasis on specialized new publications which are difficult to obtain or in difficult languages.

Rosemann, Uwe↗

Remote sensing/global change. A special bibliography

The first portion of this bibliography contains citations (with abstracts, when available) to unclassified literature contained in the NASA STI Database. These citations also appeared in issues of the abstract journal 'Scientific and Technical Aerospace Reports (STAR)', or in other announcement products offered by the NASA STI Program. The citations appear in ascending accession number order. A second section provides several indexes to the citations. They are subject term, personal author, report number, and accession number. The citations are included for the following disciplines as they relate to remote sensing and global change: astronautics, engineering, geosciences, life sciences, mathematical and computer sciences, social sciences, and space sciences.

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Johnson Space Center Research and Technology 1997 Annual Report

This report highlights key projects and technologies at Johnson Space Center for 1997. The report focuses on the commercial potential of the projects and technologies and is arranged by CorpTech Major Products Groups. Emerging technologies in these major disciplines we summarized: solar system sciences, life sciences, technology transfer, computer sciences, space technology, and human support technology. Them NASA advances have a range of potential commercial applications, from a school internet manager for networks to a liquid metal mirror for optical measurements.

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The SEL Adapts to Meet Changing Times

Since 1976, the Software Engineering Laboratory (SEL) has been dedicated to understanding and improving the way in which one NASA organization, the Flight Dynamics Division (FDD) at Goddard Space Flight Center, develops, maintains, and manages complex flight dynamics systems. It has done this by developing and refining a continual process improvement approach that allows an organization such as the FDD to fine-tune its process for its particular domain. Experimental software engineering and measurement play a significant role in this approach. The SEL is a partnership of NASA Goddard, its major software contractor, Computer Sciences Corporation (CSC), and the University of Maryland's (LTM) Department of Computer Science. The FDD primarily builds software systems that provide ground-based flight dynamics support for scientific satellites. They fall into two sets: ground systems and simulators. Ground systems are midsize systems that average around 250 thousand source lines of code (KSLOC). Ground system development projects typically last 1 - 2 years. Recent systems have been rehosted to workstations from IBM mainframes, and also contain significant new subsystems written in C and C++. The simulators are smaller systems averaging around 60 KSLOC that provide the test data for the ground systems. Simulator development lasts up to 1 year. Most of the simulators have been built in Ada on workstations. The SEL is responsible for the management and continual improvement of the software engineering processes used on these FDD projects.

Pajerski, Rose S.↗

New Horizons Regional Education Center 1999 FIRST Robotics Competition

The New Horizons Regional Education Center (NHREC) in Hampton, VA sought and received NASA funding to support its participation in the 1999 FIRST Robotics competition. FIRST, Inc. (For Inspiration and Recognition of Science and Technology) is an organization which encourages the application of creative science, math, and computer science principles to solve real-world engineering problems. The FIRST competition is an international engineering contest featuring high school, government, and business partnerships.

Purman, Richard I.↗

2000 FIRST Robotics Competition

The New Horizons Regional Education Center (NHREC) in Hampton, VA sought and received NASA funding to support its participation in the 2000 FIRST Robotics competition. FIRST, Inc. (For Inspiration and Recognition of Science and Technology) is an organization which encourages the application of creative science, math, and computer science principles to solve real-world engineering problems. The FIRST competition is an international engineering contest featuring high school, government, and business partnerships.

Purman, Richard↗

New Horizons Regional Education Center 2001 FIRST Robotics Competition

The New Horizons Regional Education Center (NHREC) in Hampton, VA sought and received NASA funding to support its participation in the 2001 FIRST Robotics competition. FIRST, Inc. (For Inspiration and Recognition of Science and Technology) is an organization which encourages the application of creative science, math, and computer science principles to solve real-world engineering problems. The FIRST competition is an international engineering contest featuring high school, government, and business partnerships.

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FIRST 2002, 2003, 2004 Robotics Competition(s)

The New Horizons Regional Education Center (NHREC) in Hampton, VA sought and received NASA funding to support its participation in the 2002, 2003, and 2004 FIRST Robotics Competitions. FIRST, Inc. (For Inspiration and Recognition of Science and Technology) is an organization which encourages the application of creative science, math, and computer science principles to solve real-world engineering problems. The FIRST competition is an international engineering contest featuring high school, government, and business partnerships.

Purman, Richard↗

An Innovative Approach to Bridge a Skill Gap and Grow a Workforce Pipeline: The Computer System, Cluster, and Networking Summer Institute

Sustainable and effective computing infrastructure depends critically on the skills and expertise of domain scientists and of committed and well-trained advanced computing professionals. But, in its ongoing High Performance Computing (HPC) work, Los Alamos National Laboratory noted a persistent shortage of well-prepared applicants, particularly for entry-level cluster administration, file systems administration, and high speed networking positions. Further, based upon recruiting efforts and interactions with universities graduating students in related majors of interest (e.g., computer science (CS)), there has been a long standing skillset gap, as focused training in HPC topics is typically lacking or absent in undergraduate and in even many graduate programs. Given that the effective operation and use of HPC systems requires specialized and often advanced training, that there is a recognized HPC skillset gap, and that there is intense global competition for computing and computational science talent, there is a long-standing and critical need for innovative approaches to help bridge the gap and create a well-prepared, next generation HPC workforce. Our paper places this need in the context of the HPC work and workforce requirements at Los Alamos National Laboratory (LANL) and presents one such innovative program conceived to address the need, bridge the gap, and grow an HPC workforce pipeline at LANL. The Computer System, Cluster, and Networking Summer Institute (CSCNSI) completed its 10th year in 2016. The story of the CSCNSI and its evolution is detailed below with a description of the design of its Boot Camp, and a summary of its success and some key factors that have enabled that success.

97 MATHEMATICS AND COMPUTING↗

Application of Quantum Machine Learning to High Energy Physics Analysis at LHC Using Quantum Computer Simulators and Quantum Computer Hardware

Machine learning enjoys widespread success in High Energy Physics (HEP) analyses at LHC. However the ambitious HL-LHC program will require much more computing resources in the next two decades. Quantum computing may offer speed-up for HEP physics analyses at HL-LHC, and can be a new computational paradigm for big data analyses in High Energy Physics.We have successfully employed three methods (1) Variational Quantum Classifier (VQC) method, (2) Quantum Support Vector Machine Kernel (QSVM-kernel) method and (3) Quantum Neural Network (QNN) method for two LHC flagship analyses: ttH (Higgs production in association with two top quarks) and H->mumu (Higgs decay to two muons, the second generation fermions). We shall address the progressive improvements in performance from method (1) to method (3).We will present our experiences and results of a study on LHC High Energy Physics data analyses with IBM Quantum Simulator and Quantum Hardware (using IBM Qiskit framework), Google Quantum Simulator (using Google Cirq framework), and Amazon Quantum Simulator (using Amazon Braket cloud service). The work is in the context of a Qubit platform (a gate-model quantum computer). Taking into account the present limitation of hardware access, different quantum machine learning methods are studied on simulators and the results are compared with classical machine learning methods (BDT, classical Support Vector Machine and classical Neural Network). Furthermore, we do apply quantum machine learning on IBM quantum hardware to compare performance between quantum simulator and quantum hardware. The work is performed by an international and interdisciplinary collaboration with the Department of Physics and Department of Computer Sciences of University of Wisconsin, CERN Quantum Technology Initiative, IBM Research Zurich, IBM T.J. Watson Research Center, Fermilab Quantum Institute, BNL Computational Science Initiative, State University of New York at Stony Brook, and Quantum Computing and AI Research of Amazon Web Services. This work pioneers a close collaboration of academic institutions with industrial corporations in the High Energy Physics analyses effort. Though the size of event samples in future HL-LHC physics and the limited number of qubits pose some challenges to the Quantum Machine learning studies for High Energy Physics, more advanced quantum computers with larger number of qubits, reduced noise and improved running time (as envisioned by IBM and Google) may outperform classical machine learning in both classification power and in speed.Although the era of efficient quantum computing may still be years away, we have made promising progress and obtained preliminary results in applying quantum machine learning to High Energy Physics. A PROOF OF PRINCIPLE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

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↗

Code 672 observational science branch computer networks

In general, networking increases productivity due to the speed of transmission, easy access to remote computers, ability to share files, and increased availability of peripherals. Two different networks within the Observational Science Branch are described in detail.

Hancock, D. W.↗

Empowering Scientific Innovation Through An Integrated Research Infrastructure: The Role of the Advanced Computing Ecosystem

As the landscape of computational science evolves, the Department of Energy (DOE) is reimagining the roles of its large-scale computing facilities to meet emerging research challenges. The Integrated Research Infrastructure (IRI) program aims to transform how experiments are designed, conducted, and shared, with significant impacts on all stakeholders. In response, the Oak Ridge Leadership Computing Facility (OLCF) has established the Advanced Computing Ecosystem (ACE), a strategic framework to prepare its hardware, software, and experimental capabilities for the IRI era. ACE focuses on integrating novel compute environments, orchestrating advanced workflows, and developing foundational technologies, ensuring a seamless transition to IRI while accelerating scientific discovery. This paper outlines ACE's role in advancing OLCF's mission and its impact on the future of computational science.

Widener, Patrick↗