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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Special Issue in Honor of Professor S. Ted Oyama: 2014 ACS Distinguished Researcher Award in Petroleum Chemistry and Storch Award in Fuel Science

This special issue of Topics in Catalysis honors Professor S. Ted Oyama for his Awards in Petroleum Chemistry and Fuel Science Research. These awards were celebrated at two American Chemical Society (ACS) symposia in 2014. First, the ACS’s Distinguished Research Award in Petroleum Chemistry Symposium, took place at the 247th ACS National Meeting in Dallas, TX, during March 17-19, 2014 and the second one, the ACS’s Storch Award in Fuel Science Symposium, took place at the 248th ACS National Meeting in San Francisco, CA, during August 10-12, 2014. Professor Oyama received the 2014 ACS Distinguished Research Award in Petroleum Chemistry ‘‘for his substantial contributions to the field of heterogeneous catalysis’’ including the discovery of highly active transition metal phosphide catalysts for hydrotreatment of petroleum and coal-derived feedstocks and biomass refining, the development of new compositions, and the understanding of their reaction mechanisms by in situ spectroscopic techniques at high temperatures and pressures of reaction. In light of this recognition, Professor Oyama was also awarded the 2014 ACS Storch Award in Fuel Science ‘‘for his broad contributions to the field of fuel science’’ including the production of hydrogen by catalytic reforming, selective oxidation of hydrocarbons, biomass conversion, their reaction kinetics and mechanisms, and spectrokinetic methods to study catalysts in situ at reaction conditions and theory and application of inorganic membranes for separation of hydrogen and fuel-relevant gases. Finally, this special issue consists of contributions by catalysis researchers who participated in the two ACS symposia honoring Professor Oyama’s Awards.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Software-Defined Network for End-to-end Networked Science at the Exascale

Domain science applications and workflow processes are currently forced to view the network as an opaque infrastructure into which they inject data and hope that it emerges at the destination with an acceptable Quality of Experience. There is little ability for applications to interact with the network to exchange information, negotiate performance parameters, discover expected performance metrics, or receive status/troubleshooting information in real time. The work we presen here is motivated by a vision for a new smart network and smart application ecosystem that will provide a more deterministic and interactive environment for domain science workflows. The Software-Defined Network for End-to-end Networked Science at Exascale (SENSE) system includes a model-based architecture, implementation, and deployment which enables automated end-to-end network service instantiation across administrative domains. An intent based interface allows applications to express their high-level service requirements, an intelligent orchestrator and resource control systems allow for custom tailoring of scalability and real-time responsiveness based on individual application and infrastructure operator requirements. This allows the science applications to manage the network as a first-class schedulable resource as is the current practice for instruments, compute, and storage systems. Deployment and experiments on production networks and testbeds have validated SENSE functions and performance. Emulation based testing verified the scalability needed to support research and education infrastructures. Key contributions of this work include an architecture definition, reference implementation, and deployment. This provides the basis for further innovation of smart network services to accelerate scientific discovery in the era of big data, cloud computing, machine learning and artificial intelligence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

RAON experimental facilities for nuclear science

The Rare Isotope Science Project (RISP) was established in December 2011 and has put quite an effort to carry out the design and construction of the accelerator complex facility named “RAON”. RAON is a rare isotope (RI) beam facility that aims to provide various RI beams of proton-and neutron-rich nuclei as well as variety of stable ion beams of wide ranges of energies up to a few hundreds MeV/nucleon for the researches in basic science and application. Proposed research programs for nuclear physics and nuclear astrophysics at RAON include studies of the properties of exotic nuclei, the equation of state of nuclear matter, the origin of the universe, process of nucleosynthesis, super heavy elements, etc. Various high performance magnetic spectrometers for nuclear science have been designed, which are KOBRA (KOrea Broad acceptance Recoil spectrometer and Apparatus), LAMPS (Large Acceptance Multi-Purpose Spectrometer), and ZDS (Zero Degree Spectrometer). The status of those spectrometers for nuclear science will be presented with a brief report on the RAON.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Scalable quantum computational science: A perspective from block-encodings and polynomial transformations

Significant developments made in quantum hardware and error correction recently have been driving quantum computing toward practical utility. However, gaps remain between abstract quantum algorithmic development and practical applications in computational sciences. In this perspective article, we propose several properties that scalable quantum computational science methods should possess. We further discuss how block-encodings and polynomial transformations can potentially serve as a unified framework with the desired properties. Recent advancements on these topics are presented, including the construction and assembly of block-encodings, and various generalizations of quantum signal processing (QSP) algorithms to perform polynomial transformations. The scalability of QSP methods on parallel and distributed quantum architectures is also highlighted. Promising applications in simulation and observable estimation in chemistry, physics, and optimization problems are presented. We hope this perspective serves as a gentle introduction to state-of-the-art quantum algorithms for the computational science community and inspires future development of scalable quantum computational science methodologies that bridge theory and practice.

Bayesian inference↗
DOE OSTI2018

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↗
DOE OSTI2024

Transforming Science Through Software: Improving While Delivering 100×

The U.S. Department of Energy (DOE) Exascale Computing Project (ECP) funded the development of new (and the transformation of important existing) applications, libraries, and tools that realized improvement in performance and capabilities of often 100 times or more on emerging exascale computers. This exceptional gain inspired the title of this special issue: Transforming Science through Software: Improving while delivering 100X. The term 100X refers to advancing capabilities in modeling, simulation, and analysis by a factor of 100 or more using some combination of new algorithms, optimization techniques, software libraries, and programming models, coupled with the next generation of hardware for high-performance computing (HPC). The papers in this issue share experiences with the practice and science of scientific software development, with an emphasis on developing a coherent, portable, and sustainable HPC software ecosystem for next-generation computational science. Finally, we hope to foster expanded community efforts related to the fundamental role of sustainable scientific software ecosystems in advancing the computing sciences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Science Capsule: Towards Sharing and Reproducibility of Scientific Workflows

Workflows are increasingly processing large volumes of data from scientific instruments, experiments and sensors. These workflows often consist of complex data processing and analysis steps that might include a diverse ecosystem of tools and also often involve human-in-the-loop steps. Sharing and reproducing these workflows with collaborators and the larger community is critical but hard to do without the entire context of the workflow including user notes and execution environment. In this paper, we describe Science Capsule, which is a framework to capture, share, and reproduce scientific workflows. Science Capsule captures, manages and represents both computational and human elements of a workflow. It automatically captures and processes events associated with the execution and data life cycle of workflows, and lets users add other types and forms of scientific artifacts. Science Capsule also allows users to create `workflow snapshots' that keep track of the different versions of a workflow and their lineage, allowing scientists to incrementally share and extend workflows between users. Our results show that Science Capsule is capable of processing and organizing events in near real-time for high-throughput experimental and data analysis workflows without incurring any significant performance overheads.

Ghoshal, Devarshi↗
DOE OSTI2017

Python in the NERSC Exascale Science Applications Program for Data

We describe a new effort at the National Energy Re- search Scientific Computing Center (NERSC) in performance analysis and optimization of scientific Python applications targeting the Intel Xeon Phi (Knights Landing, KNL) many- core architecture. The Python-centered work outlined here is part of a larger effort called the NERSC Exascale Science Applications Program (NESAP) for Data. NESAP for Data focuses on applications that process and analyze high-volume, high-velocity data sets from experimental/observational science (EOS) facilities supported by the US Department of Energy Office of Science. We present three case study applications from NESAP for Data that use Python. These codes vary in terms of “Python purity” from applications developed in pure Python to ones that use Python mainly as a convenience layer for scientists without expertise in lower level programming lan- guages like C, C++ or Fortran. The science case, requirements, constraints, algorithms, and initial performance optimizations for each code are discussed. Our goal with this paper is to contribute to the larger conversation around the role of Python in high-performance computing today and tomorrow, highlighting areas for future work and emerging best practices

Ronaghi, Zahra↗
DOE OSTI2014

Damsel: A Data Model Storage Library for Exascale Science

Computational science applications have been described as having one of seven motifs (the “seven dwarfs”), each having a particular pattern of computation and communication. From a storage and I/O perspective, these applications can also be grouped into a number of data model motifs describing the way data is organized and accessed during simulation, analysis, and visualization. Major storage data models developed in the 1990s, such as Network Common Data Format (netCDF) and Hierarchical Data Format (HDF) projects, created support for more complex data models. Development of both netCDF and HDF5 was influenced by multi-dimensional dataset storage requirements, but their access models and formats were designed with sequential storage in mind (e.g., a POSIX I/O model). Although these and other high-level I/O libraries have had a beneficial impact on large parallel applications, they do not always attain a high percentage of peak I/O performance due to fundamental design limitations, and they do not address the full range of current and future computational science data models. The goal of this project is to enable exascale computational science applications to interact conveniently and efficiently with storage through abstractions that match their data models. The project consists of three major activities: (1) identifying major data model motifs in computational science applications and developing representative benchmarks; (2) developing a data model storage library, called Damsel, that supports these motifs, provides efficient storage data layouts, incorporates optimizations to enable exascale operation, and is tolerant to failures; and (3) productizing Damsel and working with computational scientists to encourage adoption of this library by the scientific community. The product of this project, Damsel library, is openly available for download from http://cucis.ece.northwestern.edu/projects/DAMSEL. Several case studies and application programming interface reference are also available to assist new users to learn to use the library.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

ASCR Workshop on Quantum Computing for Science

This report details the findings of the DOE ASCR Workshop on Quantum Computing for Science that was organized to assess the viability of quantum computing technologies to meet the computational requirements of the DOE’s science and energy mission, and to identify the potential impact of quantum technologies. The workshop was held on February 17-18, 2015, in Bethesda, MD, to solicit input from members of the quantum computing community. The workshop considered models of quantum computation and programming environments, physical science applications relevant to DOE's science mission as well as quantum simulation, and applied mathematics topics including potential quantum algorithms for linear algebra, graph theory, and machine learning. This report summarizes these perspectives into an outlook on the opportunities for quantum computing to impact problems relevant to the DOE’s mission as well as the additional research required to bring quantum computing to the point where it can have such impact.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Ultrafast Science Opportunities with Electron Microscopy

X-rays and electrons are two of the most fundamental probes of matter. When the Linac Coherent Light Source (LCLS), the world’s first x-ray free electron laser, began operation in 2009, it transformed ultrafast science with the ability to generate laser-like x-ray pulses from the manipulation of relativistic electron beams. This document describes a similar future transformation. In Transmission Electron Microscopy, ultrafast relativistic (MeV energy) electron pulses can achieve unsurpassed spatial and temporal resolution. Ultrafast temporal resolution will be the next frontier in electron microscopy and can ideally complement ultrafast x-ray science done with free electron lasers. This document describes the Grand Challenge science opportunities in chemistry, material science, physics and biology that arise from an MeV ultrafast electron diffraction & microscopy facility, especially when coupled with linac-based intense THz and X-ray pump capabilities.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2017

Plasma Sciences Exposition at APS-DPP

Plasma Sciences Expo provides an exhibition that focuses on interactive, hands-on informal science education for students at all levels, parents, teachers and the general public. DPP research students and scientists inform this audience of the wonders of science with a particular focus on fusion and plasma science. School groups attend 8:00 am to 2:00 pm and the public attends 6 to 8 pm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Testimony to the House Science Space and Technology Committee.

Chairman Smith, Ranking Member Johnson, and distinguished members of the Committee on Science, Space, and Technology, I thank you for the opportunity to testify today on the role of science, engineering, and research at Sandia National Laboratories, one of the nation’s premiere national labs and the nation’s largest Federally Funded Research and Development Center (FFRDC) laboratory. I am Dr. Susan Seestrom, Sandia’s Associate Laboratories Director for Advanced Science & Technology (AST) and Chief Research Officer (CRO). As CRO I am responsible for research strategy, Laboratory Directed Research & Development (LDRD), partnerships strategy, and technology transfer. As director and line manager for AST I manage capabilities and mission delivery across a variety of the physical and mathematical sciences and engineering disciplines, such as pulsed power, radiation effects, major environmental testing, high performance computing, and modeling and simulation.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

The International Science and Technology Center: Product of the Past or Prototype for the Future?

The International Science and Technology Center (ISTC) – originally formed in the early 1990s to address the potential issue of “brain drain” from underemployed and underpaid nuclear weapons scientists, engineers, and technicians in the former Soviet Union – still exists to this day. Through more than two decades of changing circumstances and worldviews, the ISTC has had to reorganize, move countries, streamline its internal processes, and broaden its scope of work in an attempt to remain a relevant and useful tool for international science cooperation in the 21st century. Critics see it as a product of the past in a modern world that no longer requires the redirection of former Soviet scientists, while proponents argue that the established networks and trust from the international community that the ISTC has developed throughout its history make it a critical and useful tool for current and future science cooperation and threat reduction. Through historical and budget analysis, this paper hopes to answer the following questions: (1) how has the ISTC evolved throughout its history to become what it considers to be a useful tool for the future of science cooperation and threat reduction, and (2) if the ISTC still serves a purpose, what is that purpose, and how can they continue to adapt and evolve to better serve that purpose?

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

New Science Opportunities Enabled by LCLS-II X-Ray Lasers

This document attempts to capture the most compelling new science opportunities that are enabled by the unique capabilities of the new LCLS-II X-ray laser facility, namely: soft and tender X-rays (0.25 to 5 keV) at high repetition rates (up to 1 MHz) and hard X-rays (up to 25 keV) at 120 Hz. Many compelling areas of science have been identified by the scientific community, through a series of workshops over the past several years, where LCLS-II offers the potential to significantly advance our understanding. This document is not intended to be comprehensive of all the science to be pursued at the future LCLS facility. In particular, it does not capture important ongoing science that will continue to exploit the existing capabilities of the present LCLS facility. Nevertheless, this document will help to establish a scientific foundation for the new facility (encompassing present LCLS capabilities and new LCLS-II capabilities), and will inform LCLS strategic planning and investments over the next 5-10 years. The emphasis of this document is on identifying broad scientific opportunities, elucidating their potential impact, and providing a first-order link between these opportunities and LCLS-II capabilities. Brief descriptions are provided for various experimental approaches to be used, and novel new approaches to be developed, along with select examples of required optics and instruments. However, this document is not intended to capture all the optics and instrumentation requirements. Similarly it does not provide a detailed plan for instrumentation design or for any associated research and development that might be required. Balancing the scientific opportunities and impact, with instrumentation needs, available resources, and infrastructure, will be part of the LCLS planning process which this document will help to inform.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Software-defined network for end-to-end networked science at the exascale

Domain science applications and workflow processes are currently forced to view the network as an opaque infrastructure into which they inject data and hope that it emerges at the destination with an acceptable Quality of Experience. There is little ability for applications to interact with the network to exchange information, negotiate performance parameters, discover expected performance metrics, or receive status/troubleshooting information in real time. The work presented here is motivated by a vision for a new smart network and smart application ecosystem that will provide a more deterministic and interactive environment for domain science workflows. The Software-Defined Network for End-to-end Networked Science at Exascale (SENSE) system includes a model-based architecture, implementation, and deployment which enables automated end- to-end network service instantiation across administrative domains. An intent based interface allows applications to express their high-level service requirements, an intelligent orchestrator and resource control systems allow for custom tailoring of scalability and real-time responsiveness based on individual application and infrastructure operator requirements. This allows the science applications to manage the network as a first-class schedulable resource as is the current practice for instruments, compute, and storage systems. Deployment and experiments on production networks and testbeds have validated SENSE functions and performance. Emulation based testing verified the scalability needed to support research and education infrastructures. Key contributions of this work include an architecture definition, reference implementation, and deployment. This provides the basis for further innovation of smart network services to accelerate scientific discovery in the era of big data, cloud computing, machine learning and artificial intelligence.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Science Validation for Dark Energy Research with Optical Imaging Surveys

The Universe has been expanding at an accelerating rate over the past several billion years, as though an unknown form of dark energy permeates all of space. The ultimate scientific goal of the proposed research is to distinguish between different physical mechanisms that could account for this observed accelerated expansion, for example, the zero-point energy of the vacuum, a dynamical form of energy that varies in time and/or space, or a modification to our theory of gravity. Wide- field optical imaging surveys of the night sky can test these competing models by measuring both the cosmic expansion history and the growth of large-scale structure. To this end, the Dark Energy Survey (DES) has cataloged several hundred million galaxies and thousands of supernovae. The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), will enlarge the census to billions of galaxies and hundreds of thousands of supernovae. A critical question for these dark energy experiments is whether systematic uncertainties can continue to be controlled at a level to keep pace with the statistical precision offered by such enormous datasets. The immediate research objectives of this project were (1) to prepare and validate input datasets that are the foundation of cosmological analyses with DES, and (2) to prepare for value-added characterization of Rubin Observatory commissioning data to inform early operations and accelerate the realization of dark energy science from LSST data products. For DES, we assembled and curated cosmology-ready data releases that include value-added components such as enhanced photometric and astrometric calibrations, alternative source extraction algorithms, maps of the survey coverage and survey conditions, object classifications, object quality selections, galaxy shapes, and photometric redshifts. We used the galaxy clustering technique to validate the photometric redshift distributions of various galaxy samples to be used as lenses in combined studies of galaxy clustering and weak gravitational lensing. The galaxy clustering redshift analysis was enhanced by use of a larger sample of reference galaxies from the eBOSS spectroscopic survey that extends to higher redshifts. For LSST, we prepared for science validation studies of commissioning data aimed at dark energy science capability that extend beyond the normative system-level tests to be done by the Rubin Observatory Construction Project. We identified a set of proposed survey strategies and candidate target fields that could be observed during the commissioning period to enhance science validation activities related to studies of dark energy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Towards Predictive Plasma Science and Engineering through Revolutionary Multi-Scale Algorithms and Models (Final Report)

This report describes the high-level accomplishments from the Plasma Science and Engineering Grand Challenge LDRD at Sandia National Laboratories. The Laboratory has a need to demonstrate predictive capabilities to model plasma phenomena in order to rapidly accelerate engineering development in several mission areas. The purpose of this Grand Challenge LDRD was to advance the fundamental models, methods, and algorithms along with supporting electrode science foundation to enable a revolutionary shift towards predictive plasma engineering design principles. This project integrated the SNL knowledge base in computer science, plasma physics, materials science, applied mathematics, and relevant application engineering to establish new cross-laboratory collaborations on these topics. As an initial exemplar, this project focused efforts on improving multi-scale modeling capabilities that are utilized to predict the electrical power delivery on large-scale pulsed power accelerators. Specifically, this LDRD was structured into three primary research thrusts that, when integrated, enable complex simulations of these devices: (1) the exploration of multi-scale models describing the desorption of contaminants from pulsed power electrodes, (2) the development of improved algorithms and code technologies to treat the multi-physics phenomena required to predict device performance, and (3) the creation of a rigorous verification and validation infrastructure to evaluate the codes and models across a range of challenge problems. These components were integrated into initial demonstrations of the largest simulations of multi-level vacuum power flow completed to-date, executed on the leading HPC computing machines available in the NNSA complex today. These preliminary studies indicate relevant pulsed power engineering design simulations can now be completed in (of order) several days, a significant improvement over pre-LDRD levels of performance.

42 ENGINEERING↗