Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Advanced Computing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

The Global Diffusion of Societal Verification Tools: A Quantitative Assessment of the Public’s Ability to Engage Nonproliferation Treaty Monitoring

The spread of nuclear and dual-use technologies and the need for more robust, effective and efficient nonproliferation and arms control treaties has led to an increasing need for innovative verification approaches and technologies. This need, paired with advancements in online computing, mobile devices, commercially available satellite imagery and the evolution of online social networks, has led to a resurgence of the concept of societal verification for arms control and nonproliferation treaties. In the event a country accepts its citizens’ assistance in supporting transparency, confidence-building and societal verification, the host government will need a population that is willing and able to participate. While scholarly interest in societal verification continues to grow, social scientific research on the topic is lacking. The aim of this paper is to begin the process of understanding public societal verification capabilities, extend the availability of quantitative research on societal verification and set in motion complementary research to increase the breadth and depth of knowledge on this topic. This paper presents a potential framework and outlines a research roadmap for the development of such a societal verification capability index.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2019

Methyl Ketone Condensation over Tailored Metal Oxides

Methyl ketones represent promising oxygenate intermediates that can be derived from lignocellulosic biomass via numerous conversion routes and subsequently coupled to produce precursors for renewable diesel and aviation fuels. Basic metal oxides are known to promote ketone coupling via condensation reactions, with magnesium oxide (MgO) providing an ideal catalytic system for evaluating the reaction mechanism and role of water on observed activity. Recent studies demonstrate that the MgO(111) surface facet can be promoted to enhance activity for base catalyzed reactions; however, to our knowledge, there is a dearth of information regarding the impact of MgO(111) faceting and surface termination under reaction conditions for ketone coupling. Therefore, this talk will discuss our recent investigation into the catalytic coupling of methyl ketones over MgO(100) and MgO(111) catalysts. Results will be presented that address the synthesis and detailed characterization of MgO(111) nanosheets, as well as their activity and selectivity for ketone coupling when compared to MgO(100). The impact of water on MgO surface termination will be discussed, as well as a proposed reaction mechanism for ketone condensation over clean and hydroxyl terminated surfaces for both facets. Findings will include outcomes from experimental studies, computational modeling, and advanced surface characterization by neutron scattering. Collectively, this work provides further insight into the role of tailored metal oxide catalysts for this important class of biomass conversion chemistry.

09 BIOMASS FUELS↗
DOE OSTI2020

The Superconducting Quantum Materials and Systems Center at Fermilab

The Superconducting Quantum Materials and Systems Center, or SQMS, led by Fermilab, brings together national laboratories, academia and industry to make revolutionary advances in quantum computing and sensing, including the building and deployment of a beyond-the-state-of-the-art quantum computer. The quantum devices developed at SQMS will have game-changing impacts in basic science and in our everyday lives.

Fermilab, Fermilab↗
DOE OSTI2013

Benchmark for evaluation and validation of reactor simulations (BEAVRS)

Advances in parallel computing have made possible the development of high-fidelity tools for the design and analysis of nuclear reactor cores, and such tools require extensive verification and validation. This paper introduces BEAVRS, a new multi-cycle full-core Pressurized Water Reactor (PWR) depletion benchmark based on two operational cycles of a commercial nuclear power plant that provides a detailed description of fuel assemblies, burnable absorbers, in-core fission detectors, core loading patterns, and numerous in-vessel components. This benchmark enables analysts to develop extremely detailed reactor core models that can be used for testing and validation of coupled neutron transport, thermal-hydraulics, and fuel isotopic depletion. The benchmark also provides measured reactor data for Hot Zero Power (HZP) physics tests, boron letdown curves, and three-dimensional in-core flux maps from fifty-eight instrumented assemblies. Initial comparisons between calculations performed with MIT's OpenMC Monte Carlo neutron transport code and measured cycle 1 HZP test data are presented, and these results display an average deviation of approximately 100 pcm for the various critical configurations and control rod worth measurements. Computed HZP radial fission detector flux maps also agree reasonably well with the available measured data. All results indicate that this benchmark will be extremely useful in validation of coupled-physics codes and uncertainty quantification of in-core physics computational predictions. The detailed BEAVRS specification and its associated data package is hosted online at the MIT Computational Reactor Physics Group web site (http://crpg.mit.edu/), where future revisions and refinements to the benchmark specification will be made publicly available. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Comparison of dose measurements in CT using a novel semiconductor detector and a small ion chamber

The advance of multislice computed tomography (CT) has become inadequate the currently dosimetric protocol used in CT. Instead of dosimetry based on the measurement of CTDI using a pencil ion chamber of 100 m of length, it was proposed the use of a small ion chamber (IC) and the calculating the dose equilibrium (Deq) at the location of the chamber. The objective of this work was to compare the performance of a short IC and a commercial photodiode to measure the accumulated dose at the center of the scan length L, DL(0), and to obtain the equilibrium dose Deq using the two detectors. The result for L=100 mm was compared with the result of a pencil chamber. The results indicate that the commercial photodiode is suitable to measure the accumulated dose at the center of the scan length L as compared with the ion chambers. This methodology allows measurements of the accumulated dose for any desired scan length, allowing measuring the equilibrium dose Deq if the phantom is long enough to allow it. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Plant science decadal vision 2020–2030: Reimagining the potential of plants for a healthy and sustainable future

Abstract Plants, and the biological systems around them, are key to the future health of the planet and its inhabitants. The Plant Science Decadal Vision 2020–2030 frames our ability to perform vital and far‐reaching research in plant systems sciences, essential to how we value participants and apply emerging technologies. We outline a comprehensive vision for addressing some of our most pressing global problems through discovery, practical applications, and education. The Decadal Vision was developed by the participants at the Plant Summit 2019, a community event organized by the Plant Science Research Network. The Decadal Vision describes a holistic vision for the next decade of plant science that blends recommendations for research, people, and technology. Going beyond discoveries and applications, we, the plant science community, must implement bold, innovative changes to research cultures and training paradigms in this era of automation, virtualization, and the looming shadow of climate change. Our vision and hopes for the next decade are encapsulated in the phrase reimagining the potential of plants for a healthy and sustainable future. The Decadal Vision recognizes the vital intersection of human and scientific elements and demands an integrated implementation of strategies for research (Goals 1–4), people (Goals 5 and 6), and technology (Goals 7 and 8). This report is intended to help inspire and guide the research community, scientific societies, federal funding agencies, private philanthropies, corporations, educators, entrepreneurs, and early career researchers over the next 10 years. The research encompass experimental and computational approaches to understanding and predicting ecosystem behavior; novel production systems for food, feed, and fiber with greater crop diversity, efficiency, productivity, and resilience that improve ecosystem health; approaches to realize the potential for advances in nutrition, discovery and engineering of plant‐based medicines, and "green infrastructure." Launching the Transparent Plant will use experimental and computational approaches to break down the phytobiome into a "parts store" that supports tinkering and supports query, prediction, and rapid‐response problem solving. Equity, diversity, and inclusion are indispensable cornerstones of realizing our vision. We make recommendations around funding and systems that support customized professional development. Plant systems are frequently taken for granted therefore we make recommendations to improve plant awareness and community science programs to increase understanding of scientific research. We prioritize emerging technologies, focusing on non‐invasive imaging, sensors, and plug‐and‐play portable lab technologies, coupled with enabling computational advances. Plant systems science will benefit from data management and future advances in automation, machine learning, natural language processing, and artificial intelligence‐assisted data integration, pattern identification, and decision making. Implementation of this vision will transform plant systems science and ripple outwards through society and across the globe. Beyond deepening our biological understanding, we envision entirely new applications. We further anticipate a wave of diversification of plant systems practitioners while stimulating community engagement, underpinning increasing entrepreneurship. This surge of engagement and knowledge will help satisfy and stoke people's natural curiosity about the future, and their desire to prepare for it, as they seek fuller information about food, health, climate and ecological systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Exascale Operating Systems and Runtime Software Report

Here U.S. Department of Energy (DOE) workshops and reports have identified four key exascale challenges: dramatically improving power efficiency; improving resilience in the presence of increasing faults; enabling efficient data movement across deepening memory hierarchies and new storage technologies; and managing dramatically increased parallelism, especially at the node level. Software solutions that address these challenges must also improve programmability, expanding the community of computational scientists who can use leadership-class platforms. To address these challenges, DOE must develop new techniques, novel designs, and advanced software architectures for next-generation exascale software infrastructure. In this report, we discuss challenges and approaches to exascale operating system and runtime (OS/R) software. The Exascale Operating Systems and Runtime (OS/R) Software Technical Council canvassed hardware architects, application programmers, parallel tool developers, DOE high-performance computing (HPC) facilities, and the vendors that sell and support integrated platforms. After considering the collective requirements of these constituents and examining the future research challenges and current software gaps, the council recommends that DOE invest in targeted advanced computer science research and in specific coordinating activities to enable the effective and successful development of anticipated exascale systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Computer Science Research Institute (CSRI) Summer Proceedings 2013

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia National Laboratories for focused collaborative research on computer science, computational science, and mathematics problems that are critical to the mission of the laboratories, the Department of Energy, and the United States. The CSRI provides a mechanism by which university researchers learn about and impact national— and global—scale problems while simultaneously bringing new ideas from the academic research community to bear on these important problems. A key component of CSRI programs over the last decade has been an active and productive summer program where students from around the country conduct internships at CSRI. Each student is paired with a Sandia staff member who serves as technical advisor and mentor. The goals of the summer program are to expose the students to research in mathematical and computer sciences at Sandia and to conduct a meaningful and impactful summer research project with their Sandia mentor. Every effort is made to align summer projects with the student's research objectives and all work is coordinated with the ongoing research activities of the Sandia mentor in alignment with Sandia technical thrusts. For the 2013 CSRI Proceedings, research articles have been organized into the following broad technical focus areas — Computational Mathematics and Algorithms, Combinatorial Algorithms and Visualization, Advanced Architectures and Systems Software, Computational Applications — which are well aligned with Sandia's strategic thrusts in computer and information sciences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

COLUMBUS─An Efficient and General Program Package for Ground and Excited State Computations Including Spin–Orbit Couplings and Dynamics

The COLUMBUS program system provides the tools for performing high-level multireference (MR) computations, including the multireference configuration interaction (MRCI) method and its multireference averaged quadratic coupled cluster (MR-AQCC) extension, allowing computations on a wide range of fascinating atomic and molecular systems, including the treatment of open-shells and complicated excited state phenomena. The inclusion of spin−orbit coupling (SOC) directly within the MRCI step enables the description of systems containing heavy elements, such as lanthanides and actinides, whose properties are strongly influenced by SOC. Analytic energy gradients and nonadiabatic couplings at the correlated MRCI level provide the foundation for a variety of dynamics studies, giving insight into ultrafast photochemistry. New and ongoing method developments in COLUMBUS include the computation of spin densities, improved descriptions of ionic states, enhancements to the AQCC method, and the porting of COLUMBUS to graphical processing units (GPUs). New external interfaces enable an enhanced description of electronic resonances and molecules in strong laser fields. This work highlights these new developments while providing a detailed account of the diverse applications of COLUMBUS in recent years.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Determination of Molecular Structure and Dynamics of Molten Salts by Advanced Neutron and X-ray Scattering Measurements and Computer Modeling

The design and development of fully functional Molten-Salt Reactors (MSR) require detailed knowledge of the molten salt properties in order to understand and predict the salt’s behavior. Fundamental properties of interest include molecular structure, speciation, and dynamics (such as diffusion coefficients) of salt components and dissolved corrosion and fission products. Computer modeling is necessary to predict changes in physical and chemical properties due to irradiation, burning of dissolved fuel, and corrosion. The modeling requires experimental data, and advanced neutron and x-ray scattering and spectroscopy provide the most reliable and direct determination of the structure (Pair-Distribution Functions, PDF), and dynamics of ions in the melt. This project dealt with both fluoride and chloride salts. The PDFs have been measured by a combination of neutron and x-ray diffraction. We utilized the techniques of isotope substitutions, a very powerful tool available for neutron-scattering, to extract the details of the liquid structure. Although similar measurements have been done before, modern advanced neutron and x-ray-scattering techniques allow collecting the data at much higher resolution and in a wider range of temperatures. Importantly, we were among the first to study fluoride salts by neutron scattering. The importance of impurities and their effects on salt properties have become apparent recently and so new methods of salt purification were developed. We took advantage of these developments to produce reliable data, which have been used for computer simulations of both clean salts and those with added fission and corrosion products most relevant for MSRs. Ab initio molecular dynamics simulations have been performed to understand the multi-component liquid solution, in particular solubility of impurities and thermodynamic interactions in relation to the ionic-cluster structure of the fluid. We applied machine learning to regress from the simulation and experimental data in order to develop a fast-acting model that can handle molten salt with an arbitrary (≥ 10) number of chemical elements and be able to predict chemical potential as a function of composition and temperature. This project resulted in a number of experimental and computer-simulation publications, a patent application, and numerous conference presentations (American Physical Society, American Chemical Society, and The Electrochemical Society among others). Multiple students and postdocs participated and collaborated on aspects of this project. This project seeded new collaborations between MIT and other institutions, such as the University of Massachusetts Lowell, the University of Illinois Urbana-Champaign, the University of California Berkeley, and Oak Ridge and Los Alamos National Labs. As such, this project has had a broad and lasting impact beyond its original scientific scope.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Workshop on Manufacturing and Integration Challenges for Analog and Neuromorphic Computing

The U.S. Department of Energy’s (DOE’s) Advanced Manufacturing Office (AMO) held its third virtual workshop on Semiconductor R&D for Energy Efficiency on August 11-13, 2021. This public workshop – titled “Manufacturing and Integration Challenges for Analog and Neuromorphic Computing” – brought together more than 180 leading scientific and technical experts to identify challenges and opportunities to improve manufacturing capabilities for analog and neuromorphic computing architectures to significantly increase energy efficiency of microelectronic devices. The workshop featured perspectives of researchers from national laboratories, universities, government agencies, and industry with expertise in novel and emerging devices, processes, and metrology and characterization. This workshop is intended to inform an AMO research, development, demonstration, and deployment (RDD&D) plan to significantly reduce semiconductor energy use by 2030. It was co-sponsored by the Semiconductor Research Corporation (SRC) and the DOE Office of Science’s Advanced Scientific Computing Research (ASCR).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Intro to HPC Bootcamp: Engaging New Communities Through Energy Justice Projects

The U.S. Department of Energy (DOE) is a long-standing leader in research and development of high-performance computing (HPC) in the pursuit of science. However, we face daunting challenges in fostering a robust and diverse HPC workforce. Basic HPC is not typically taught at early stages of students' academic careers, and the capacity and knowledge of HPC at many institutions are limited. Even so, such topics are prerequisites for advanced training programs, internships, graduate school, and ultimately for careers in HPC. To help address this challenge, as part of the DOE Exascale Computing Project's Broadening Participation Initiative, we recently launched the Introduction to HPC Training and Workforce Pipeline Program to provide accessible introductory material on HPC, scalable AI, and analytics. We describe the Intro to HPC Bootcamp, an immersive program designed to engage students from underrepresented groups as they learn foundational HPC skills. Here, the program takes a novel approach to HPC training by turning the traditional curriculum upside down. Instead of focusing on technology and its applications, the bootcamp focuses on energy justice to motivate the training of HPC skills through project-based pedagogy and real-life science stories. Additionally, the bootcamp prepares students for internships and future careers at DOE labs. The first bootcamp, hosted by the advanced computing facilities at Argonne, Lawrence Berkeley, and Oak Ridge National Labs and organized by Sustainable Horizons Institute, took place in August 2023.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2014

Advanced Test Reactor Core Modeling Update Project: Annual Report for Fiscal Year 2014

Legacy computational reactor physics software tools and protocols currently used for support of Advanced Test Reactor (ATR) core fuel management and safety assurance, and to some extent, experiment management, are inconsistent with the state of modern nuclear engineering practice, and are difficult, if not impossible, to verify and validate (V&V) according to modern standards. Furthermore, the legacy staff knowledge required for effective application of these tools and protocols from the 1960s and 1970s is rapidly being lost due to staff turnover and retirements. In late 2009, the Idaho National Laboratory (INL) initiated a focused effort, the ATR Core Modeling Update Project, to address this situation through the introduction of modern high-fidelity transport theory based computational software and models to replace the legacy methods, with appropriate verification and validation (V&V) protocols according to applicable national standards. The project has now completed its fifth, and last, full year of development activity, and has entered an accelerated deployment phase that is expected to run through 2015.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2011

An Advanced Framework for Improving Situational Awareness in Electric Power Grid Operation

With the deployment of new smart grid technologies and the penetration of renewable energy in power systems, significant uncertainty and variability is being introduced into power grid operation. Traditionally, the Energy Management System (EMS) operates the power grid in a deterministic mode, and thus will not be sufficient for the future control center in a stochastic environment with faster dynamics. One of the main challenges is to improve situational awareness. This paper reviews the current status of power grid operation and presents a vision of improving wide-area situational awareness for a future control center. An advanced framework, consisting of parallel state estimation, state prediction, parallel contingency selection, parallel contingency analysis, and advanced visual analytics, is proposed to provide capabilities needed for better decision support by utilizing high performance computing (HPC) techniques and advanced visual analytic techniques. Research results are presented to support the proposed vision and framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Recent advances, and unresolved issues, in the application of computational modelling to the prediction of the biological effects of nanomaterials

Nanomaterials research is one of the fastest growing contemporary research areas. The unprecedented properties of these materials have meant that they are being incorporated into products very quickly. Regulatory agencies are concerned they cannot assess the potential hazards of these materials adequately, as data on the biological properties of nanomaterials are still relatively limited and expensive to acquire. Computational modelling methods have much to offer in helping understand the mechanisms by which toxicity may occur, and in predicting the likelihood of adverse biological impacts of materials not yet tested experimentally. This paper reviews the progress these methods, particularly those QSAR-based, have made in understanding and predicting potentially adverse biological effects of nanomaterials, and also the limitations and pitfalls of these methods. - Highlights: • Nanomaterials regulators need good information to make good decisions. • Nanomaterials and their interactions with biology are very complex. • Computational methods use existing data to predict properties of new nanomaterials. • Statistical, data driven modelling methods have been successfully applied to this task. • Much more must be learnt before robust toolkits will be widely usable by regulators.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Incubating advances in integrated photonics with emerging sensing and computational capabilities

As photonic technologies grow in multidimensional aspects, integrated photonics holds a unique position and continuously presents enormous possibilities for research communities. Applications include data centers, environmental monitoring, medical diagnosis, and highly compact communication components, with further possibilities continuously growing. Herein, we review state-of-the-art integrated photonic on-chip sensors that operate in the visible to mid-infrared wavelength region on various material platforms. Among the different materials, architectures, and technologies leading the way for on-chip sensors, we discuss the optical sensing principles that are commonly applied to biochemical and gas sensing. Our focus is on passive optical waveguides, including dispersion-engineered metamaterial-based structures, which are essential for enhancing the interaction between light and analytes in chip-scale sensors. We harness a diverse array of cutting-edge sensing technologies, heralding a revolutionary on-chip sensing paradigm. Our arsenal includes refractive-index-based sensing, plasmonics, and spectroscopy, which forge an unparalleled foundation for innovation and precision. Furthermore, we include a brief discussion of recent trends and computational concepts, incorporating Artificial Intelligence & Machine Learning (AI/ML) and deep learning approaches over the past few years to improve the qualitative and quantitative analysis of sensor measurements.

Jain, Sourabh (ORCID:0000000279923275)↗