Improving Performance of Sampling-Based Uncertainty Quantification on Advanced Computing Architectures Through Embedded Ensemble Propagation.
Abstract not provided.
Phipps, Eric Todd↗
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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.
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Computational Advances and Data Analytics to Reduce Subsurface Uncertainty
Presented by NETL at ARMA, 6/16
Rose, Kelly K.↗
Advanced computational procedures for the understanding of agricultural processes
Explore the source record for details and available documents.
Kalra, N↗
Advanced Computing for Automated and Connected Vehicles -- a primer.
Abstract not provided.
Moen, Christopher D.↗
Advanced Computing for CAV Presentations to Automotive Industry.
Abstract not provided.
Moen, Christopher D.↗
Advanced Computational Accident Scenario Modeling for Safety Margin Economic Analysis
The intent of this research is to establish a new tool in the Risk Informed Safety Margin Characterization (RISMC) tool-kit for the fiscal analysis of potential power plant upgrades. This is being done by providing proof-of-concept of the Safety Margin Economic Evaluation (SMEE) methodology of performing cost-benefit analyses of potential Nuclear Power Plant (NPP) upgrades to allow for more data-driven decision making with regards to nuclear safety. To this end, the RAVEN code developed by the Idaho National Laboratory is being used to perform a cost-benefit analysis of several potential power plant safety upgrades to compare the material cost of the upgrades with the probabilistic benefit of avoiding accident scenario consequences to find the most cost effective safety upgrades. Additionally, the MELCOR and MACCS2 codes developed by the Sandia National Laboratory are being used for accident scenario modeling. Evaluating potential NPP upgrades is concluded by doing a detailed cost-benefit analysis of the upgrades. The cost of the upgrade is the direct material cost of implementing, maintaining, and operating the upgrade at an NPP for the projected duration of its lifetime. The benefit of the upgrade is more complex, and is essentially the Risk avoided, where Risk is defined as Consequences multiplied by Probability. Here, Consequences is the economic impact of a severe accident and/or nuclear release and Probability is the likelihood that an NPP upgrade will prevent or mitigate a severe accident, reducing or even eliminating its Consequences. (authors)
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Radiation Mapping at JET and ITER using advanced computational acceleration techniques and tools - Paper 63
The Applied Radiation Physics group at the Culham Centre for Fusion Energy (CCFE) have developed and applied state-of-the-art radiation mapping methods and tools to enable complex shielding calculations in fusion devices during plasma operations, and associated maintenance in the device and surrounding areas. Here, we present the description and application of those tools to produce radiation maps both to support the JET safety case (the EU experimental tokamak device based at Culham) and the planned DT campaign in the next few years; and the ITER device. Radiation mapping of fusion facilities are essential for assessing radiation hardness of electronics during operations, and to define safe working dose limits to staff during routine maintenance. At CCFE the Monte Carlo radiation transport code MCNP6 is one of the codes used to perform radiation transport calculations. Due to the size and complexity of the JET and ITER devices, and their surrounding buildings, a suite of tools have been created at CCFE to reduce the computational requirements of the calculations. This paper describes three of these tools, which have been developed and applied to nuclear and radiological field mapping in fusion devices. The results presented in this paper highlight the application of three methods that have been used to improve the computational efficiency and capabilities for radiation mapping in fusion devices such as JET and ITER. These methods are Global Variance Reduction, the Surface Source Mesh routine and the Smeared Source routine. This paper demonstrates the three techniques used in combination, enabling a very computationally challenging fusion problem to become tractable (with acceptable computing effort), also enabling improved capability to allow the mapping of radiations fields during transport operations for activated materials. (authors)
61 RADIATION PROTECTION AND DOSIMETRY↗
Advanced Computational Modeling of High-Level Waste Vitrification at the Hanford Site
The U.S. Department of Energy (DOE) has selected vitrification for stabilizing legacy tank waste at the Hanford site, where radioactive waste from plutonium production was historically stored in underground tanks. This waste will be separated into low-activity waste (LAW) and high-level waste (HLW) fractions and processed at the Waste Treatment and Immobilization Plant (WTP). At WTP, glass melters are used for the vitrification of radioactive tank waste, transforming it into a stable borosilicate glass form for safe long-term storage. The melter vessel is constructed from highly durable and heat-resistant materials, where the vitrification process occurs. The main regions that are modeled are the melt pool, plenum, cold cap, riser/discharge chamber, and surrounding structure with insulation layers. Forced convection induced by air bubblers at the base of the melter ensure uniform temperature distribution and provide heat to the cold cap layer. The cold cap is a region of reacting batch feed that floats on top of the molten glass and is where the batch-to-glass reactions occur. Joule heating provided by electrodes mounted along the vertical walls of the melter and immersed directly in the glass, generates the necessary heat for the net endothermic conversion processes that occur in the cold cap. The high temperatures, radioactivity, and opaque nature of the glass prevent direct observation inside the melters. Therefore, computational models are essential for providing insight into factors that affect melter throughput. Thermocouples in the plenum provide operators with plenum temperature measurements. Operational adjustments include bubbling rate, voltage supplied to the electrodes, feed adjustments, and glass removal rate. Different computational fluid dynamics (CFD) models have been developed, each serving a specific purpose. There are CFD models of different scale melters, as well as models that capture the two-phase flow interfaces of rising bubbles in the molten glass or models with a simplified molten glass region so that the surrounding structure and plenum can be feasibly incorporated. Pilot-scale melter models have been developed to serve as validation of the methods employed in the simulation of the full-scale WTP melters. Models incorporating resolved bubbling are used to develop momentum source terms to implement into a single phase, multi-region, steady-state flow model that is being validated by measured process parameters such as glass production rate, voltage, input power, plenum temperatures, etc. The resolved bubbling model uses the multiphase volume of fluid approach to model the system with a high-resolution interface capturing scheme to maintain sharp interfaces between the molten glass and the air phase. The suite of CFD models is continually being improved to incorporate more realistic physics and achieve faster turnaround time. For example, an incremental controller is implemented to automatically adjust electrode voltage within the simulation to a molten glass set point temperature of 1150°C. Newer models feature improved meshes to ensure conformal meshes between regions and eliminate unnecessary mesh refinement in areas that are not of interest (such as boundary layers in offgas ports). Instead of explicitly modeling the structural, refractory, and insulation layers of the melter, a thermal resistance approach is used with published correlations used for boundary conditions. The development of robust and efficient CFD models will be instrumental in enabling the WTP to successfully fulfill its mission of safely stabilizing legacy nuclear waste.
12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗
High Performance Computing Modeling Advances Accelerator Science for High-Energy Physics
The development and optimization of particle accelerators are essential for advancing our understanding of the properties of matter, energy, space, and time. Particle accelerators are complex devices whose behavior involves many physical effects on multiple scales. Therefore, advanced computational tools utilizing high-performance computing are essential for accurately modeling them. In the past decade, the US Department of Energy's SciDAC program has produced accelerator-modeling tools that have been employed to tackle some of the most difficult accelerator science problems. The authors discuss the Synergia framework and its applications to high-intensity particle accelerator physics. Synergia is an accelerator simulation package capable of handling the entire spectrum of beam dynamics simulations. Our authors present Synergia's design principles and its performance on HPC platforms.
43 PARTICLE ACCELERATORS↗
Computations for Advanced Nuclear Fuels
The objective of the project was to develop advanced computational techniques to improve the understanding of fission gas distribution and heat transfer in solid fuel under normal and accident conditions. To successfully implement an efficient and effective nuclear power strategy, it is essential to develop new fuels that can provide optimal performance over long periods of time. In this project, our aims were to make progress towards replacement of the empirical models used in existing fuel performance codes. Our specific objectives have been to develop understandings of phonon and molecular transport in nuclear fuels using both analysis and simulations. While we made progress in both the phonon and molecular transport areas, as the research progressed we concentrated much more on the first area. The challenges here alone turned out to be substantial. We explored a number of areas including full Chapman-Enskog solutions for the Phonon transport equation. After very considerable effort, we came to believe that some of the results reported in the literature cannot be viewed as converged, and substantial effort beyond what we could accomplish in the time frame we had will be needed to improve the results. We therefore focused on what was achievable and still useful, and we describe these efforts and results below.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Spectral Advanced Radiological Computer System
Advanced SPARCS Training Workshop in Chile April 9-12, 2018
61 RADIATION PROTECTION AND DOSIMETRY↗
Advances in the computation of the Sjöstrand, Rossi, and Feynman distributions
This study illustrates recent computational advances in the application of the Sjöstrand (area), Rossi, and Feynman methods to estimate the effective multiplication factor of a subcritical system driven by an external neutron source. The methodologies introduced in this study have been validated with the experimental results from the KUKA facility of Japan by Monte Carlo (MCNP6 and MCNPX) and deterministic (ERANOS, VARIANT, and PARTISN) codes. When the assembly is driven by a pulsed neutron source generated by a particle accelerator and delayed neutrons are at equilibrium, the Sjöstrand method becomes extremely fast if the integral of the reaction rate from a single pulse is split into two parts. These two integrals distinguish between the neutron counts during and after the pulse period. To conclude, when the facility is driven by a spontaneous fission neutron source, the timestamps of the detector neutron counts can be obtained up to the nanosecond precision using MCNP6, which allows obtaining the Rossi and Feynman distributions.
97 MATHEMATICS AND COMPUTING↗
Advanced Scientific Computing Research Exascale Requirements Review. An Office of Science review sponsored by Advanced Scientific Computing Research, September 27-29, 2016, Rockville, Maryland
The widespread use of computing in the American economy would not be possible without a thoughtful, exploratory research and development (R&D) community pushing the performance edge of operating systems, computer languages, and software libraries. These are the tools and building blocks — the hammers, chisels, bricks, and mortar — of the smartphone, the cloud, and the computing services on which we rely. Engineers and scientists need ever-more specialized computing tools to discover new material properties for manufacturing, make energy generation safer and more efficient, and provide insight into the fundamentals of the universe, for example. The research division of the U.S. Department of Energy’s (DOE’s) Office of Advanced Scientific Computing and Research (ASCR Research) ensures that these tools and building blocks are being developed and honed to meet the extreme needs of modern science. See also http://exascaleage.org/ascr/ for additional information.
97 MATHEMATICS AND COMPUTING↗
The role of quantum computing in advancing scientific high-performance computing: A perspective from the ADAC institute
Quantum computing (QC) has gained significant attention over the past two decades due to its potential for speeding up classically demanding tasks. This transition from an academic focus to a thriving commercial sector is reflected in substantial global investments. While advancements in qubit counts and functionalities continue at a rapid pace, current quantum systems still lack the scalability for practical applications, facing challenges such as too high error rates and limited coherence times. Here, this perspective paper examines the relationship between QC and high-performance computing (HPC), highlighting their complementary roles in enhancing computational efficiency. It is widely acknowledged that even fully error-corrected QC will not be suited for all computational tasks. Rather, future compute infrastructures are anticipated to employ quantum acceleration within hybrid systems that integrate HPC and QC. While QC can enhance classical computing, traditional HPC remains essential for maximizing quantum acceleration. This integration is a priority for supercomputing centers and companies, sparking innovation to address the challenges of merging these technologies. The novelty of this work lies in its unique perspective, reflecting the collective insights of the Accelerated Data Analytics and Computing (ADAC) Institute, a global consortium of over 20 leading HPC centers. Recognizing the growing importance of QC, ADAC established a Quantum Computing Working Group in 2023 to foster collaboration and knowledge-sharing among its members. This paper synthesizes insights from the group’s collaborative efforts and incorporates findings from a member survey that captures shared experiences, ongoing projects, and strategic directions. By outlining the current landscape and challenges of QC integration into HPC ecosystems, this work offers HPC specialists practical and forward-looking guidance on the opportunities and implications of QC in computationally intensive endeavors.
Accelerated Data Analytics and↗
Synergistic Challenges in Data-Intensive Science and Exascale Computing. Summary report of the Advanced Scientific Computing Advisory Committee (ASCAC) Subcommittee, March 2013
The ASCAC Subcommittee on Synergistic Challenges in Data-Intensive Science and Exascale Computing has reviewed current practice and future plans in multiple science domains in the context of the challenges facing both Big Data and the Exascale Computing. challenges. The review drew from public presentations, workshop reports and expert testimony. Data-intensive research activities are increasing in all domains of science, and exascale computing is a key enabler of these activities. We briefly summarize below the key findings and recommendations from this report from the perspective of identifying investments that are most likely to positively impact both data-intensive science goals and exascale computing goals.
97 MATHEMATICS AND COMPUTING↗
A comparison of Amazon Web Services and Microsoft Azure cloud platforms for high performance computing
Advances in commercial cloud computing necessitate continual evaluation of the cloud's performance on a variety of applications. This work looks at compute oriented instances from Amazon Web Services and Microsoft Azure cloud platforms and evaluates them with several high-performance computing benchmarks, including HPCC and HPCG. These benchmarks illustrate that the most cost competitive solution depends on the application to be run.
Kotas, Charlotte↗
Nuclear Physics Exascale Requirements Review: An Office of Science Review sponsored jointly by Advanced Scientific Computing Research and Nuclear Physics, June 15 - 17, 2016, Gaithersburg, Maryland
Imagine being able to predict — with unprecedented accuracy and precision — the structure of the proton and neutron, and the forces between them, directly from the dynamics of quarks and gluons, and then using this information in calculations of the structure and reactions of atomic nuclei and of the properties of dense neutron stars (NSs). Also imagine discovering new and exotic states of matter, and new laws of nature, by being able to collect more experimental data than we dream possible today, analyzing it in real time to feed back into an experiment, and curating the data with full tracking capabilities and with fully distributed data mining capabilities. Making this vision a reality would improve basic scientific understanding, enabling us to precisely calculate, for example, the spectrum of gravity waves emitted during NS coalescence, and would have important societal applications in nuclear energy research, stockpile stewardship, and other areas. This review presents the components and characteristics of the exascale computing ecosystems necessary to realize this vision.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Future High Performance Computing Capabilities: Summary Report of the Advanced Scientific Computing Advisory Committee (ASCAC) Subcommittee
The ASCAC Subcommittee on Future High Performance Computing (HPC) Capabilities has reviewed opportunities and challenges related to the most promising technologies that are currently planned for the post-exascale (2020's) and post-Moore (2030's and beyond) timeframes. We briefly summarize in this report the key findings and recommendations from this review, from the perspective of planning and research directions that need to be given priority to prepare for the very significant challenges that await us in the post-Moore computing era. An overarching concern that emerged from the subcommittee's deliberations is that DOE has lost considerable momentum in funding and sustaining a research pipeline in the applied math and computer science areas that should have been the "seed corn" for preparing for these future challenges, and it is therefore critical to correct this gap as soon as possible. While the subcommittee understands the paramount importance of DOE's commitment to deliver exascale capabilities, we believe that it is essential for DOE ASCR to fund research and development that looks beyond the Exascale Computing Project (ECP) horizon so as to ensure our nation's continued leadership in HPC and we were glad to learn about the ASCAC exascale transition subcommittee in this regard.
97 MATHEMATICS AND COMPUTING↗