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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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Performing Consequence Analysis for Multi-Unit/Spent Fuel Pool Source Terms.
Abstract not provided.
Sensitivity Analysis in Performance Assessment: Towards a Joint Approach.
Abstract not provided.
Sandia HPC cluster performance monitoring analysis & visualization.
Abstract not provided.
Sensitivity Analysis in Performance Assessment: Towards a Joint Approach.
Abstract not provided.
Nonlinear analysis and performance of energy harvesting absorbers with stoppers for controlling fluid-induced vibrations of dynamical systems.
Abstract not provided.
A Tool for Performing Link Analysis, Operational Sequence Analysis, and Workload Analysis to Support Nuclear Power Plant Control Room Modernization
Nuclear power continues to have an imperative role for the U.S.’s electricity generation. However, for these nuclear power plants (NPPs) to remain economically viable, new strategies for reducing operations and maintenance costs must be explored. The U.S. Department of Energy Light Water Reactor Sustainability Program is researching how to digitally transform existing analog and hybrid main control rooms into a fully integrated control room that addresses this challenge. The transformation will fundamentally change the conduct of operations for these U.S. NPPs. Human factors engineering has a vital role in this effort, where traditional task analysis methods are important in informing the design of advanced human-system interface displays. This work describes a preliminary tool to support task analysis for the development of these advanced displays. Details on the use of this tool, including the specific task analysis methods offered, are presented in this paper.
MC performance study for an early $v_μ$ charged-current inclusive analysis with MicroBooNE
This note describes an analysis performed on Monte Carlo data to evaluate the sensitivity of MicroBooNE for an early ν µ charged-current inclusive cross section measurement. Such an analysis is intended to be done using the first three months of Booster Neutrino Beam data. The event selection is entirely based on an automated event reconstruction. The Monte Carlo prediction for a flux-integrated and single differential cross section measurement with an approximate estimation of statistical and systematic uncertainties for the MicroBooNE detector as designed is presented. This allows the comparison of the sensitivity of MicroBooNE to theory and other experiments.
Measurement and analysis of GPU-accelerated applications with HPCToolkit
To address the challenge of performance analysis on the US DOE’s forthcoming exascale supercomputers, Rice University has been extending its HPCToolkit performance tools to support measurement and analysis of GPU-accelerated applications. To help developers understand the performance of accelerated applications as a whole, HPCToolkit’s measurement and analysis tools attribute metrics to calling contexts that span both CPUs and GPUs. To measure GPU-accelerated applications efficiently, HPCToolkit employs a novel wait-free data structure to coordinate monitoring and attribution of GPU performance. To help developers understand the performance of complex GPU code generated from high-level programming models, HPCToolkit constructs sophisticated approximations of call path profiles for GPU computations. To support fine-grained analysis and tuning, HPCToolkit uses PC sampling and instrumentation to measure and attribute GPU performance metrics to source lines, loops, and inlined code. To supplement fine-grained measurements, HPCToolkit can measure GPU kernel executions using hardware performance counters. To provide a view of how an execution evolves over time, HPCToolkit can collect, analyze, and visualize call path traces within and across nodes. Finally, on NVIDIA GPUs, HPCToolkit can derive and attribute a collection of useful performance metrics based on measurements using GPU PC samples. Here, we illustrate HPCToolkit’s new capabilities for analyzing GPU-accelerated applications with several codes developed as part of the Exascale Computing Project.
Neutronics Analysis for ITER Diagnostic Generic Upper Port Plug
This paper presents new results of neutronics analysis performed for the updated design of the ITER Diagnostic Generic Upper Port Plug (DGUPP). Such analysis is performed regularly during the development of the ITER Ports design. Neutronics analysis is an important step in support of the development of ITER components irradiated by 14 MeV neutrons generated in D-T fusion thermonuclear reactions. The neutrons are born in the ITER tokamak plasma chamber and then impinge on the surrounding blanket and port plugs, after that they diffuse through shielding material of vacuum vessel components or could stream through the diagnostic channels and assembly gaps far away from plasma up to the bio-shield and in a small amount beyond it. While ITER machine is in operation it is inaccessible, after the shut-down it is planned to provide personnel access to the Upper Port Inter-Space Structure (UP ISS) behind the Port Plug via the corridors. Neutrons activate the ITER materials and those radioactive materials emit decay gammas during the shut-down causing a Shut-Down Dose Rate (SDDR) field distributed all around the activated materials. Decay gammas could also stream through the void channels. That emphasizes the need for calculation of decay gamma transport in evaluations of SDDR, which is reflected in the use of transport - activation interface code described in Section of Computational Modelling. The assessment of radiation environment (fluxes and SDDR) at DGUPP was focused on the port back-side area of UP ISS, where personnel access is planned along the ISS maintenance corridors. Minimization of SDDR at the front part of the ISS maintenance corridors was the target value for optimization of the DGUPP shielding and analysis of related neutronics effects. Following the dose ALARA (As Low As Reasonably Achievable) principle, every possibility to reduce SDDR should be investigated, emphasizing the importance of this analysis. The challenges of such analysis are inextricably connected with the engineering complexity of the ITER machine, with integration of many diagnostics systems having channels and gaps inside the ITER ports. Those gaps result in radiation streaming and negatively affect the shielding performance of the port plugs. The computational complication is caused by the need to model precisely the ITER geometry and then to run deep penetrating radiation transport in the substantially heterogenic toroidal geometry of ITER large-size tokamak, with 30 m height and diameter of its bio-shield. The whole mass of Upper Port Plug (UPP) could be up to 25 tons and it must be very precisely positioned inside the port opening in blanket and Vacuum Vessel. Facing the engineering challenges for the assembly of DGUPP, there were proposed two Project Change Requests (PCRs) No. 439 and 709 concerning the design updates of UPP/blanket interface and its remote handling.
Using heterogeneous GPU nodes with a Cabana-based implementation of MPCD
In this study, the Kokkos based library Cabana, which has been developed in the Co-design Center for Particle Applications (CoPA), is used for the implementation of Multi-Particle Collision Dynamics (MPCD), a particle-based description of hydrodynamic interactions. Cabana allows for a function portable implementation, which has been used to study the interplay between CPU and GPU usage on a multi-node system as well as analysis of said interplay with performance analysis tools. As a result, we see most advantages in a homogeneous GPU usage, but we also discuss the extent to which heterogeneous applications might be more performant, using both CPU and GPU concurrently.
Assessing pellet-clad interaction with VERA: WBN1, cycles 6-7
The Consortium for Advanced Simulation of Light Water Reactors (CASL) aims to provide high fidelity simulations of nuclear reactors through the development of the Virtual Environment for Reactor Applications (VERA). One of the primary goals of CASL is to estimate local cladding failure through pellet-clad interaction (PCI). While this capability is being pursued through several different approaches, the procedure presented here focuses on running independent fuel performance calculations with the BISON fuel performance code being developed by Idaho National Laboratory using the multicycle output data from coupled neutron transport/thermal-hydraulics simulations generated by MPACT, CTF, and MAMBA. This type of approach is consistent with traditional fuel performance analysis methods, where the fuel performance analyses are typically separate from core simulation analyses. Recent work simulating 12 cycles of Watts Bar Unit 1 (WBN1) with VERA are capitalized upon, and stand-alone quarter-core BISON results can be obtained for several cycles, assessing parameters of interest to PCI (e.g., maximum centerline fuel temperature, maximum clad hoop stress, minimum gap thickness, and cumulative damage index). This is accomplished by using the coupled neutronics/thermal-hydraulics output power and temperature distributions as inputs for each BISON fuel rod case. Building on previous work which demonstrated this capability for Cycles 1 through 3, this paper presents the results for Cycles 6 and 7. Cycle 7 is of particular interest because significant CRUD-induced power shift was observed. While the current results do not immediately indicate that any rods are at an extreme risk of failure, further analysis on rods highlighted by this work may shed additional light on the likelihood of failure. (authors)
A Preliminary Radiological Risk Assessment Model for Disposition of Remote-Handled Transuranic Wastes at Los Alamos National Laboratory Area G - 20116
The U.S. Department of Energy (DOE) operates a low-level radioactive waste (LLW) disposal site at Material Disposal Area G, in Los Alamos, New Mexico, USA. Area G has been the primary LLW disposal site for Los Alamos National Laboratory (LANL) since the 1960's. In addition to LLW, Area G is host to a variety of other wastes, the disposition of which must be determined before closure of the site. A probabilistic Radiological Risk Assessment (RRA) for Area G is used in order to support decision making regarding some wastes that are not addressed in the extant Area G Performance Assessment (PA) and Composite Analysis (CA). Between 1979 and 1987, 33 special shafts were augered into the Bandelier Tuff at Area G. This volcanic tuff is present across Pajarito Plateau on the eastern slopes of the Jemez Mountains, and varies widely in its consistency, from weakly indurated non-welded layers to welded layers that uphold the mesa cliffs of the Plateau. These mesas are home to LANL, Area G, and the townsites of Los Alamos and White Rock, with residences about 1400 m from Area G. The 33 Shafts were lined with steel casing, and contain remote-handled (RH) transuranic wastes (TRU) resulting from experiments and analysis performed in special glove boxes at the Chemistry and Metallurgy Research (CMR) facility at LANL. Some of these wastes originated as used nuclear fuel. The purpose of the Area G RRA is to evaluate the potential future risk to humans and the environment from the RH TRU in the 33 Shafts in the context of the risk associated with the surrounding wastes at Area G. The analysis is responsive to expectations outlined in DOE Order 458.1, Radiation Protection of the Public and the Environment, and is informed by the Manual and Guidance accompanying DOE O 435.1, Radioactive Waste Management. Because the waste meets the definition of TRU, the regulatory context necessarily takes into consideration the regulation governing the disposal of TRU from the U.S. Environmental Protection Agency (EPA): 40 CFR 191, Environmental Radiation Protection Standards for Management and Disposal of Spent Nuclear Fuel, High-Level and Transuranic Radioactive Wastes. Given the broader regulatory context for the RRA, the analysis is subject to different assumptions from those made in the existing DOE O 435.1 PA and CA, such as allowing for future occupation of the site. The analysis begins with a comprehensive evaluation of features, events, processes, and exposure scenarios (FEPS) for Area G and the wastes it contains. These FEPSs are screened to eliminate from further consideration those of extremely low probability and/or consequence, and a conceptual site model (CSM) is subsequently developed. The scope and structure of the Area G RRA Model is informed by this CSM, and the Area G RRA Model is developed using the GoldSim systems analysis modeling platform. This paper presents the initial version of a defensible, transparent, and reasonably realistic model, which is based on the state of knowledge of the wastes, the site, and the FEPSs that govern contaminant transport from wastes into the environment and subsequent exposures to humans and other biota. Probabilistic model input distributions represent uncertainties inherent in the real and modeled systems. The results of the Area G RRA Model inform decisions regarding the disposition of the RH TRU in the 33 Shafts. (authors)
Decision and Modeling Strategy for a Radiological Risk Assessment at Area G, Los Alamos, New Mexico - 17258
The U.S. Department of Energy (DOE) owns a low-level radioactive waste (LLW) disposal site at Material Disposal Area G, in Los Alamos, New Mexico, USA. Area G has been the primary LLW disposal site for Los Alamos National Laboratory (LANL) since the 1960's, and is now approaching the end of its service life. In addition to LLW, Area G is host to a variety of other wastes, the disposition of which must be determined before closure of the site. A probabilistic Radiological Risk Assessment (RRA) for Area G is used in order to support decision making regarding some wastes that are not addressed in the extant Area G Performance Assessment (PA) and Composite Analysis (CA). Between 1979 and 1987, 33 special shafts were augered into the Bandelier Tuff at Area G. This tuff is present across Pajarito Plateau on the eastern slopes of the Jemez Mountains, and varies widely in its consistency, from weakly indurated non-welded layers to welded layers that uphold the mesa cliffs of the Plateau. These mesas are home to LANL, Area G, and the town of Los Alamos. The 33 Shafts were lined with steel casing, and contain remote-handled (RH) transuranic wastes (TRU) resulting from experiments and analysis performed in special glove boxes at the Chemistry and Metallurgy Research (CMR) facility at LANL. Some of these wastes originated as used ('spent') nuclear fuel. The purpose of the Area G RRA is to evaluate the potential future risk to humans and the environment from the RH TRU in the 33 Shafts in the context of the risk associated with the surrounding wastes at Area G. The analysis is responsive to expectations outlined in DOE Order 458.1, Radiation Protection of the Public and the Environment, and is informed by the Manual and Guidance accompanying DOE O 435.1, Radioactive Waste Management. Because the waste meets the definition of TRU, the regulatory context also takes into consideration the regulation governing the disposal of TRU from the U.S. Environmental Protection Agency (EPA): 40 CFR 191, Environmental Radiation Protection Standards for Management and Disposal of Spent Nuclear Fuel, High-Level and Transuranic Radioactive Wastes. Given the broader regulatory context for the RRA, the analysis is subject to different assumptions from those made in the existing DOE O 435.1 PA and CA, such as allowing for future occupation of the site. The analysis begins with a comprehensive evaluation of features, events, processes, and exposure scenarios (FEPS) for Area G and the wastes it contains. These FEPS are screened to eliminate from further consideration those of extremely low probability and/or consequence, and a conceptual site model (CSM) is subsequently developed. The scope and structure of the Area G RRA Model is informed by this CSM, and the Area G RRA Model is developed using the GoldSim systems analysis modeling platform. This paper outlines the development of a defensible, transparent, and reasonably realistic model, which is based on the state of knowledge of the wastes, the site, and the FEPS that govern contaminant transport and human exposures. Probabilistic model input distributions represent uncertainties inherent in the real and modeled systems. The results of the Area G RRA Model will inform decision analysis regarding the disposition of the RH TRU in the 33 Shafts. (authors)
Saint Joseph's University Institute for Environmental Stewardship
Task A: Examination of the physiological, morphological, and reproductive responses of Panicum virgatum (switchgrass) cultivars identified as potential biofuel producing cultivars as well as naturally-occurring varieties of switchgrass to projected changes in climate for the central portion of the United States. This project was a multi-year project set in a field site located at the Konza Prairie Biological Station near Manhattan, KS USA. The major objective of the study was to understand the physiological and growth responses of the important biofuel grass species, Panicum virgatum (switch grass) to simulated changes in precipitation expected for the Central Plains region of the United States. Population level adaptation to broad-scale regional climates or within-population variation in genome size of this genetically and phenotypically diverse C4 grass species may influence the responses to future precipitation variability associated with climate change. Therefore, we investigated switchgrass responses to water variability between natural populations collected across latitudinal gradient and populations. P. virgatum plants from natural populations originating from Kansas, Oklahoma, and Texas received frequent, small precipitation events (“ambient’) or infrequent, large precipitation events (‘altered”) to simulate contrasting rainfall variability expected from this region. We measured leaf-level physiology, aboveground biomass varied significantly by population origin but did not differ by genome size. Our results suggest that trait variation in P. virgatum is primarily attributed to population-level adaptation across latitudinal gradient, not genome size, and that neither population-level adaptation nor genome size may be important predictors of P. virgatum responses to future climatic conditions. Based solely on the data presented here, the most important consideration when deciding what varieties of switchgrass to cultivate for biofuel feedstocks under future climate scenarios is local adaptation and not necessarily genome size as has been hypothesized in the literature. Task B: Installation of an extensive green roof system on the Science Center at Saint Joseph's University for research, research-training and educational outreach activities. An experimental green roof system was designed and installed by an outside contractor (Roofmeadows) on the roof of the Science Center at Saint Joseph's University. The roof system includes four test plots, each with a different drainage system, instrumentation to monitor storm water retention, roof deck temperature, heat flux into and out of the building, rain fall, wind speed and direction, relative humidity and heat emission from the roof system. The vegetative roof was planted with 26 species of plants, distributed throughout the roof area, to assess species/variety growth and coverage characteristics, both in terms of the different drain layer systems, and in terms of the different exposures along the north to south axis of the building. Analysis of the drain layer performance, in terms of storm water retention, shows that the aggregate (stone) drainage layer system performed the best, with the moisture management mat system second, and the geotextile drain layer and reservoir sheet layer systems coming in last. This information is of value in the planning and design of vegetative roof systems since the different types of drainage layer systems have different installation costs and different weights. The different drainage layer systems also seem to be having an impact on plant growth and spread with the test plot with the reservoir sheet layer actually having the poorest plant coverage and plant spread of all areas of the roof studied. Plant growth performance analysis is ongoing, but significant differences have been observed in the third growing season ('13) along the north to south axis, with most species doing better towards the northern end of the roof (in terms of percent ground coverage and plant spread and reproduction). Interestingly, plant growth in all four of the test plots was reduced relative to the lower areas of the roof (the lower area was ca. 2 inches lower than the test plots, due to the space needed for sensors under the plots. The lower roof area uses an aggregate drain layer comparable to that in the third test plot), even when accounting for the north to south differences. The reasons for these differences are not clear and studies are underway to examine the impact of wind scour, drainage rates, temperature, and other factors. This information will be of value to planners of extensive vegetative roof systems in the Philadelphia (and broader) region, since plant growth and roof system overall performance is influenced by local climate, making broad generalizations of performance difficult. Task C: Education and community outreach efforts by the IES involving conferences at SJU, presentations by faculty and students off campus, and educational signage. The Institute for Environmental Stewardship hosted three storm water management workshops on the SJU campus in Philadelphia, in collaboration with the Lower Merion Conservancy, a not-for-profit organization located in Montgomery County, PA. These workshops were free and open to the public. The three workshops (held each year in March) drew more than 200 participants total. The presenters included local and state government agencies, not for profit organizations involved in storm water and open space preservation, designers, engineers, planners and others. Feedback was uniformly positive and we plan to continue the workshops for the foreseeable future. Educational signage has been installed at four locations on campus to explain campus infrastructure related to storm water (rain gardens, vegetative roof and green facades), as well as detailed signage installed on the Science Center roof for the vegetative roof system. More than 100 people (from in and outside of SJU) have thus far participated in tours of the roof system. A digital signage system has been installed in the adjacent library and this system provides information about the vegetative roof project and other efforts. A web camera system for the roof has also been installed and the video will be simulcast to the digital signage and with web site (www.sju.edu/ies) in the near future.
Finite time step and spatial grid effects in δf simulation of warm plasmas
This paper introduces a technique for analyzing time integration methods used with the particle weight equations in δf method particle-in-cell (PIC) schemes. The analysis applies to the simulation of warm, uniform, periodic or infinite plasmas in the linear regime and considers the collective behavior similar to the analysis performed by Langdon for full-f PIC schemes [1,2]. We perform both a time integration analysis and spatial grid analysis for a kinetic ion, adiabatic electron model of ion acoustic waves. An implicit time integration scheme is studied in detail for δf simulations using our weight equation analysis and for full-f simulations using the method of Langdon. It is found that the δf method exhibits a CFL-like stability condition for low temperature ions, which is independent of the parameter characterizing the implicitness of the scheme. The accuracy of the real frequency and damping rate due to the discrete time and spatial schemes is also derived using a perturbative method. The theoretical analysis of numerical error presented here may be useful for the verification of simulations and for providing intuition for the design of new implicit time integration schemes for the δf method, as well as understanding differences between δf and full-f approaches to plasma simulation.