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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 37 records · Page 2

In-situ visual inspection of the CASTOR V/21 used nuclear fuel dry storage cask: a demonstration of camera system capabilities - 15505

On June 11, 2014 the Gesellschaft fur Nuklear Service (GNS) CASTOR V/21 spent fuel dry storage cask was inspected in-situ at the Idaho Nuclear Technology and Engineering Center (INTEC). The purpose of this inspection is to demonstrate and document the technology necessary to perform inspections of spent fuel dry storage casks. The inspection includes internal temperature measurement, internal radiation measurement, and a visual examination using a bore-scope type camera system inserted through the cask fill/drain penetration. It is concluded from this inspection that in-situ inspections of bolted lid spent fuel storage containers is possible using current camera technologies. Using 3D Phase Measurement Technology, measurements of entities such as cracks or corrosion are possible. The internal surfaces of the CASTOR V/21 cask that were inspected were free of corrosion and exhibited no evidence of degradation. One crack identified in previous inspections was examined and appeared the same as in the previous inspections. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

GRACC: GRid ACcounting Collector

The OSG has long maintained a central accounting system called Gratia. It uses small probes on each computing and storage resource in order to collect resource usage. The probes report to a central collector which stores the usage in a database. The database is then queried to generate reports. As the OSG aged, the size of the database grew very large. It became too large for the database technology to efficiently query to generate detailed reports. The design of a replacement requires data storage that could be queried efficiently to generate multi-year reports. Additionally, it requires flexibilityto add new attributes to the collected data.In this paper we will describe updates to the GRACC architecture in the last 18 months. GRACC uses modern web technologies that were designed for large data storage, query, and visualization. That includes the open source database Elasticsearch, message broker software RabbitMQ, and Grafana and Kibana as data visualization platforms. It uses multiple agents that perform operations on the data to transform it for easier querying and summarization.

Weitzel, Derek↗

A near infra-red video system as a protective diagnostic for electron cyclotron resonance heating operation in the Wendelstein 7-X stellarator

The Wendelstein 7-X stellarator is a large nuclear fusion device based at Max-Planck-Institut für Plasmaphysik in Greifswald in Germany. The main plasma heating system for steady state operation in W7-X is electron cyclotron resonance heating (ECRH). During operation, part of plama facing components will be directly heated by the non-absorbed power of 1 MW rf beams of ECRH. In order to avoid damages of such components made of graphite tiles during the first operational phase, a near infra-red video system has been developed as a protective diagnostic for safe and secure ECRH operation. Both the mechanical design housing the camera and the optical system are very flexible and respect the requirements of steady state operation. The full system including data acquisition and control system has been successfully tested in the vacuum vessel, including on-line visualization and data storage of the four cameras equipping the ECRH equatorial launchers of W7-X.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

CPU Isosurface Ray Tracing of Adaptive Mesh Refinement Data

Adaptive mesh refinement (AMR) is a key technology for large-scale simulations that allows for adaptively changing the simulation mesh resolution, resulting in significant computational and storage savings. However, visualizing such AMR data poses a significant challenge due to the difficulties introduced by the hierarchical representation when reconstructing continuous field values. Here, we detail a comprehensive solution for interactive isosurface rendering of block-structured AMR data. We contribute a novel reconstruction strategy—the octant method—which is continuous, adaptive and simple to implement. Furthermore, we present a generally applicable hybrid implicit isosurface ray-tracing method, which provides better rendering quality and performance than the built-in sampling-based approach in OSPRay. Finally, we integrate our octant method and hybrid isosurface geometry into OSPRay as a module, providing the ability to create high-quality interactive visualizations combining volume and isosurface representations of BS-AMR data. Lastly, we evaluate the rendering performance, memory consumption and quality of our method on two gigascale block-structured AMR datasets.

97 MATHEMATICS AND COMPUTING↗

Scientific Computing Strategic Plan for the Idaho National Laboratory

Scientific computing is a critical foundation of modern science. Without innovations in the field of computational science, the essential missions of the Department of Energy (DOE) would go unrealized. Taking a leadership role in such innovations is Idaho National Laboratory’s (INL’s) challenge and charge, and is central to INL’s ongoing success. Computing is an essential part of INL’s future. DOE science and technology missions rely firmly on computing capabilities in various forms. Modeling and simulation, fueled by innovations in computational science and validated through experiment, are a critical foundation of science and engineering. Big data analytics from an increasing number of widely varied sources is opening new windows of insight and discovery. Computing is a critical tool in education, science, engineering, and experiments. Advanced computing capabilities in the form of people, tools, computers, and facilities, will position INL competitively to deliver results and solutions on important national science and engineering challenges. A computing strategy must include much more than simply computers. The foundational enabling component of computing at many DOE national laboratories is the combination of a showcase like data center facility coupled with a very capable supercomputer. In addition, network connectivity, disk storage systems, and visualization hardware are critical and generally tightly coupled to the computer system and co located in the same facility. The existence of these resources in a single data center facility opens the doors to many opportunities that would not otherwise be possible.

97 MATHEMATICS AND COMPUTING↗

Energy Systems Integration Facility Stewardship Summary: Fiscal Year 2022

A summary of NREL's good stewardship of the nationally unique Energy Systems Integration Facility (ESIF) highlighting performance metrics, infrastructure and capability upgrades, and examples of R&D impact. In fiscal year 2022, ESIF researchers made breakthroughs in everything from long-duration energy storage and cybersecurity visualizations to a world record in heavy-duty hydrogen vehicle fueling, and built out research assets to advance microgrid operation and controls, renewable hydrogen production, electric vehicles, energy-efficient buildings, and more.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗

GUIDE: A Scalable Information Directory Service to Collect, Federate, and Analyze Logs for Operational Insights into a Leadership HPC Facility

In this paper, we describe the GUIDE framework to collect, federate, and analyze log data from the Oak Ridge Leadership Computing Facility's (OLCF), and how we use it derive insights into center operations. We collectsystem logs and extract monitoring data at every level of the various OLCF subsystems, and have developed a suite of pre-processing tools to make the raw data consumable. The cleansed logs are then ingested and federated into a central, scalable data warehouse, Splunk, that offers storage, indexing, querying, and visualization capabilities. We have further developed and deployed a set of analytics tools to analyze these multiple disparate log streams in concert, and derive operational insights. We describe our experience from developing and deploying the GUIDE infrastructure, and deriving valuable insights on the various subsystems, based on two years of operations in the production OLCF environment.

Vazhkudai, Sudharshan↗

Understanding Performance-Quality Trade-offs in Scientific Visualization Workflows with Lossy Compression

The cost of I/O is a significant challenge on current supercomputers, and the trend is likely to continue into the foreseeable future. This challenge is amplified in scientific visualization because of the requirement to consume large amounts of data before processing can begin. Lossy compression has become an important technique in reducing the cost of performing I/O. In this paper we consider the implications of using compressed data for visualization within a scientific workflow. We use visualization operations on simulation data that is reduced using three different state-of-the-art compression techniques. We study the storage efficiency and preservation of visualization features on the resulting compressed data, and draw comparisons between the three techniques used. Our contributions can help inform both scientists and researchers in the use and design of compression techniques for preservation of important visualization details.

Chen, Jieyang↗

Aluminum Clad Spent Nuclear Fuel Task 4: Performance of Aluminum SNF in Dry Storage Experiment Test Plan

This document presents the activities to be performed in support of understanding the performance of aluminum spent nuclear fuel (ASNF) in dry storage. These activities will visually examine and acquire baseline samples of as-irradiated ATR fuel assembly components to determine fuel condition and the morphology of the aluminum oxyhydroxides present on the fuel external surfaces. Because the boehmite phase of oxyhydroxide is projected to be a significant contributor to radiolytic hydrogen production and general corrosion, being able to quantify its presence is of major importance to long term storage of aluminum spent nuclear fuel. Baseline samples will be taken from irradiated end adapters, removed from ATR SNF elements, stored in the ATR Canal. These will be transferred to Idaho National Laboratory (INL) Materials and Fuels Complex (MFC) to perform non-destructive and destructive testing to determine the degree of hydration of the wet-stored aluminum components prior to drying and air storage. Examination of the dry stored SNF at Idaho Nuclear Technology and Engineering Center (INTEC) in CPP-603 Irradiated Fuel Storage Facility (IFSF) will allow the opportunity to identify gross degradation and as conditions permit, sample the surface oxide on fueled and un-fueled portions of the stored assemblies. The information resulting from analysis of the ATR Canal samples will be used to support validation of surrogate samples prepared under Task 6, sample surrogate preparation, and used in Task 1, oxyhydroxide layer behavior and chemistry, Task 2, oxide layer radiolytic gas generation, and Task 5, oxide layer response to drying. Surface oxide samples collected from SNF in IFSF dry storage will SNF dry storage prediction modeling from Task 3, sealed and vented system episodic breathing and gas generation prediction.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Offshore Geologic Carbon Storage (GCS) Inventory

The Offshore Geological Carbon Storage Inventory Web Map is an online web mapping application designed to help users explore and visualize the Offshore Geologic Carbon Storage Inventory. This dataset is an inventory of offshore geologic carbon storage (GCS) projects and studies, gathered to summarize ongoing GCS efforts taking place offshore globally. This inventory includes both actualized projects as well as characterization studies and aggregates a variety of attribute fields for each project / study. It is intended to be used for research and comparison purposes, see full disclaimer and credits.

Assessment↗

InSituNet: Deep Image Synthesis for Parameter Space Exploration of Ensemble Simulations

We propose InSituNet, a deep learning based surrogate model to support parameter space exploration for ensemble simulations that are visualized in situ. In situ visualization, generating visualizations at simulation time, is becoming prevalent in handling large-scale simulations because of the I/O and storage constraints. However, in situ visualization approaches limit the flexibility of post-hoc exploration because the raw simulation data are no longer available. Although multiple image-based approaches have been proposed to mitigate this limitation, those approaches lack the ability to explore the simulation parameters. Our approach allows flexible exploration of parameter space for large-scale ensemble simulations by taking advantage of the recent advances in deep learning. Specifically, we design InSituNet as a convolutional regression model to learn the mapping from the simulation and visualization parameters to the visualization results. With the trained model, users can generate new images for different simulation parameters under various visualization settings, which enables in-depth analysis of the underlying ensemble simulations. We demonstrate the effectiveness of InSituNet in combustion, cosmology, and ocean simulations through quantitative and qualitative evaluations.

deep learning↗

Performance Visualization for TAU Instrumented Scientific Workflows

In exascale scientific computing, it is essential to efficiently monitor, evaluate and improve performance. Visualization and especially visual analytics are useful and inevitable techniques in the exascale computing era to enable such a human-centered experience. In this ongoing work, we present a visual analytics framework for performance evaluation of scientific workflows. Ultimately, we aim to solve two current challenges: the capability to deal with workflows, and the scalability toward exascale scenario. On the way to achieve these goals, in this work, we first incorporate TAU (Tuning and Analysis Utilities) instrumentation tool and improve it to accommodate workflow measurements. Then we establish a web-based visualization framework, whose back end handles data storage, query and aggregation, while front end presents the visualization and takes user interaction. In order to support the scalability, a few level-of-detail mechanisms are developed. Finally, a chemistry workflow use case is adopted to verify our methods

97 MATHEMATICS AND COMPUTING↗

Investigation of Imaging Spent Nuclear Fuel Dry Casks using Cosmic Ray Muons

Recently, the use of cosmic ray muons for cargo scanning applications has been demonstrated and muons have been shown to have the potential to allow for nondestructive assessment of nuclear material accountancy. Relativistic muons have the ability to penetrate dense materials and monitoring the subsequent scattering of muons can provide information about the structure and composition of materials stored in cargo containers. The suitability of cosmic muons for a number of monitoring and imaging applications has been investigated over the years and includes applications to archaeology, volcano imaging, material identification and medical diagnosis. Novel applications of cosmic ray muons have been proposed for examination of comatose patients towards bone density monitoring and also for determination of the molten nuclear fuel location in nuclear reactors having suffered from the effects of a severe accident similar to the one happened in Fukushima. There is a need to develop a capability to monitor nuclear waste and investigate whether the stored content agrees with facility declarations to allow proliferation detection and international treaty verification. Monitoring nuclear waste and controlling nuclear material at its source is one of the main strategies to minimize the risks of nuclear proliferation and reduce potential homeland threats. Since the early 1950's, when the first nuclear power plant began to produce electricity, approximately 65,000 metric tons of spent nuclear fuel have been generated, 25% of which are under dry storage conditions. After the spent nuclear fuel has been placed inside the dry cask, the cask is welded, not allowing for visual inspection. During the long storage life of the cask, intermediate handling and transportation activities take place which does create concerns regarding fuel integrity. Accidents and natural disasters also contribute to this concern. Previous work on spent nuclear fuel dry cask monitoring using muons has shown that the muon scattering distributions are adequately separated and a and a decision rule derived from Bayes' Theorem rendering the classification of different dry casks feasible. Muons present significant advantages over the existing imaging techniques such as the utilization of the passive nature of muons, the lack of radiological sources and consequently the absence of any artificial radiological dose. In the present work, a methodology is developed to demonstrate the applicability of muons for imaging of spent nuclear fuel dry casks. Purpose is to use muons to differentiate between spent nuclear fuel dry casks with different amounts of loading. Monte Carlo simulations of dry casks with different spent nuclear fuel loading are performed to simulate the passage of polyenergetic muons having energies in the range of 1-60 GeV through matter. A 'Muon Generator' is developed to generate muons that follow the actual sea level energy distribution. The 'Muon Generator' is validated against a series of actual spectrum measurements and then coupled with the Monte Carlo particle transport code GEANT4. The accumulated dataset of scattering angles were processed with the Point-of- the-Closest-Approach (PoCA) imaging algorithm and the obtained images demonstrate that an empty dry cask can be clearly distinguished from a half-loaded or a fully loaded one. The apparent separation of the images demonstrates that the muon scattering can be used as a feature for imaging spent nuclear fuel dry casks. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The Exploitation of Data Reduction for Visualization

The disparity between the computational speed and storage bandwidth, as demonstrated in Figure 1, is a well known problem that grows with each successive generation. The visualization community is principally responding to this issue by using in situ to reduce which data must be written to storage. However, other communities are taking different, possibly complementary approaches. In particular, data compression is a common general approach to reduce storage demands. Data compression technologies are typically not designed with post processing in mind. The principal metrics measured are compression ratio, the improved bandwidth to storage, and the error introduced. It is assumed that data is inflated to its full size before any post processing can happen. Although when talking about bandwidth disparities, HPC’s dirty little secret is that no part of the memory nor interconnect hardware is increasing at the rate of computation. For example, the Summit supercomputer has a peak computation rate almost 10 times its predecessor, Titan, but only about 4 times the memory, less than twice the aggregate memory bandwidth, and almost no improvement in the interconnect bisection bandwidth. Naively inflating data for post processing does not help with limitations in the memory and interconnect systems.

97 MATHEMATICS AND COMPUTING↗

Morphology of U 3 O 8 materials following storage under controlled conditions of temperature and relative humidity

Changes in the visual characteristics of uranium oxide surfaces and morphology following storage under different conditions of temperature and relative humidity may provide insight into the history of an unknown sample. Sub-samples of three α-U 3 O 8 materials—one that was phase-pure and two that were phase-impure—were stored under controlled conditions for two years. We used scanning electron microscopy to image the oxides before and after storage, and a morphology lexicon was used to characterize the images. Finally, temporal changes in morphology were observed in some sub-samples, and changes were greatest following exposure to high relative humidity.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Cinema image-based in situ analysis and visualization of MPAS-ocean simulations

We created an in situ exploration visualization of an MPAS-Ocean simulation.We leveraged compositing in Cinema to provide interactive exploration.We decreased the storage footprint of the analysis and visualization results. Due to power and I/O constraints associated with extreme scale scientific simulations, in situ analysis and visualization will become a critical component to scientific exploration and discovery. Current analysis and visualization options at extreme scale are presented in opposition: write files to disk for interactive, exploratory analysis, or perform in situ analysis to save data products about phenomena that a scientists knows about in advance. In this study, we demonstrate extreme scale visualization of MPAS-Ocean simulations leveraging a third option based on Cinema, which is a novel framework for highly interactive, image-based in situ analysis and visualization that promotes exploration.

97 MATHEMATICS AND COMPUTING↗

Technical Track on Biomass Carbon Removal and Storage (BiCRS): Mapping bioresources, phase 1 - Consistency check comparing Mission Innovation’s Data Visualization Tool for Bioresources and the Clean Energy Ministerial Biofuture Initiative Global Biomass data accessible via the US Department of Energy’s Bioenergy Knowledge Discovery Framework (KDF)

The Mission Innovation (MI) Carbon Dioxide Removal (CDR) Mission, Technical Track on Biomass Carbon Dioxide Removal and Storage (BiCRS), has produced a biomass resource database for its members. In parallel, Oak Ridge National Laboratory (ORNL) developed the International Feedstock Reporting data portal—herein referred to as the CEM Biofuture-KDF data—on behalf of the Clean Energy Ministerial Biofuture Initiative (CEM Biofuture), as a specific task under Biofuture’s 2024–25 Action Plan. This work was conducted at the request of CEM Biofuture and funded by the U.S. Department of Energy in support of that initiative, and it is hosted within DOE’s Knowledge Discovery Framework (KDF).

09 BIOMASS FUELS↗