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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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This case study compares energy and usability of remote virtual machines accessed through zero-client devices with traditional laptop computers to determine if zero-client computing could be a solution to reducing building energy use.
High-energy physics (HEP) experiments require data acquisition (DAQ) systems that can orchestrate complex detector operations, high data throughput, and responsive, real-time feedback to operators. Traditional DAQ stacks, which are often bespoke, command-line driven and highly specific, impose large learning curves on users. The Off-The-Shelf Data Acquisition (\textit{otsdaq}) framework was created to address these issues by offering a highly customizable and scalable browser-based ’desktop’ environment, in which experiment-specific control and monitoring applications can be easily deployed and integrated. Although the initial development of the \textit{otsdaq} software was aimed at the Fermilab Test Beam Facility, \textit{otsdaq} is now being leveraged for broader deployment, including the upcoming Mu2e experiment, where real-time monitoring of field-programmable gate array (FPGA)-based Data Transfer Controllers (DTCs), Clock and Fanout (CFO) boards, and several other subsystems are critical. We contribute a set of targeted improvements to \textit{otsdaq}: bitmap visualization functionality for configured data, improved and corrected delta-based DTC throughput metrics, version control (VC)-backed source navigation for console messages, custom navigation hooks to eliminate disruptive user interface glitches, and copy-to-clipboard support for macro execution history. These changes improve usability, reduce debugging time, and increase accuracy in performance data as Mu2e moves toward commissioning.
New abstract from the final version being submitted now: This paper discusses the evolution and enhanced usability of the ŠKODA VPVR/M cask for the transport of irradiated fuel assemblies, particularly within the context of the demand for the delivery of newly appearing irradiated HEU fuel types for which the cask did not yet have a license to transport. Over time, the cask’s internal basket construction has demonstrated notable adaptability to accommodate various exotic HEU fuel types from research reactors of differing origins. The paper outlines sever-al custom internal baskets developed for specific fuel types, including those from Belarus and Serbia, as well as from Georgia, Uzbekistan, and MNSR cores, as well as a recently designed basket for MTR and TRIGA assemblies. The findings high-light the high flexibility and adaptability of the cask, supported by successful rede-signs and licensing efforts, underscoring its value for the safe and secure transport of nuclear material. Old abstract from the draft version that was already approved: The Russian Research Reactor Fuel Return (RRRFR) program, since its inception, has continuously used the ŠKODA VPVR/M Cask fleet designed for the repatriation of irradiated highly enriched uranium (HEU) fuel. As the program progressed (from shut-down and a quasi-abandoned reactor, and/or as it began to include fuels of Chinese and US origin), new challenges emerged for the transport Cask. These were fuel types that had not yet been licensed for the Cask. Although these requirements did not arise during the design of the basic ŠKODA VPVR/M Cask, as revealed by the retrospective analyses, the Internal Basket of the ŠKODA VPVR/M Cask gives a high degree of flexibility to accommodate additional fuel types. This paper provides a brief overview of the ŠKODA VPVR/M Cask, which holds a B(U) type license, and introduces the different types of Internal Baskets that have already been licensed to transport so-called exotic irradiated HEU fuel types, in addition to the original license. The paper presents a new Internal Basket design for accommodating MTR-type and TRIGA-type irradiated HEU fuel assemblies. This includes a detailed presentation of the design basis and the new MTR-TRIGA Internal Basket, as well as the licensing matters of the package under the name ŠKODA MTR-TRIGA Cask, and the conformity test (dry- and wet-run) operations made to verify compliance with the new Internal Basket. Then, as a summary, the usage record for the Cask fleet is presented, and finally, the paper concludes with the consolidated experiences gained during the utilization of the ŠKODA VPVR/M Cask fleet, emphasizing the high degree of Cask flexibility ensured by the Internal Basket’s construction.
The NBS web site contains system status and support material for NBS applications.
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Thermoplastic 3D printing (T3DP) is an additive manufacturing (AM) technology, which can be used for the production of dense single- and especially multi-material components. This becomes possible because of the combination of the precise deposition of small droplets of molten thermoplastic suspensions containing ceramic or metal particles, and a curing mechanism caused on cool down increasing the viscosity. In this paper, the droplet formation behavior of zirconia suspensions for T3DP (82 and 84 wt.%) was investigated. The droplet fusion factor (dff) is introduced to calculate the necessary distance between two droplets to form filament-like structures by fusion of adjacent droplets. Filament-like structures with a smooth surface and a nearly homogeneous cross section were manufactured for both suspensions with a dff of 44% or higher.
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To inform charger deployment decisions, this paper aims to understand the potential utilization and deployment priority for public charging infrastructure. A data-driven Cumulative Public Recharging (CPR) model is developed to explore the travel patterns by using 2017 National Household Travel Survey data. Given the daily trip sequence, trip distance, and dwell times, the study examines the daily expected driving range and BEV feasibility under different charging speeds, battery capacity, and charging behaviors. The results suggest that more advanced public chargers increase the daily expected driving range. Home charging is sufficient for most daily short-distance trips while public chargers are still needed for medium- and long-distance trips. Extreme fast charging (xFC) may not be necessary for people with home charging but could be more useful for people without home charging and for urgent charging. In conclusion, xFC becomes even less important to drivers with longer BEV ranges, a finding that contradicts conventional thinking.
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Abstract The release of global climate projections coupled with the demand for local-resolution climate-forced meteorology has prompted many research groups to downscale these projections using various statistical, dynamical, and current machine learning techniques. Such downscaled datasets are being used to plan infrastructure and other community needs over the coming decades. Faced with roughly a dozen available US downscaled datasets, many practitioners ask, ‘What are the relevant differences between datasets?’ This work highlights the difficulty of comparing downscaled datasets and illustrates ways in which datasets differ even when using identical climate model input data. We show that substantial variability in precipitation projections arises from downscaling alone and that the downscaled dataset agreement varies depending on global climate projection. This analysis emphasizes the need for greater coordination and movement toward rigorous benchmarking of downscaling strategies within the downscaling research community, à la the land-modeling community, to better quantify downscaling dataset differences, strengths, and weaknesses for practitioners.
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It has been demonstrated that monazite-type materials are excellent candidates for nuclear waste forms, and hence, their facile synthesis is of great importance for the needed sequestration of existing nuclear waste. The synthesis of monazite, LaPO 4 , requires inconveniently high temperatures near 1000°C and generally involves the conversion of the presynthesized rhabdophane, LaPO 4 •nH 2 O, to the LaPO 4 monazite phase. During this structure transformation, the rhabdophane converts irreversibly to the thermodynamically stable monoclinic monazite structure. A low-temperature (185° to 260°C) mild hydrothermal acid-promoted synthesis of monazite is described that can both transform presynthesized rhabdophane or assemble reagents to the monoclinic monazite structure. The pH dependence of this reaction is detailed, and its applicability to the LnPO 4 (Ln = La, Ce, Pr, Nd, Sm-Gd), Ca 0.5 Th 0.5 PO 4 , and Sr 0.5 Th 0.5 PO 4 systems is discussed. The crystal growth of Ca 0.5 Th 0.5 PO 4 and Sr 0.5 Th 0.5 PO 4 is described, and their crystal structures were reported. In situ x-ray diffraction studies, performed as a function of temperature, provide insight into the structure transformation process.
In the HPC area, both hardware and software move quickly. Often new hardware is developed and deployed, the corresponding software stack, including compilers and other tools, are under active development while leading edge software developers are working to port and tune their applications, all at the same time. While the software ecosystem is in flux, one of the key challenges for users is obtaining insight into the state of implementation of key features in the programming languages and models their applications are using – whether they have been implemented, and whether the implementation conforms to the specification, especially for newly implemented features (less tested by widespread use). OpenMP is one of the most prominent shared memory programming models used for on-node programming in HPC. With the shift towards accelerators (such as GPUs and FPGAs) and heterogeneous programming OpenMP features are getting more complex. It is natural to ask whether generative AI approaches, and large language models (LLMs) in particular, can help in producing validation and verification test suites to allow users better and faster insights into the availability and correctness of OpenMP features of interest. In this work, we explore the use of ChatGPT-4 to generate a suite of tests for OpenMP features. We have chosen a set of directives and clauses, a total of 78 combinations, which first appeared in OpenMP 3.0 (released in May 2008) but are also relevant for accelerators. We prompted ChatGPT to generate tests in the C and Fortran languages, for both host (CPU) and device (accelerator). On the Summit super-computer using the GNU implementation, we found that, of the 78 generated tests 67 C tests and 43 Fortran tests compiled successfully and fewer than those executed to completion. On further analysis we show that not all generated tests are valid. We document the process, results, and provide detailed analysis regarding the quality of tests generated. With the aim of providing input to a production quality validation and verification suite, we manually implement the corrections required to make the tests valid according to the current OpenMP specification. We quantify this effort as small, medium, or large, and record the lines of code changed to correct the invalid tests. With the corrected tests we validate recent implementations from HPE, AMD, and GNU on the Frontier supercomputer. Our experiment and subsequent analysis show that although LLMs are capable of producing HPC specific codes, they are limited by their understanding of the deeper semantics and restrictions of programming models such as OpenMP. Unsurprisingly more commonly used features have better support, while some OpenMP 3.0 directives such as sections and tasking are not universally supported on accelerators. We demonstrate that successful compilation and execution to completion are inadequate metrics for evaluating generated code and that, at this time, commodity LLMs require expert intervention for code verification. This points to gaps in the training data that is currently available for HPC. We demonstrate that with "small" effort 37% of generated invalid C tests and 63% of generated invalid Fortran tests could be corrected. This improves productivity of test generation as we circumvent writing from scratch and the common programming errors associated with it.
The LLNL team has carried out extensive analysis of GridPACK code, including two major code reviews (each being a 2-day event) and a vendor emulation exercise, where the team integrated GridPACK library within a third-party application. The code analysis identified a number of areas for improvement of GridPACK code architecture, but it did not find fundamental flaws in the GridPACK design. The team found the GridPACK strategy of developing a software development kit (SDK) for power systems application development to be sound and well aligned with Office of Electricity long term objectives. The SDK aims to provide power systems software vendors an easy access to high performance computing (HPC) libraries.
The recently developed capability to perform ex-core calculations in the Virtual Environment for Reactor Applications (VERA) with Shift is now available in production releases of VERA. To support these production releases, updates to the VeraShift interface are needed continually. The updates completed under this milestone are documented in this report, including improvements to memory usage and code robustness, as well as the resolution of issues with unexpected behavior that arose during testing.