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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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DOE OSTI2024

Development of the ARM Lagrangian Large-Scale Forcing Data (ARMLAGTRAJ) Value-Added Product Based on the lagtraj Framework

The Atmospheric Radiation Measurement (ARM) large-scale forcing data developed based on the constrained variational analysis (VARANAL) value-added product (VAP) (Zhang and Lin 1997, Zhang et al. 2001, Xie et al. 2004, Tang et al. 2019) has been widely used for single-column models (SCMs), cloud-resolving models (CRMs), and large-eddy simulation models (LESs) to understand and improve physical processes in models. Recently, the U.S. Department of Energy (DOE) ARM user facility conducted several major field campaigns using ship-based moving observational platforms. For example, the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign focused on the role of subtropical marine-boundary layer (MBL) clouds, and the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign aimed to improve understanding of the coupled climate systems in the Arctic. Observations from moving platforms are critical to provide a comprehensive characterization of coupled-system processes associated with all stages of the cloud and/or sea-ice life cycle. Traditional ARM large-scale forcing data have been developed at fixed locations. They need to be extended to include these moving platforms to address data needs for ship-based field campaigns or to support LES modeling in a Lagrangian framework. With these considerations in mind, we develop ARM-type Lagrangian large-scale forcing data sets based on the lagtraj framework (Boeing et al. 2020) with notable enhancements in generating forcings that are more suitable for ARM field campaigns. The lagtraj is a novel tool that generates forcings for LES and SCM simulation in both Lagrangian and Eulerian perspective. This technical report focuses on the major changes we performed on the lagtraj algorithm and provides an overview of the ARM Lagrangian Large-Scale Forcing Data (ARMLAGTRAJ) value-added products.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Enhanced Component Performance Study: Motor-Driven Pumps 1998-2020

This report presents an enhanced performance evaluation of motor-driven pumps (MDPs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2020 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The MDP failure modes considered for standby systems are fail to start (FTS), fail to run (FTR) for one hour of operation (FTR≤1H), FTR after one hour of operation (FTR>1H), and for normally running systems FTS and FTR. An eight-hour unreliability estimate is also calculated and trended. The component reliability estimates and the reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire study period. The following increasing trends were identified for MDPs for the most recent 10-year period: • Standby MDP frequency of start demands (demands per reactor year) • Standby MDP frequency of FTR≤1H hours (hours per reactor year) • Standby MDP frequency of FTR>1H hours • Normally running MDP frequency of run hours. The following decreasing trends were identified for MDPs for the most recent 10-year period: • Standby MDP FTR≤1H failure probability • Normally running MDP FTR failure rate • Standby MDP unavailability • Normally running MDP total unreliability (8-hour mission) • Standby MDP frequency of FTR≤1H events (failures per reactor year) • Normally running MDP frequency of FTR events.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Examining the Ice-Nucleating Particles from the North Slope of Alaska (ExINP-NSA) (Final Campaign Report)

The Examining the Ice-Nucleating Particles from the North Slope of Alaska (ExINP-NSA) campaign was conducted at the National Oceanic and Atmospheric Administration’s (NOAA) Barrow Atmospheric Baseline Observatory (71.3230° N, 156.6114° W, “BRW” hereafter), next to the Atmospheric Radiation Measurement (ARM) user facility NSA site and ~ 6 km northeast of the town of Utqiaġvik. The location of the NSA site is shown in Figure 1. Our observing period began in October 2021 and continued until May 2024. This campaign was funded by the U.S. Department of Energy (DOE) Office of Science Early Career Research Program through grant number DE-SC001879. This grant contains funding for three ARM field campaigns. The previous field campaigns were performed at ARM’s Southern Great Plains atmospheric observatory in Oklahoma (SGP; 36.6073° N, 97.4876° W) and the ARM’s Eastern North Atlantic atmospheric observatory on Graciosa Island, Azores (ENA; 39.0916° N, 28.0257° W). The ExINP-NSA campaign aims included: • Determining the number concentration of ice-nucleating particles (n INPs ) active at temperatures spanning the range of heterogeneous freezing processes (from ≈−30 °C to 0 °C) using a combination of online and offline measurements, • Determining whether local meteorological conditions and/or synoptic scale air mass transport impact INP abundance and/or ice nucleation efficiency, • Examining if the physicochemical properties of INPs relate to aerosol chemistry, and • Assessing if there is a similarity in INP properties across three ARM sites Multi-seasonal datasets of INP abundance in the NSA region were delivered from this campaign. This campaign also allowed researchers to perform a comprehensive analysis of atmospheric INPs based on long- term ground-based measurements in the Alaskan Arctic. Our data and results from the ExINP-NSA campaign will help refine current earth system models. One of the stated goals of ARM is to advance aerosol-cloud ice interaction, which will be a direct result of this campaign. Current earth system models poorly represent INPs, and the 15-minute time resolution data over several seasons generated during this campaign will provide an invaluable resource, especially combined with the datasets generated during two previous ARM ExINP campaigns. These datasets will allow for a greater understanding of ice nucleation processes as they may (or may not) relate to local meteorological processes and aerosol chemistry and will eventually help further the understanding of the Earth’s atmospheric processes and energy balance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Final Technical Report

Statement of the problem or situation that is being addressed in your application. The DOE and its national laboratories developed the Home Energy Score™ (HES) to encourage homeowners to improve their energy performance, lower costs and to share energy information through the MLS listing, appraisal, and financing channels. While the HES is an instrumental tool, it is currently underutilized and consists of technical, structural and sector barriers which need to be addressed in order to scale and many energy efficiency contractors are understandably overwhelmed by the added time and effort and lack of incentive to sell and deliver deep retrofit projects while simultaneously meeting the DOE HES program requirements; consequently, contractors may decide to forgo participation. Home Energy Rating System (HERS) Raters have the opportunity to play the critical Assessor role in producing a Home Energy Score (HES); this role has immense potential but currently is unfulfilled. Lastly, while utilities are interested in their customer base achieving greater energy efficiency, especially to help offset growing residential loads in states like California that are accelerating electrification, utilities do not have access to the market actors who are on the front line of influence to homeowners or review and approve their permits: HERS Raters, assessors, contractors and building departments. General statement of how this problem is being addressed: ConSol will integrate the Home Energy Score™ (HES) to its State of California, approved home energy rating services (HERS) platform (CHEERS) to develop a single tool for contractors nationwide to assess, record and install recommended cost, energy, and emissions saving measures to the 140 million single-family homes throughout the U.S. and 14 million homes in California (CHEERS+HES). The CHEERS high fidelity energy code permitting data will be integrated with HES for simple, accurate, easy-to-use home energy estimation and analysis and will directly gain access to the retrofit and renovations markets with the same upgraded platform. This innovative project will assist the utilities in supporting existing homes in their jurisdictions with HES and develop measures to improve energy efficiency and reduce emissions. How is this problem being addressed? What is the overall project approach? In effort to expand the Home Energy Score™ (HES) by increasing the use of aggregable home energy asset data, ConSol proposes to integrate the DOE HES via Application Programming Interface (API) to its State of California approved home energy rating services platform (CHEERS). Once the CHEERS platform and HES are integrated (CHEERS+HES), this enhanced platform will be instantly available and actively deployed via Phase 1 pilot to HERS Raters, assessors and contractors in California to market-test the solution, understand the rate of adoption and identify opportunities for improvement prior to scaling nationally. The CHEERS high fidelity energy code permitting data will be integrated with HES for simple, accurate, easy-to-use home energy estimation and analysis and will directly gain access to the retrofit and renovations markets with the same upgraded platform. This innovative project will assist the building industry and homeowners with an easy-to-use assessment if energy and carbon impacts of existing homes, and assist the utilities in supporting existing homes in their jurisdictions with HES to improve energy efficiency and reduce emissions. What is to be done in Phase I? During Phase I of this proposed project, ConSol will (1) design software architecture that links CHEERS to the Home Energy ScoreTM via API, (2) solicit partnership from one or more California utilities for a regional pilot, (3) test the new software with its HERS Raters and contractor network in the partnership utility jurisdiction, (4) launch a pilot version of the newly developed software with HERS Raters and contractors in the utility territory, and (5) explore California’s GoGreen energy efficiency homeowner lending program in parallel with the pilot. Commercial Applications and Other Benefits. Summarize the future applications or public benefits if the project is carried over into Phase II or Phase III and beyond. The CHEERS+HES commercialized product will be ready for national market scale following a successful Phase 1 performance. The CHEERS+HES adoption is estimated to reach a 5% adoption growth rate versus the 110,000 baseline, starting in Year 1 after Phase I completion, and continuing each year. As a direct benefit to the DOE, CHEERS will set a goal of 100,000 Home Energy Score assessments for existing home alterations within the first 10 years following Phase 1 performance. The technical benefits of this proposed project include the harmonized, automated, and seamless integration of the DOE HES into the widely used and market leading California energy registry, CHEERS. The social benefits include the aggregate energy, cost and GHG savings by allowing the broader public streamlined access to the CHEERS+HES measurement and the energy efficiency recommended measures that may result. Key Words: Home Energy ScoreTM (HES); Application Programming Interface (API); Home Energy Rating Services (HERS); HERS Raters; contractors; assessors; existing homes, energy asset data; cost, energy, and emissions saving measures; energy code (Title 24) compliance; document repository; utilities; pilot; newly developed software; energy efficiency; homeowner. Summary for Members of Congress: The DOE Home Energy Score™ (HES) is a tool to encourage homeowners to improve their energy performance, lower costs and share energy information but is underutilized and consists of barriers which need to be addressed in order to scale. In effort to expand the HES, CHEERS, Inc. will integrate the HES to its State of California, approved home energy rating services (HERS) platform (CHEERS) to develop a single tool for contractors nationwide to assess, record and install recommended cost, energy, and emissions saving measures to the 140 million single-family homes throughout the U.S. and 14 million homes in California.

Application Programming Interface (API)↗
DOE OSTI2022

Conversion of METL Diagnostic Flowmeters to Permanent Magnet Based Electromagnetic Flowmeters

The Mechanisms Engineering Test Loop (METL) uses three flowmeters to monitor sodium circulation through the main loop, the Cold Trap leg, and the Plugging Meter leg. When constructed, the Cold Trap flowmeter (CTFM) and Plugging Meter flowmeter (PMFM) were equipped with permanent magnets and Hall Sensors. By October of 2019, during normal operations, both the CTFM and PMFM failed, producing either erroneous or zero signals. Repairs to the flowmeters were attempted in January of 2020 but failed to resolve the issues. Therefore, starting in March of 2021, a plan was developed to convert the installed flowmeters to more robust permanent magnet based electromagnetic flowmeters (EMFMs). The Cold Trap EMFM (CT EMFM) and Plugging Meter EMFM (PM EMFM) were fully installed by August of 2021. Initial testing and commissioning were completed in November of 2021. Finally, the first calibration runs were finished in March of 2022. This report discusses the design, conversion, and calibration of the as-built CTFM and PMFM to robust permanent magnet based EMFMs. During the design phase, theoretical models were used to estimate the signal output and required magnet sizes. Then, the CTFM and PMFM were disassembled and converted to EMFMs. After commissioning, the CT EMFM and PM EMFM were calibrated using a ‘Time Transfer Procedure’ carried out with METL Expansion Vessels and Test Vessel Two. The accuracy of the calibration was estimated through an uncertainty analysis. Finally, the report describes some lessons learned for future flowmeter conversions and follow-up work. In total, both METL EMFM’s met the desired performance targets. Testing data showed that the METL EMFMs provide a output signal of roughly 2 mV at 1 GPM and 250 °C. During calibration, flowrates between 0.7 GPM and 2.4 GPM were achieved. In this flow range, calibration coefficients of 0.485 and 0.935 were measured as with errors ranging from 15-5% and 16-5% for the CT EMFM and PM EMFM, respectively. Above 1.5 GPM, the error was assumed to be about 5% for both METL EMFMs. Several points will be considered for future follow-up work on the METL EMFM’s. First, the signal noise issues in the PM EMFM will be addressed. It is likely the source of the noise is due to some stray EMF from a heater. Secondly, the NdFeB magnets will be replaced with a grade that has a Curie temperature above 80 °C. For example, a few grades of NeFeB magnets have Curie temperatures which exceed 150 °C and some SmCo magnets have Curie temperatures as high as 500 °C. Third, more calibration runs will be completed in the range of 0.5-2.5 GPM. This will further improve the accuracy of the calibration coefficient. Fourth, calibration runs will be completed up to 5 GPM. This requires a larger pressure relief valve to be installed on the Expansion Vessel and Test Vessel 2, as well as a revised calibration procedure. Lastly, calibration runs will be completed to account for cold spots in the system, which reduced the inlet temperature of the METL EMFMs. Overall, these points will improve the calibration coefficients derived in this work and also improve the performance of the METL EMFMs.

42 ENGINEERING↗
DOE OSTI2020

Screening IMS Seismic Detections using Dynamic Correlation Processor: Progress report for 2020

LLNL completed the FY20 workplan entailing application of the Dynamic Correlation Processor (DCP) to International Monitoring System (IMS) primary seismic data in 2019 and 2020. The effective analysis period was curtailed to January 1 through November 12, 2019 due to a data compression change that rendered later data unusable. Fixing the data compression error is a priority for our data source, and we plan to extend the period of data analysis when the fix is implemented. We found that the percentage overlap between detections generated by the International Data Centre (IDC) DFX software and detections generated by DCP varied widely by station. Overlap is 30-40% at some stations, suggesting that a large percentage of DFX detections could be screened (removed) from the detection-event association algorithm. However, detection overlap was much lower, a few percent, at many stations and the percentage overlap was low at stations known to have many mines and other local sources of seismicity. Unexpectedly low detection overlap at many stations prompted us to examine results for the ARCES station in detail. There is considerable mine activity near ARCES, but our initial FY20 analysis found only ~2% DCP/DFX detection overlap. Differences in the pre-processing (e.g. beam recipes) used by DCP and DFX appear to be the cause of low detection overlap at ARCES. DCP uses wideband filters to improve detector robustness and the IDC uses narrow-band pre-filtering to improve sensitivity. After reprocessing ARCES using the IDC beam recipe, DCP/DFX overlap increased to ~74%. This result shows that we must reprocess the IMS network using the IDC station-specific beam recipes if we are to effectively screen DFX detections and improve automatic event building performance at the IDC.

58 GEOSCIENCES↗
DOE OSTI2020

The Cost of Floating Offshore Wind Energy in California Between 2019 and 2032

California’s energy planning is centered around meeting the emissions reduction and renewable energy requirements of Senate Bill 350 by 2030. However, state power system planning is expected to eventually address California’s requirement to achieve 100% of total retail electricity sales from renewable energy and zero-carbon resources by 2045, as mandated by Senate Bill 100. To comply with these directives, California needs to investigate the further development of energy efficiency, storage, and a diverse range of renewable energy, zero-carbon emission, and transmission resources, including offshore wind. Wind resources off the coast of California have the potential to generate a significant portion of the state’s electric energy as it moves toward a zero-carbon economy and can help diversify its energy mix. Floating offshore wind technology, which is suitable for the deep waters along the California coast, is currently in a precommercial phase, with approximately 84 megawatts (MW) installed worldwide at the end of 2019. Globally there are over 7,000 MW in planning and permitting phases of development, with the first commercial-scale projects expected to be operational in 2024. This study provides site-specific cost and performance data for floating offshore wind to inform California’s long-term energy planning. The identification of new resources to meet California’s policy goals at least cost is part of the Integrated Resource Planning (IRP) process, which is coordinated by the California Public Utilities Commission (CPUC). In 2019–2020 IRP modeling, offshore wind was included for the first time as a candidate resource in some sensitivity cases (CPUC 2019). The data and information presented in this report can be used to update offshore wind inputs in future IRP cycles. The authors conducted a geospatial cost analysis over portions of the offshore wind resource area of California. The analyzed spatial domain includes sites with a mean wind speed of at least 7 meters per second and water depths between 40 meters (m) and 1,300 m. Costs and energy production vary across this analysis domain. We calculated these parameters on a grid layout with over 750 sites, with each site representing a 1,000-MW commercial offshore wind power plant. Levelized cost of energy (LCOE) was calculated at each site over the analysis domain. The resulting variation in LCOE across the analysis domain is illustrated through heat maps in this report. Five study areas were selected within the analysis domain where more detailed cost analysis was conducted and cost parameters, such as annual energy production, capital cost expenditures (CapEx), operational cost expenditures (OpEx), and net capacity factors are reported. These five study areas include Morro Bay, Diablo Canyon, Humboldt, Cape Mendocino and Del Norte.

17 WIND ENERGY↗
DOE OSTI2026

Tandem Photovoltaics Core Program Final Technical Report

The Tandem Photovoltaics Core Program was a multi-year initiative aimed at advancing hybrid tandem solar cell technologies to enhance solar module efficiency beyond the limits of single junction devices. This project focused on the development, testing, and scaling of prototype photovoltaic devices, with the goal of achieving commercial relevance and driving industry adoption. The work was divided into three tasks: 1) Comparative Analysis of Tandem Technologies: This task focused on quantifying energy yield under real-world conditions and assessing economic viability of tandems relative to silicon-based modules. The project's modeling framework incorporated performance data, cost of materials, and manufacturing process impacts to optimize tandem designs 2) Tandem Integration and Prototyping: In this task, we developed innovative tandem designs by combining metal halide perovskite (MHP) top cells and silicon (Si) bottom cells. The project focuses on both mechanical integration and direct deposition techniques to enable compatibility with commercially relevant Si technologies, such as passivated contact or PERC cells. 3) Scale-up and Reliability: This task addressed the challenges of large-area fabrication by developing scalable deposition methods and robust interconnection schemes for tandems. The project looked at different accelerated testing such as thermal cycling, damp heat exposure, and potential induced degradation, to ensure long-term stability of devices in field conditions. Tandem solar cells can greatly increase module efficiency beyond conventional single junction (SJ) devices, which are approaching their theoretical limit. There are many ways to fabricate a tandem cell or module in terms of materials used, configuration, and terminal connection. This SETO core project focused critical factors in enabling tandems to enter the market, including hardware integration, technoeconomic analysis (TEA), and energy yield analysis. We focused on MHP/Si hybrid tandem solar cells and modules as a model system for their versatility in module design comparisons, providing valuable insights for other tandem options. While champion cells with areas <1cm2 are regularly demonstrated by groups around the world, it is significantly more challenging to translate these advances into modules, and fewer institutions and companies are working at the module level. This project addressed questions about module fabrication, testing, and reliability that are hard to answer without actually fabricating prototypes. We also performed analysis and road-mapping activities to understand the potential for a wider variety of tandems, including all-perovskite tandems fabricated in collaboration with the Perovskite PV core program. Detailed technical results from this project are described for each task in Section 7.

14 SOLAR ENERGY↗
DOE OSTI2022

Divertor Component Testing

Power exhaust is an immense challenge in tokamaks. Commonwealth Fusion Systems (CFS), in collaboration with MIT and others, is working on the design of a compact (R 0 = 1.85 m), high-field (B 0 = 12 T) tokamak for the demonstration of net fusion energy, called SPARC. Empirical scaling laws indicate that the unmitigated heat flux in the boundary plasma will exceed 10 GW/m 2 . Such high heat fluxes will be a formidable challenge. The scope of this work is to utilize the HHF testing expertise maintained by ORNL, used in support of NSTX-U and to demonstrate the thermal performance of tungsten-coated graphitic foam targets, to help CFS and its collaborators to assess the performance of (1) base materials (tungsten and its alloys) and (2) divertor mockups under SPARC-like divertor heat flux conditions. These activities will be performed by ORNL personnel using electron beam exposure facilities at the Pennsylvania State University’s Applied Research Laboratory (ARL). ARL is a Department of Defense University Affiliated Research Center where ORNL has successfully executed NSTX-U and graphitic foam high heat flux testing using electron beam (e-beam) facilities, which is a nonstandard service. For the assessment of base materials, CFS will do an initial thermal analysis, in consultation with ORNL, to understand under what scenarios the materials are most likely to fail. CFS will supply to ORNL various tungsten-based material samples to test with testing taking 3 weeks. ORNL will thermally stress the samples under SPARC divertor-like conditions to either failure or to a prescribed number of pulses. ORNL will record experimental data, including IR surface temperature and embedded thermocouple readings, and report results to CFS

36 MATERIALS SCIENCE↗
DOE OSTI2021

Argonne Leadership Computing Facility: 2021 Operational Assessment Report

This Operational Assessment Report describes how the Argonne Leadership Computing Facility (ALCF) met or exceeded every one of its goals for calendar year (CY) 2021 as an advanced scientific computing center. In CY 2021, the ALCF operated its production resource, Theta, an Intel-based Cray XC40 system (11.7-petaflops) augmented with 24 NVIDIA DGX A100-based nodes (3.9-petaflops) that supports diverse workloads, integrating data analytics with artificial intelligence (AI) training and learning in a single platform. In 2021, we began deploying Polaris, our newest 40- petaflops system, and augmented this powerful testbed system with an additional 28 nodes to support the integration of real-time experiments and HPC resources. We also deployed our two largest storage systems yet, named Grand and Eagle, that will bring new services to our users and will power data-driven research for years to come. Last year, Theta delivered a total of 20.8 million node-hours to 16 Innovative and Novel Computational Impact on Theory and Experiment (INCITE) projects and 7.2 million node-hours to ASCR Leadership Computing Challenge (ALCC) projects (32 awarded during the 2020–2021 ALCC year and 17 awarded during the 2021–2022 ALCC year), as well as substantial support to Director’s Discretionary (DD) projects (5.5 million node-hours). As Table ES.1 shows, Theta performed exceptionally well in terms of overall availability (95.1 percent), scheduled availability (99.4 percent), and utilization (98.1 percent; Table 2.1). As of the submission date of this document, ALCF’s user community has published 249 papers in high-quality, peer-reviewed journals and technical proceedings. At the 2021 International Conference for High Performance Computing, Networking, Storage and Analysis (SC’21), Argonne researchers won two HPCwire Readers’ Choice Awards and were part of a Gordon Bell Prize finalist team recognized for developing an AI-enabled, multi-resolution simulation framework for studying complex biomolecular machines. Their framework was used to observe the SARS-CoV-2 replication-transcription machinery in action, by directly integrating experimental data. ALCF also provided a comprehensive program of high-performance computing (HPC) support services to help our community make productive use of the facility’s diverse and growing collection of resources. We are now entering the exascale era, with exascale machines being planned for national laboratories across the country, including Aurora at Argonne National Laboratory (Argonne) in 2023. ALCF researchers have been leading and guiding numerous strategic activities that will push the boundaries of what’s possible in computational science and engineering and allow us to deliver science on day one.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

ECP ST Capability Assessment Report (CAR) for VTK-m (FY20)

The ECP/VTK-m project is providing the core capabilities to perform scientific visualization on Exascale architectures. The ECP/VTK-m project fills the critical feature gap of performing visualization and analysis on processors like graphics-based processors. The results of this project will be delivered in tools like ParaView, Vislt, and Ascent as well as in stand-alone form. Moreover, these projects are depending on this ECP effort to be able to make effective use of ECP architectures. One of the biggest recent changes in high-performance computing is the increasing use of accelerators. Accelerators contain processing cores that independently are inferior to a core in a typical CPU, but these cores are replicated and grouped such that their aggregate execution provides a very high computation rate at a much lower power. Current and future CPU processors also require much more explicit parallelism. Each successive version of the hardware packs more cores into each processor, and technologies like hyper threading and vector operations require even more parallel processing to leverage each core's full potential. VTK-m is a toolkit of scientific visualization algorithms for emerging processor architectures. VTK-m supports the fine-grained concurrency for data analysis and visualization algorithms required to drive extreme scale computing by providing abstract models for data and execution that can be applied to a variety of algorithms across many different processor architectures. The ECP/VTK-m project is building up the VTK-m codebase with the necessary visualization algorithm implementations that run across the varied hardware platforms to be leveraged at the Exascale. We will be working with other ECP projects, such as ALPINE, to integrate the new VTK-m code into production software to enable visualization on our HPC systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Subcritical Californium Source Drive Noise Analysis Measurements With Unreflected Uranium (93.15) Hydride

On July 6, 1989, subcritical californium source-driven noise analysis (CSDNA) measurements were performed with bare uranium hydride cylindrical assemblies at the Los Alamos National Laboratory Critical Experiments Facility in KIVA 1. Three configurations of ~7.5 cm radius-enriched (93.15 wt. % 235 U) uranium hydride with a density of ~10 g/cm 3 cylinders were assembled with uranium hydride heights of ~11, ~14, and ~16 cm. The uranium hydride (~2 and ~3 cm high) was in thin-welded stainless steel cans. The neutron multiplication factors obtained on-line from the measured ratios of spectral densities were 0.942 ± 0.002, 0.917 ± 0.003, and 0.867 ± 0.004 for uranium hydride heights of ~16, ~14, and ~11 cm., respectively. Neutron multiplication factors for these three configurations calculated by Los Alamos National Laboratory Monte Carlo methods were 0.952 ± 0.005, 0.922 ± 0.005, and 0.860 ± 0.005, all of which are in good agreement with the measurements. The break frequency noise analysis data could be fitted to obtain the prompt neutron decay constant at all subcritical states. Some data presented in this report are from notes that are not in the logbooks. A discussion of the two different point kinetics theories of the measurements that illustrated the deficiencies of the rigorous theory at low neutron multiplication factors (k eff < 0.80) is given in an Appendix. These measurements may be the only configuration of unreflected, highly enriched uranium hydride configuration assembled. The presence of hydrogen diluted the uranium density, decreasing the reactivity, but this is offset by slowing down the neutron energy to the energy ranges of higher-fission cross sections. Extrapolations to delayed critical indicate that adding one more 3 cm can and one more 2 cm can would result in the unreflected cylindrical system being slightly above critical with a critical mass of ~37 kg, which is considerably less than the critical mass of an unreflected and unmoderated highly enriched uranium metal sphere. An unreflected, highly enriched uranium hydride sphere would have a critical mass less than 37 kg.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Deep Direct-Use Geothermal Feasibility Study for Hawthorne NV

The Hawthorne Nevada, deep direct-use geothermal study is a two-year effort funded by the U.S. Department of Energy to determine the techno-economic feasibility of implementing a large-scale, direct-use facility for the Hawthorne Army Depot (HAD) and the public facilities of the city of Hawthorne and Mineral County. The approach links a production side analysis (PSA) and a demand side analysis (DSA) into a whole-system analysis (WSA) to provide an integrated assessment of the resource and the probability of delivering economically viable direct-use energy to Hawthorne. Hawthorne, Nevada is in the western part of the Basin and Range province and has been the focus of geothermal investigations for over 40 years. Over the last 15 years, several studies completed by the U.S. Navy Geothermal Program Office (GPO) in conjunction with industry professionals quantified the existence of several low temperature geothermal prospects, the most promising of which is called Prospect A. The promise of Prospect A is based on drilling and flow testing that produced ~100 °C water at flow rates of up to 31 l/s (500 gallons per minute). Measured productivity indexes range from 40-85 l/s/MPa, suggesting a warm and productive heat source. Despite the promise of the resource, uncertainties in its spatial extent and long-term sustainability mean that techno-economic analyses must include probabilities of the sustainability of the resource under different operating scenarios. Here, the PSA is conducted by integrating a wide range of disparate data to estimate lognormal P90, P50, and P10 resource capacities. These capacities are used as input to a thermal-hydrologic (T-H) model to estimate thermal drawdown for each capacity estimate for several different DSA scenarios. Using a systems-based approach, the WSA links the dynamic T-H simulations of the PSA/DSA combinations with the techno-economic model GEOPHIRES to account for both the temporal dynamics and uncertainties in the system to produce probabilistic distributions of several performance metrics including the levelized cost of heat (LCOH) and the return on investment (ROI). This report is the final delivery for the project and documents the study's activities and results.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Application of NEAMS Multiphysics Framework for Species Tracking in Molten Salt Reactors

This report from Idaho National Laboratory (INL) summarizes the key modeling and simulation activities conducted under the Department of Energy (DOE) Molten Salt Reactor (MSR) Campaign during the Fiscal Year 2023 (FY23). The focus of the work was to leverage state-of-the-art modeling capabilities from the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) codes to enable novel multiphysics and multiscale modeling and simulation of MSRs. Through collaboration with NEAMS code developers, advanced multiphysics analysis capabilities for MSR systems were demonstrated by coupling depletion, thermal-hydraulics, and thermochemistry into an innovative framework for chemical species transport in MSRs. As a result, the framework can track nuclides throughout their lifetimes in the core, from production (depletion) to advection throughout the salt volume (thermal-hydraulics) and off-gassing or precipitation outside of the salt (thermochemistry). This work supports the near-term deployment of MSRs by integrating the synergistic efforts between the DOE’s MSR Campaign and NEAMS program. The resulting framework will help better connect system design modelers with experimentalists to better understand and predict complex physical behaviors in MSRs. Researchers and MSR developers alike can now leverage these new modeling and simulation capabilities to perform novel analyses with applications including: • MSR dynamics during normal operational transients and accident scenarios • Off-gas system design and performance for fuel cycle and depletion analysis • Corrosion and active chemistry control for reactor component health and lifetime determination • Source term, decay heat and activity determination in accident scenarios • Special nuclear material accountancy and chemical forensic analysis for safeguards • Digital twin development of experiments and experimental reactor demonstrations • Measurement requirements for instrumentation and control design • Uncertainty and sensitivity analysis of missing data to inform future experimental data collection.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Assessment of Cloud-Based Applications Enabling a Scalable Risk-Informed Predictive Maintenance Strategy Across the Nuclear Fleet

The current light water reactor fleet uses time-based or failure-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging technologies in terms of artificial intelligence (AI) and cloud computing to enable a cost-effective, predictive maintenance strategy. This report examines the feasibility of cloud computing for the nuclear industry’s needs in terms of the cloud’s computing capabilities, feasibility, and regulatory concerns. The technical viability of cloud computing was analyzed using one year worth of data from a boiling water reactor’s safety relief valve. Models were hosted on a local desktop, Idaho National Laboratory’s high-performance computer, and Microsoft Azure. Data was loaded, processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was used to determined that cloud computing has adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, there is a benefit as the plant no longer needs manage their own servers, software, cybersecurity, and IT support staff. Many of these features can be offloaded on to the cloud provider. A comprehensive analysis was completed that showed the current annual cost of operating is more expensive than using cloud computing resources. Lastly, the regulatory framework does not explicitly address AI or autonomous control. Currently, the NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than new regulations to address the use of AI and ML. But since many of the AI applications are focused on non-safety related applications, such as balance-of-plant components, they will likely have little or no regulatory restrictions or necessary approvals. Demonstrating how AI can improve maintenance and operation of these non-safety related systems seems like the likely path forward for implementing AI and cloud computing resources inside nuclear power plants (NPPs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Imagery Applications for Advanced Event Analytics (WBS 24.3.1.3.3-IDC FY202 Final Project Report)

Accurate event locations and replicability of location analyses are essential for assessing the nature of an event, its context, ambient site conditions, and proximity to relevant facilities and infrastructure. Additionally, accurate event locations provide valuable information that reduce uncertainties, improve confidence in event analyses, and inform in-field verification activities. However, event location/relocation and replicability are difficult due to a number of factors, including spatially-sparse network coverage in some areas of the globe and variability in seismic data processing. This team proposed that the incorporation of high-fidelity imagery as a data backbone to the analytical assessment of a suspected underground explosion and/or an advanced seismic event bulletin produced by the International Data Centre (IDC) of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO PrepCom) could reduce uncertainties and improve confidence in analyses. Specifically, temporally-separated images can reduce uncertainty by identifying areas where change has occurred (e.g., building construction or demolition, road or facilities improvements). The primary goal of this project was to develop an automated geospatial processing script for imagery change detection to better reflect needs of the technical community (including the IDC) and to make the use of such a tool accessible in a variety of settings across platforms. Technical experts at Los Alamos National Laboratory successfully built GAIA: the Geospatial Automated Imagery Analysis tool, to fill this need. GAIA combines five tool components to produce orthorectified time separated imagery and imagery change detection maps. Our toolkit (1) reduces error by providing a standardized workflow for image analyses and (2) significantly reduces processing time from between 7 and 24+ hours to approximately 5 minutes. Technical experts at Sandia National Laboratories supported GAIA via beta-testing and by introducing a web-based system approach for increased applicability. To test the function, performance, broad application, and ease-of-use of GAIA, we applied it to four separate test cases. The results of this preliminary investigation show promise in reducing uncertainty in seismic event locations: if satellite imagery can show regions where operations that produce seismic activity likely occurred, then pursuing imagery to locate epicenters of seismic nuclear events could reduce the time needed to find the true epicenter location.

58 GEOSCIENCES↗
DOE OSTI2023

Leaf Nitrogen, Leaf Mass Area, Leaf Water Content, Seward Peninsula, Alaska, 2017

Nitrogen and carbon content, leaf mass per area and leaf water content of leaves sampled from the NGEE Arctic Teller study site, Seward Peninsula, Alaska in 2017. Data is included for 13 species from the deciduous shrub, forb and graminoid plant functional types. See related dataset for leaf reflective spectra, sample photographs and dGPS locations. This data package includes leaf sample information and trait data (*.csv). Note that leaf nitrogen content analysis was performed on a subset of samples. Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA103_flmd.csv. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Imagery Applications for Advanced Event Analytics (WBS 24.3.1.3.3-IDC FY2020 Final Project Report)

Accurate event locations and replicability of location analyses are essential for assessing the nature of an event, its context, ambient site conditions, and proximity to relevant facilities and infrastructure. Additionally, accurate event locations provide valuable information that reduce uncertainties, improve confidence in event analyses, and inform in-field verification activities. However, event location/relocation and replicability are difficult due to a number of factors, including spatially-sparse network coverage in some areas of the globe and variability in seismic data processing. This team proposed that the incorporation of high-fidelity imagery as a data backbone to the analytical assessment of a suspected underground explosion and/or an advanced seismic event bulletin produced by the International Data Centre (IDC) of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO PrepCom) could reduce uncertainties and improve confidence in analyses. Specifically, temporally-separated images can reduce uncertainty by identifying areas where change has occurred (e.g., building construction or demolition, road or facilities improvements). The primary goal of this project was to develop an automated geospatial processing script for imagery change detection to better reflect needs of the technical community (including the IDC) and to make the use of such a tool accessible in a variety of settings across platforms. Technical experts at Los Alamos National Laboratory successfully built GAIA: the Geospatial Automated Imagery Analysis tool, to fill this need. GAIA combines five tool components to produce orthorectified time-separated imagery and imagery change detection maps. Our toolkit (1) reduces error by providing a standardized workflow for image analyses and (2) significantly reduces processing time from between 7 and 24+ hours to approximately 5 minutes. Technical experts at Sandia National Laboratories supported GAIA via beta-testing and by introducing a web-based system approach for increased applicability. To test the function, performance, broad application, and ease-of-use of GAIA, we applied it to four separate test cases. The results of this preliminary investigation show promise in reducing uncertainty in seismic event locations: if satellite imagery can show regions where operations that produce seismic activity likely occurred, then pursuing imagery to locate epicenters of seismic nuclear events could reduce the time needed to find the true epicenter location.

58 GEOSCIENCES↗