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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Evaluation of Oak Ridge National Laboratory Health Physics Research Reactor Operation Data for Critical Benchmark Creation

The Oak Ridge National Laboratory (ORNL) Health Physics Research Reactor (HPRR) was a research reactor designed and built at ORNL in 1961. The critical assembly used a highly enriched uranium and molybdenum alloy as the fuel and could be operated in steady-state or burst modes. The HPRR has recently been the object of an investigation to create a criticality benchmark. Such benchmarks are very important, as they are used primarily to show the accuracy of newly developed modeling codes and to help experimental validation and reactor licensing. The evaluated experiments considered in this paper were carried out between 1974 and 1986 from various HPRR activities such as steady-state subcritical, steady-state critical, and burst prompt super-critical operations of the reactor for dosimetry, irradiation, or training purposes. By using the HPRR experimental logbook information and the as-built drawings of the critical assembly, a highly detailed model of the HPRR was created with SCALE 6.2.4/KENO-VI, and a first version of a critical benchmark of the HPRR was developed following the International Criticality Safety Benchmark Evaluation Project (ICSBEP) guidelines for thorough description and uncertainty/sensitivity quantification. Unfortunately, in most of the evaluated experiments, the obtained difference between calculated and experimental k eff is around 1,000 pcm, corresponding to a relative error of approximately 1%, beyond the quality standards of the ICSBEP recommending a relative error below 0.1%. Moreover, the derived experimental uncertainty is high, around 4% relative, mainly due to the U-Mo fuel density uncertainty, but also from numerous other factors. For these reasons, the creation of a valuable critical benchmark from HPRR operation data is thus far compromised. In this paper, the different steps of the experiments’ evaluation are summarized, and the reasons for the experimental/calculation discrepancies and potential ways to solve them are explored. This paper also aims to remind us always to exercise considerable care when performing experimental work, and to record all the data possible for potential future uses.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Current Progress of the Final Design of a Subcritical Assembly at the Oak Ridge National Laboratory

During the past decade, the US Department of Energy (DOE)/National Nuclear Security Administration (NNSA) Nuclear Criticality Safety Program (NCSP) has been coordinating nuclear criticality safety (NCS) courses to provide training and qualification to new staff, supervisors, managers, regulators, and other professionals involved with NCS. To address the growing need for more NCS training possibilities, a subcritical assembly was designed at Oak Ridge National Laboratory (ORNL). The Oak Ridge Subcritical Assembly (ORSA), operated at ORNL, could be used in a new course for fissile material handlers/operators or as a backup training facility for currently existing NCSP hands-on NCS training. This paper describes some of the design steps necessary for obtaining a final ORSA design, beginning with a successful feasibility study performed in 2020. Numerous parameters within each main element of the assembly were considered, such as the reflector used, the type of fuel coating or plating used, and the number of fuel plates used. The design choices related to each parametric study described in this paper are detailed and justified at the end of each subsection. An overview of the current final design characteristics of ORSA and the experiments’ possibilities is also provided. ORSA will be built with fuel plates from legacy Aerojet General Nucleonics (AGN)-201M research reactors currently stored at the Y-12 National Security Complex (Y-12). The cylindrical fuel plates comprise UO 2 particles embedded in polyethylene and have a nominal enrichment of 19.5 ± 0.5 wt % 235 U. The basis for the final design was the feasibility study from 2020. In the feasibility study, ORSA achieved k eff = 0.95, corresponding to a multiplication factor of 20, with approximately 620 g of 235 U (four 4 cm plates, three 2 cm plates, and two 1 cm plates) and an 8.5 cm thick graphite reflector radially and on top of the assembly. The bottom of the assembly has a graphite thickness of 5 cm, and the chosen graphite density was 2.3 g/cm 3 . All design calculations were performed using SCALE 6.2.4 KENO-VI and with the ENDF/B VII.1 Continuous Energy cross-section library.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Finite Element Analysis (FEA) for Water-Foam Fracturing of Granite Rock

In addition to the foam data that were obtained from literature and that were collected from the current study, simulation data was also generated from finite element analysis (FEA) conducted in this study using COMSOL Multiphysics software. The FEA models were built to simulate the experiments conducted at Oak Ridge National Laboratory (ORNL) on cement and granite samples. In these FEA models, temperature was kept at ambient while the pressure profile resembled the loading conditions during the ORNL experiments, where pressure was either monotonically increased or applied cyclically. The cement material was used as a model material and was used to study Von Mises stress and tensile stress distribution for different bore hole length geometry using a parametric sweep with water as fracturing fluid using solid-fluid interaction module. For the granite material, FEA models were developed for stress analysis of cylindrical samples with water or foam fluids. The solid mechanics module in COMSOL was implemented to solve for Von Mises stress and tensile stress. The fluid-structure interaction module was implemented to solve for water-foam interaction on granite cylinder with addition of fluid-loading on structure, i.e., large deformation in solid mechanics with no impact on fluid deformation. Foam was considered as a pseudo single-phase compressible fluid for which material properties were calculated from water and gas (nitrogen) phases. The density of foam is calculated as a function of the densities of water and nitrogen, while viscosity is a function of temperature. Four types of FEA analyses were modelled: 1. Monotonic injection with water 2. Monotonic injection with foam 3. Cyclic injection with water 4. Cyclic injection with foam All the COMSOL files are converted to a zip file which is save in .mph.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

WHONDRS River Corridor Sediment and Water Geochemistry and In Situ Sensor Data from Machine-Learning-Informed Sites across the Contiguous United States (v6)

This dataset supports a broader study examining hyporheic zone respiration rates to improve predictive models at a contiguous United States (CONUS) scale. The CONUS-Scale Model-Sample Study (CM) was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Sampling began in April 2022 and ended in October 2023. In addition to the widely distributed CONUS sites, a more spatially focused sampling occurred in the Yakima River Basin, WA in summer 2022. Data from this more spatially intensive sampling occurred under the label “Second Spatial Study (SSS)” and were also included in the machine learning models. Other data types collected from SSS that were not part of CM were published in a separate data package (https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566). This data package was originally published in February 2023. It was updated in June 2023 (v2; new and modified files); December 2023 (v3; new and modified files); June 2024 (v4; new and modified files); April 2024 (v5; new and modified files); and September 2025 (v6; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of two folders of field photos and videos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocols; (7) a subfolder with sample data; and (8) a subfolder with sensor data. The sample data subfolder contains (1) surface water and sediment dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) surface water and sediment total nitrogen data and averages; (3) surface water major cations and anions and averages; (4) sediment grain size data; (5) sediment iron (II) data and averages; (6) wet sediment mass, dry sediment mass, water mass, and wet sediment volume in incubation and sediment ICR vials; (7) sediment incubation respiration rate data and averages; (8) normalized respiration rate data and averages; (9) methods codes; (10) sediment specific surface area; (11) sediment percent carbon and nitrogen; (12) sediment gravimetric moisture and averages; (15) sediment X-ray diffraction (XRD) data; (16) sediment adenosine triphosphate (ATP) and averages; (17) a subfolder with sediment incubation respiration data, scripts, and plots; (18) surface water and sediment FTICR methods; and (19) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains five subfolders, one containing the sediment .xml data files, one containing the water .xml files, one containing the sediment CoreMS output files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS).The sensor data subfolder contains (1) a subfolder with miniDOT dissolved oxygen and temperature data and plots; (2) miniDOT dissolved oxygen and temperature summary data; and (3) miniDOT installation methods. All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4. CORRECTION: Carbon and nitrogen content are reported as percentages. The current column headers "01395_C_percent_per_mg" and "01397_N_percent_per_mg" are incorrect. These should read "01395_C_percent" and "01397_N_percent" and will be corrected in the next version of this data package. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Model America: Data and Models for every U.S. Building

The 5-year goal of the “Model America” concept was to generate a model of every building in the United States. This data repository delivers on that goal with "Model America v1". Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM). There were 125,715,609 buildings detected in the United States. Of this number, 122,146,671 (97.2%) buildings resulted in a successful generation and simulation of a building energy model. This dataset includes the full 125 million buildings. Future updates may include additional buildings, data improvements, or other algorithmic model enhancements in "Model America v2". This dataset contains OSM and IDF zip files for every U.S. county. Each zip file contains the generated buildings from that county. The .csv input data contains the following data fields: 1. ID - the Unique Building Identifier (UBID), generated using the Pacific Northwest National Laboratory (PNNL) BuildingID framework 2. Centroid - building center location in latitude/longitude (from Footprint2D) 3. Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...) 4. State_abbr - state name 5. Area - estimate of total conditioned floor area (ft2) 6. Area2D - footprint area (ft2) 7. Height - building height (ft) 8. NumFloors - number of floors (above-grade) 9. WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) 10. CZ - ASHRAE Climate Zone designation 11. BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards 12. Standard - building vintage This data is made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD), U.S. Dept. of Energy’s (DOE) Building Technologies Office (BTO), Office of Electricity (OE), Biological and Environmental Research (BER), and National Nuclear Security Administration (NNSA). Update (September 23, 2025): We corrected the ID field in all state-level.csv input files to ensure one-to-one consistency with the corresponding .osm and .idf output files. The schema and file structure are unchanged; only the values in the ID column were modified. No files were added or removed, and the .zip bundles (containing .osm / .idf) are unchanged. The corrected .csv inputs were re-extracted in March 2025 from the original data generated ~ 2021 (Theta supercomputer runs), and published here to align input IDs with model outputs. Update (September 6, 2026): The Model America dataset was updated to replace the previous building ID field with the Unique Building Identifier (UBID), using the Pacific Northwest National Laboratory (PNNL) BuildingID framework. UBIDs provide standardized, location-based identifiers for individual building footprints and improve interoperability with other building and geospatial datasets. The data files containing the previous building identifiers were updated to include UBIDs. This update standardizes building identification; the underlying Model America building characteristics and energy simulation results were not recomputed as part of this update.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Machine learning model inputs, outputs, and scripts associated with “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions” (Malhotra et al., in prep). This effort was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the contiguous United States (CONUS). New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Associated sediment and water geochemistry and in situ sensor data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689, https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719, and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1603775. This data package is associated with two GitHub repositories found at https://github.com/parallelworks/dynamic-learning-rivers and https://github.com/WHONDRS-Hub/ICON-ModEx_Open_Manuscript. In addition to this readme, this data package also includes two file-level metadata (FLMD) files that describes each file and two data dictionaries (DD) that describe all column/row headers and variable definitions. This data package consists of two main folders (1) dynamic-learning-rivers and (2) ICON-ModEx_Open_Manuscript which contain snapshots of the associated GitHub repositories. The input data, output data, and machine learning models used to guide sampling locations are within dynamic-learning-rivers. The folder is organized into five top-level directories: (1) “input_data” holds the training data for the ML models; (2) “ml_models” holds machine learning (ML) models trained on the data in “input_data”; (3) “examples” contains files for direct experimentation with the machine learning model, including scripts for setting up “hindcast” run; (4) “scripts” contains data preprocessing and postprocessing scripts and intermediate results specific to this data set that bookend the ML workflow; and (5) “output_data” holds the overall results of the ML model on that branch. Each trained ML model resides on its own branch in the repository; this means that inputs and outputs can be different branch-to-branch. There is also one hidden directory “.github/workflows”. This hidden directory contains information for how to run the ML workflow as an end-to-end automated GitHub Action but it is not needed for reusing the ML models archived here. Please see the top-level README.md in the GitHub repository for more details on the automation. The scripts and data used to create figures in the manuscript are within ICON-ModEx_Open_Manuscript. The folder is organized into four folders which contain the scripts, data, and pdf for each figure. Within the “fig-model-score-evolution” folder, there is a folder called “intermediate_branch_data” which contains some intermediate files pulled from dynamic-learning-rivers and reorganized to easily integrate into the workflows. NOTE: THIS FOLDER INCLUDES THE FILES AT THE POINT OF PAPER SUBMISSION. IT WILL BE UPDATED ONCE THE PAPER IS ACCEPTED WITH ANY REVISIONS AND WILL INCLUDE A DD/FLMD AT THAT POINT. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Report from the Inaugural Meeting on the Opportunities at the SEEMS Facility June 11-12, 2019

The Inaugural Meeting on the Opportunities at the Single Event Effects—Muon Spectroscopy (SEEMS) facility was held June 11–12, 2019, at Oak Ridge National Laboratory (ORNL). Capabilities of the SEEMS facility concept were reviewed, with emphasis on particle beams for single event effects (SEE) testing of electronic devices (integrated circuits) and systems—a topic of growing interest and concern in aerospace avionics, satellites, supercomputing, autonomous cars, unmanned aerial vehicles and more. Participants from these industries and their regulators attended. A clear consensus on the growing and urgent need for SEE test capabilities like those offered by SEEMS was expressed. Subsequent to the meeting, letters of support for SEEMS were sent by The Boeing Company and Honeywell to the ORNL Laboratory Director, Thomas Zacharia.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Solidification of REDC Organics and Airborne Release Fraction Measurements

The Radiochemical Engineering Development Center (REDC) generates various liquid organic wastes from processing irradiated targets to recover heavy elements. In the past, these organics were discharged to the Oak Ridge National Laboratory (ORNL) liquid low-level waste (LLLW) system, along with the aqueous waste. Because of a reduction in aqueous LLLW from other ORNL generators and an increase in the radionuclide concentration, particularly 238 Pu, in the organic waste stream, the organics can no longer be discharged to the LLLW system. The plan is to solidify the liquid organic waste for disposal as solid debris waste. The documented safety analysis for REDC uses an airborne release fraction of 5 x 10 -4 with a respirable fraction of 0.2 for plutonium and other actinides from packaged solid debris waste during a fire scenario, for an overall airborne release fraction/respirable fraction of 10 -4 . Solidifying the organic liquids, either by using PM-199 Organoclay ® or by grouting, would produce solid waste forms with no free liquid, which should qualify for disposal at the Waste Isolation Pilot Plant. The use of Organoclay would be much simpler to implement inside a hot cell. Granular Organoclay can be added to the organic waste solutions until there is a dry layer on top of the liquid and then allowed to cure for a few hours. Grouting the liquids would require using multiple ingredients and mixing steps. Both methods produced waste forms that trapped cerium, as a surrogate for plutonium, inside the waste, with airborne release fractions during fire scenario tests of well below the 10 -4 limit.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Commercialization of Big Area Additive Manufacturing (CRADA NFE-16-06083 Final Report)

Oak Ridge National Laboratory (ORNL) first partnered with Cincinnati Incorporated (CI) through a Cooperative Research and Development Agreement (CRADA) (NFE-14-04957) in 2014 to demonstrate the feasibility and viability of Big Area Additive Manufacturing (BAAM). The first CRADA was a success and paved the way for large format additive manufacturing (LFAM). ORNL and CI partnered again for this second CRADA (NFE-16-06083) to improve process control, enhance printing capabilities, and shift towards production capability.

42 ENGINEERING↗
DOE OSTI2020

Electrical Safety Practices Developed for Automotive Lithium Ion Battery Dismantlement

ORNL is developing electrical safety practices for handling and disassembling automotive lithium ion batteries in a research environment. Online literature searches did not reveal any standard electrical safety practices for disassembling lithium ion battery stacks from automobiles. Until recently, there has been insufficient motivation to recycle or refurbish spent automotive lithium ion batteries due to limited volumes entering the secondary market. However, a growing volume of spent lithium ion batteries are beginning to collect in automobile salvage yards, recycling facilities, landfills, and other places due to a shortage of economically and environmentally viable end-of-life options. ORNL studied automotive battery pack, module, and cell dismantlement to understand the risks, hazards, and controls necessary to perform dismantlement safely and economically. Packs, modules, and cells were manually taken apart, while wearing appropriate personal protective equipment, with insulated hand tools. These dismantlement studies point out the hazards and risks associated with dismantling automotive lithium ion batteries and describe practices for controlling such hazards and risks while demonstrating the controls through a case study of a first-generation Chevrolet Volt battery pack.

25 ENERGY STORAGE↗
DOE OSTI2020

Involute Working Group – Validation of CFD Turbulence Models for Steady-State Safety Analysis

There are three research reactors in the world having fuel plates curved as circle-involute (a spiral generated around a circle): The Oak Ridge National Laboratory (ORNL) High Flux Isotope Reactor (HFIR) located in Tennessee, U.S.A. [ORNL, 2018]; The Laue-Langevin Institute (ILL) High Flux Reactor (RHF) located in Grenoble, France [ILL, 2018]; and, The Technical University of Munich (TUM) Research Neutron Source Heinz Maier-Leibnitz (FRM II) located in Garching, Germany [TUM, 2018]. All three reactors are currently using Highly Enriched Uranium (HEU, 235U/U ≥ 20 wt. %) as fuel and all three are actively engaged in activities to convert to Low Enriched Uranium (LEU, 235U/U < 20 wt. %) fuel. More information on these reactors can be found in Section two. For various reasons, these reactors have expressed interest in using Computational Fluid Dynamics (CFD) tools to perform their Steady-State Thermal-Hydraulic (SSTH) safety calculations. Using CFD tools for SSTH analysis represents generally a significant departure from traditional methods and requires thorough verification and validation (V&V) to be accepted by regulators. This is why Argonne National Laboratory (ANL) and the involute reactors formed an informal group to help each other in this endeavor. This so-called Involute Working Group (IWG) aims at supporting the qualification of CFD tools for SSTH safety calculations. Activities include benchmarking, code-to-code comparison, Verification and Validation (V&V) as well as technical support. More information on the IWG and the reasons why involute-plate reactors are interested in CFD can be found in Section three. The present study aims at testing three turbulence models commonly implemented in commercial software (namely K-Epsilon, K-Omega and Reynolds-Stress) and assessing their relevance for involute-plate reactor application. An experiment performed by Gambill and Bundy in 1961 was performed to measure heat transfer coefficients in conditions prototypic of the HFIR reactor [Gambill, 1961]. More details on this experiment are provided in Section four. Based on the information available, CFD models of this experiment have been created and the experimental results have been compared to the ones obtained with these CFD models. CFD models and the results of this comparison are provided in Section five.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Smart technologies enable homes to be efficient and interactive with the grid

Oak Ridge National Laboratory researchers compare two different approaches to test how advanced, energy-efficient building technologies such as smart thermostats, heat pump water heaters, and advanced heat pump HVAC (heating, ventilation and air conditioning) can be optimized within a home and connected at a neighborhood-scale load to a community microgrid in the Alabama Power Smart Neighborhood located in Hoover. Working with Southern Company and Alabama Power, ORNL researchers are pioneering that future where smart homes and smart neighborhoods can benefit both homeowners and utilities, by reducing energy consumption by 44% and peak demand by 34%.This project is one of two neighborhoods in the U.S Department of Energy’s (DOE’s) Connected Neighborhood project, supported by Building Technologies Office , where ORNL researchers leverages DOE investment in micro-grids and responsive, flexible building loads research to improve grid reliability – a goal of DOE’s Grid-interactive Efficient Buildings (GEB) Initiative. Researchers control the neighborhood and microgrid to enable utilities achieve their desired load and cost profiles while ensuring the comfort of homeowners in the Smart Neighborhood. This transactive control approach maximizes the utilization of technical resources of the microgrid and controllable loads, while reducing costs for both the homeowners and Alabama Power. These tests partially seek to determine a more precise range of tolerance with respect to occupant comfort as researchers work to facilitate customer acceptance and perception of new building technologies that enable energy savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Report on Oak Ridge National Laboratory Testing of Ambient Cure TransPowr E3X®

A key to industry acceptance of a new technology is extensive validation in field trials. The Powerline Conductor Accelerated Test facility (PCAT) at Oak Ridge National Laboratory (ORNL) is specifically designed to evaluate the performance and reliability of novel overhead conductor and conductor instrumentation under field conditions. The facility is set up to capture large amounts of data during testing. General Cable used the ORNL PCAT facility to validate the performance of TransPowr® with Ambient Cure E3X™ Technology—a standard overhead conductor with a high emissivity, low absorptivity ambient cure surface coating. Extensive testing has demonstrated a significant improvement in conductor performance across a wide range of operating temperatures with respect to uncoated conductor of the same type, indicating that E3X Technology can provide a reduction in temperature, a reduction in sag, and an increase in ampacity when applied to the surface of any overhead conductor. This report provides results of that testing.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Additive Manufacturing of Stamping Tools for Appliances

Oak Ridge National Laboratory (ORNL) worked with Whirlpool Corporation to demonstrate additive manufacturing (AM) of stamping dies for the appliance industry using a large-scale wire arc metal additive manufacturing system jointly developed between Lincoln Electric and ORNL. An appliance stamping die was successfully printed, machined, nitrided, and demonstrated in the last quarter of 2019.

42 ENGINEERING↗
DOE OSTI2020

Initial High Temperature Inelastic Constitutive Model for Alloy 617

This report describes progress on a Alloy 617 inelastic constitutive model slated for inclusion in the ASME Boiler & Pressure Vessel Code in Code Case N-898 “Use of Alloy 617 (UNS N06617) for Class A Elevated Temperature Construction, Section III, Division 5” as part of an appendix on inelastic modeling. This appendix will provide a reference material model for A617 for use in conjunction with the ASME design by inelastic analysis criteria. This report focuses on the implementation and evaluation of an existing Alloy 617 model developed to represent the data collected at Idaho National Laboratory (INL) and Oak Ridge National Laboratory (ORNL) as part of the Alloy 617 Code Case experimental campaign. While the model accurately captures the cyclic stress/strain behavior of Alloy 617, it fails to capture the long-term creep and lower temperature tensile data. In addition, the model form is complicated and has over 50 configurable parameters. As such, we recommend the development of a simplified model, incorporating key features of the ORNL model but reducing the model complexity.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Feasibility Study for a Subcritical Assembly at the Oak Ridge National Laboratory

A conceptual design has been completed for a new subcritical assembly at Oak Ridge National Laboratory (ORNL). This subcritical assembly will support the Nuclear Criticality Safety Program (NCSP) training and education program to augment current subcritical assembly capabilities at Sandia National Laboratories (SNL) and at the National Criticality Experiments Research Center (NCERC). The proposed subcritical assembly uses legacy AGN-201M research reactor fuel plates that are available at the Y-12 National Security Complex. This subcritical assembly contains approximately 620 grams of 235 U as UO 2 particulates distributed homogeneously in radiation-stabilized polyethylene. The fuel plates will have a graphite neutron reflector to obtain a core multiplication, $M$, from 10 to 50, corresponding to a k eff of 0.9 to 0.95, respectively. The subcritical assembly will be able to support at least four experiments for the training courses: the addition of fissile material to increase neutron multiplication (mass), a core separation experiment (interaction), the effect of adding moderators to the core (moderation), and the effect of adding neutron absorbers to the core (poison/absorption). The proposed ORNL subcritical assembly will provide additional student bandwidth to support NCSP training courses and to provide for some backup capacity in the event that nuclear facility operations are disrupted at SNL or NCERC due to some unforeseen issue. The subcritical assembly will be designed to be an inherently safe subcritical assembly—subcritical under all normal and abnormal conditions—and it will provide the capability to conduct hands-on training to support NCSP and general nuclear criticality safety (NCS) staff training and qualification goals.

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DOE OSTI2020

MSR Fuel Salt Qualification Methodology

This report documents the continuing activities at Oak Ridge National Laboratory (ORNL) in support of the US Nuclear Regulatory Commission (NRC) efforts to develop an efficient, appropriate process for liquid fuel salt system qualification. Fuel qualification for salt-cooled molten salt reactors (MSRs) is part of the ongoing coated particle fuel qualification effort. Fuel qualification is a process which provides high confidence that physical and chemical behavior of fuel is sufficiently understood so that it can be adequately modeled for both normal and accident conditions, reflecting the role of the fuel design in the overall safety of the facility. Uncertainties are defined so that calculated fission product releases include the appropriate margins to ensure conservative calculation of radiological dose consequences. The initial phase of ORNL’s activities is documented in ORNL/LTR-2018/1045 Molten Salt Reactor Fuel Qualification Considerations and Challenges.

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