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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Status of New Models Hosted on the Virtual Test Bed (VTB) in 2024

The National Reactor Innovation Center (NRIC) mission is to support deployment of novel reactor concepts. This is achieved by providing physical and virtual spaces for building and testing various components, systems, and complete pilot plants. The Virtual Test Bed (VTB) represents the virtual counterpart to the physical test bed. It is in development in collaboration with the Department of Energy’s (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. The mission of the VTB is to accelerate the deployment and licensing of advanced reactors by leveraging state-of-the-art modeling and simulation (M&S) tools developed by the DOE NEAMS program. This is accomplished by three primary means: (1) openly hosting simulations that showcase analysis capabilities, (2) continuously testing the models hosted against code updates to avoid deprecation, and (3) filling key M&S gaps that are relevant for the physical NRIC test beds. The VTB repository consists of two sub-entities: 1. A documentation website detailing the models (https://mooseframework.inl.gov/virtual_test_bed). 2. A GitHub repository that hosts the corresponding files (https://github.com/idaholab/virtual_test_bed). Previous documentation on the models hosted in the VTB can be found in [1,2,3,4]. These references also include additional background information on the various NEAMS codes showcased in the VTB (which is omitted here for brevity). This paper primarily provides a status update of the most recent additions to the repository.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Compression mechanisms of ferroelectric PbTiO 3 via high pressure neutron scattering

Switchable atomic displacements generate electric dipole moments in ferroelectric materials utilized in many contemporary devices. Lead titanate, a perovskite oxide with formula PbTiO 3 , has been referred to as a textbook example of a prototype displacive ferroelectric and is a testing platform of widely used models of piezoelectric response of complex solid-solutions. PbTiO 3 has been addressed by experimental and computational studies, often with apparently conflicting conclusions. To date, hydrostatic pressure experiments have been interpreted in terms of a model in which the dipole moments gradually diminish with increasing pressure until a transition to a cubic phase, characterized by a zero average dipole moment, occurs. Additionally, the model unrealistically assumes an even compression of the crystal. Here we show by high-pressure neutron powder diffraction measurements that a fast and slow shrinkage of 12-oxygen cages around Pb and octahedra around Ti, respectively, takes place. A phase diagram consolidating earlier and present results is given.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Cluster-dynamics-based parameterization for sulfuric acid–dimethylamine nucleation: comparison and selection through box and three-dimensional modeling

Clustering of gaseous sulfuric acid (SA) enhanced by dimethylamine (DMA) is a major mechanism for new particle formation (NPF) in polluted atmospheres. However, uncertainty remains regarding the SA–DMA nucleation parameterization that reasonably represents cluster dynamics and is applicable across various atmospheric conditions. This uncertainty hinders accurate three-dimensional (3-D) modeling of NPF and the subsequent assessment of its environmental and climatic impacts. Here we extensively compare different cluster-dynamics-based parameterizations for SA–DMA nucleation and identify the most reliable one through a combination of box model simulations, 3-D modeling, and in situ observations. Results show that the parameterization derived from Atmospheric Cluster Dynamic Code (ACDC) simulations, incorporating the latest theoretical insights (DLPNO-CCSD(T)/aug-cc-pVTZ//ωB97X-D/6-311++G(3df,3pd) level of theory) and adequate representation of cluster dynamics, exhibits dependable performance in 3-D NPF simulation for both winter and summer conditions in Beijing and shows promise for application in diverse atmospheric conditions. Another ACDC-derived parameterization, replacing the level of theory with RI-CC2/aug-cc-pV(T+d)Z//M06-2X/6–311++G(3df,3pd), also performs well in NPF modeling at relatively low temperatures around 280 K but exhibits limitations at higher temperatures due to inappropriate representation of SA–DMA cluster thermodynamics. Additionally, a previously reported parameterization incorporating simplifications is applicable for simulating NPF in polluted atmospheres but tends to overestimate particle formation rates under conditions of elevated temperature (>∼300 K) and low-condensation sink (<∼3×10 -3 s −1 ). Our findings highlight the applicability of the new ACDC-derived parameterization, which couples the latest SA–DMA nucleation theory and holistic cluster dynamics, in 3-D NPF modeling. The ACDC-derived parameterization framework provides a valuable reference for developing parameterizations for other nucleation systems.

Shen, Jiewen↗
DOE OSTI2014

Is the residual vertical velocity a good proxy for stratosphere-troposphere exchange of ozone?

Stratosphere-troposphere exchange (STE) of ozone (O 3 ) is key in the budget of tropospheric O 3 , in turn affecting climate forcing and global air quality. We compare three commonly used diagnostics meant to quantify cross-tropopause O 3 fluxes with a Chemistry-Transport Model driven by two distinct European Centre forecast fields. Here, our reference case calculates accurate, geographically resolved net transport across an isosurface in artificial tracer e90 representing the tropopause. Hemispheric fluxes derived from the ozone mass budget of the lowermost stratosphere yield similar results. Use of the Brewer-Dobson residual vertical velocity as a scaled proxy for ozone flux, however, fails to capture the interannual variability. Thus, the common notion that the strength of stratospheric overturning circulation is a good measure for global STE does not apply to O 3 . Finally, climatic variability in the modeled O 3 flux needs to be diagnosed directly rather than indirectly through the overturning circulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Discovery of black dye crystal structure polymorphs: Implications for dye conformational variation in dye-sensitized solar cells

Here, we present the discovery of a new crystal structure polymorph (1) and pseudopolymorph (2) of the Black Dye, one of the world’s leading dyes for dye-sensitized solar cells, DSSCs (10.4% device performance efficiency). This reveals that Black Dye molecules can adopt multiple low-energy conformers. This is significant since it challenges existing models of the Black Dye···TiO 2 adsorption process that renders a DSSC working electrode; these have assumed a single molecular conformation that refers to the previously reported Black Dye crystal structure (3). The marked structural differences observed between 1, 2, and 3 make the need for modeling multiple conformations more acute. Additionally, the ordered form of the Black Dye (1) provides a more appropriate depiction of its anionic structure, especially regarding its anchoring group and NCS bonding descriptions. The tendency toward NCS ligand isomerism, evidenced via the disordered form 2, has consequences for electron injection and electron recombination in Black Dye embedded DSSC devices. Dyes 2 and 3 differ primarily by the absence or presence of a solvent of crystallization, respectively; solvent environment effects on the dye are thereby elucidated. This discovery of multiple Black Dye conformers from diffraction, with atomic-level definition, complements recently reported nanoscopic evidence for multiple dye conformations existing at a dye···TiO 2 interface, for a chemically similar DSSC dye; those results emanated from imaging and spectroscopy, but were unresolved at the submolecular level. Taken together, these findings lead to the general notion that multiple dye conformations should be explicitly considered when modeling dye···TiO 2 interfaces in DSSCs, at least for ruthenium-based dye complexes.

36 MATERIALS SCIENCE↗
DOE OSTI2015

MELCOR Computer Code Manuals Volume 3: MELCOR Assessment Problems [Draft]

MELCOR is a fully integrated, engineering-level computer code that models the progression of severe accidents in light-water reactor nuclear power plants. MELCOR is being developed at Sandia National Laboratories (SNL) for the U.S. Nuclear Regulatory Commission (NRC) as a second-generation plant risk assessment tool and the successor to the Source Term Code package. A broad spectrum of severe accident phenomena in both boiling and pressurized water reactors is treated in MELCOR in a unified framework. These include thermal-hydraulic response in the reactor coolant system (RCS), reactor cavity, containment, and confinement buildings; core heatup, degradation, and relocation; core-concrete attack; hydrogen production, transport, and combustion; and fission product release and transport behavior. Current uses of MELCOR include estimation of severe accident source terms and their sensitivities and uncertainties in a variety of applications. This publication of the MELCOR computer code manuals corresponds to MELCOR 2.0, released to users in September 2008. Volume 1 contains a primer that describes MELCOR's phenomenological scope, organization (by package), and documentation. The remainder of Volume 1 contains the MELCOR User's Guides, which provide the input instructions and guidelines for each package. Volume 2 contains the MELCOR Reference Manuals, which describe the phenomenological models that have been implemented in each package. Volume 3, MELCOR Assessment Problems, presents a portfolio of test and sample problems consisting of both analyses of experiments and of full plant problems. These analyses will be repeated with future releases of MELCOR in order to provide a metric on code predictions as new versions are released.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Regional Real-Time PV Spinning Reserve Estimator

Curtailed photovoltaic (PV) generation is a zero-marginal-cost spinning reserve that can be used for a number of active power control services. Unlike traditional spinning reserve providers, however, i.e., fossil-fueled generators, which have well-defined operating characteristics, e.g., available headroom or potential high limit (PHL), PV plants have by nature variable and uncertain operating characteristics. To ensure the effective coordination between PV plants and the system operator during an active power control event, accurate knowledge of the PV PHL is essential. It ensures that enough headroom is reserved by the PV plants to deliver the award services in real time and informs feasible dispatch decisions made by the market operator. To tackle this challenge, a novel reference-control grouping-based PV plant reserve estimation method has been proposed by the National Renewable Energy Laboratory under past projects funded by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Solar Energy Technologies Office. The estimation method separates inverters within a plant into two groups: a control group and a reference group. While the reference group is reserved to operate at its PHL, the control group can be curtailed to provide the grid services. Real-time outputs from the reference inverters are used to estimate the PHL for the whole plant based on the ratio between capacities of the reference group and of the plant. This work further enhances the methodology by (1) improving the model accuracy through machine learning; (2) automating the reference inverter selection through correlation analysis; (3) considering estimation look-ahead windows; and (4) applying to regional spinning reserve estimation. Significant performance improvement has been observed based on real-world data collected by CAISO, Southern Company, and Terabase Energy. Compared with the original scaling method, the newly proposed machine learning-based approach reduces the estimation errors by 30% and 13% at the plant level and region level, respectively. Results obtained from this project are intended to be used by grid operators, market operators, balancing authorities, and PV plant owners and operators to facilitate PV participation in ancillary service markets. Regulators, policymakers, and system planners can also consider the results of this work in their decision-making processes. In addition to the performance improvement on the existing reference-control based grouping method, we also investigated how the variability of PV generation from a single PV inverter can be used to represent the variability of PV generation at the plant level.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

AGR-2 safety test predictions using the PARFUME code

This report documents calculations performed to predict failure probability of TRISO-coated fuel particles and diffusion of fission products through these particles during safety tests following the second irradiation test of the Advanced Gas Reactor program (AGR-2). The calculations include the modeling of the AGR-2 irradiation that occurred from June 2010 to October 2013 in the Advanced Test Reactor (ATR) and the modeling of a safety testing phase to support safety tests planned at Oak Ridge National Laboratory and at Idaho National Laboratory (INL) for a selection of AGR-2 compacts. The heat-up of AGR-2 compacts is a critical component of the AGR-2 fuel performance evaluation, and its objectives are to identify the effect of accident test temperature, burnup, and irradiation temperature on the performance of the fuel at elevated temperature. Safety testing of compacts will be followed by detailed examinations of the fuel particles to further evaluate fission product retention and behavior of the kernel and coatings. The modeling was performed using the particle fuel model computer code PARFUME developed at INL. PARFUME is an advanced gas-cooled reactor fuel performance modeling and analysis code (Miller 2009). It has been developed as an integrated mechanistic code that evaluates the thermal, mechanical, and physico-chemical behavior of fuel particles during irradiation to determine the failure probability of a population of fuel particles given the particle-to-particle statistical variations in physical dimensions and material properties that arise from the fuel fabrication process, accounting for all viable mechanisms that can lead to particle failure. The code also determines the diffusion of fission products from the fuel through the particle coating layers, and through the fuel matrix to the coolant boundary. The subsequent release of fission products is calculated at the compact level (release of fission products from the compact). PARFUME calculates the release fraction as the ratio of the number of atoms released from the compact to the amount produced in the compact fuel kernels and through uranium contamination. These safety test predictions aim at giving guidance for the upcoming safety tests to be conducted at ORNL and INL. The AGR-2 compacts modeled in this study belong to the four U.S. capsules of the AGR-2 irradiation test train. For each capsule, the compacts with the lowest and highest burnups were selected to provide a prediction envelope. The objective of this document is to present results of calculations and analyses made by PARFUME on these selected AGR-2 compacts. These results include: • Fuel failure probability • Palladium penetration • Fractional release of fission products Details associated with completion of these calculations are provided in the remainder of this document: the AGR-2 Safety Testing plan is briefly introduced in Section 2, PARFUME modeling is outlined in Section 3, results are described in Section 4, conclusions are given in Section 5, and references are listed in Section 6.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Rate Theory Modeling and Simulations of Silicide Fuel at LWR Conditions

Uranium silicide (U 3 Si 2 ) fuel has higher thermal conductivity and higher uranium density, making it a promising candidate for the accident-tolerant fuel (ATF) used in light water reactors (LWRs). However, previous studies on the fuel performance of U 3 Si 2 , including both experimental and computational approaches, have been focusing on the irradiation conditions in research reactors, which usually involve low operation temperatures and high fuel burnups. Thus, it is important to examine the fuel performance of U 3 Si 2 at typical LWR conditions so as to evaluate the feasibility of replacing conventional uranium dioxide fuel with this silicide fuel material. As in-reactor irradiation experiments involve significant time and financial cost, it is appropriate to utilize modeling tools to estimate the behavior of U 3 Si 2 in LWRs based on all those available research reactor experimental references and state-of-the-art density functional theory (DFT) calculation capabilities at the early development stage. Hence, in this report, a comprehensive investigation of the fission gas swelling behavior of U 3 Si 2 at LWR conditions is introduced. The modeling efforts mentioned in this report was based on the rate theory (RT) model of fission gas bubble evolution that has been successfully applied for a variety of fuel materials at devious reactor conditions. Both existing experimental data and DFT-calculated results were used for the optimization of the parameters adopted by the RT model. Meanwhile, the fuel-cladding interaction was captured by the coupling of the RT model with simplified mechanical correlations. Therefore, the swelling behavior of U 3 Si 2 fuel and its consequent interaction with cladding in LWRs was predicted by the rate theory modeling, providing valuable information for the development of U 3 Si 2 fuel as an accident-tolerant alternative for uranium dioxide.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Requirements and Conceptual Design of Off-gas Systems for the Reprocessing of Metallic Fuels

An assessment has been conducted to determine how key regulations regarding volatile radionuclide emissions to the atmosphere may apply to the off-gas streams associated with electrochemical reprocessing. The scope of this assessment was based upon a generic electrochemical reprocessing scheme with a throughput rate of 200 MTIHM/y applied to metallic fuel discharged from a sodium fast reactor (SFR), but the findings are able to be translated to other advanced nuclear scenarios as merited. Air dispersion modeling was performed using the EPA CAP-88 model and evaluated the uncontrolled decontamination factors (DFs) that would be required to achieve regulatory compliance with the dose-based limits set forth by EPA regulation 40 CFR 190.10(a). These DFs were compared to those required by fuel cycle–based limits set forth by EPA regulation 40 CFR 190.10(b). Two theoretical sites with disparate climatological conditions were selected for air dispersion modeling (Idaho and Tennessee). The radionuclides modeled included 3 H, 85 Kr, 129 I, and selected alpha-emitting transuranic isotopes (referred to here as 239 Pu-TRU <1y ). It was found that the fuel cycle-based limits in 40 CFR 190.10(b) are most restrictive for 85 Kr and 239 Pu-TRU <1y , with DFs of 3 and 6.1E+09, respectively. The dose-based limit as derived from 40 CFR 190.10(a) could require mitigation of tritium in some scenarios, with an estimated DF of about 3 for the reference scenarios. The fuel cycle-based limit for 129 I resulted in a DF of about 240 for the reference scenario. The need for iodine mitigation based on dose to the public depended upon the physical form of iodine as either particulate or vapor-phase species. Emission of iodine from the facility as a vapor necessitated DFs of about 2 but emission as a particulate would require DFs >6,000 to meet thyroid dose-based limits. Effects of physical form on needed iodine mitigation are significant, but the understanding of speciation of iodine both during electrochemical reprocessing and after release to the atmosphere is limited. The electrochemical processing unit operations were evaluated to identify potential release points for the volatile radionuclides and to assess the potential for retention of the radionuclides within the process (thus decreasing the need for mitigation). Mitigation strategies for 3 H, 85 Kr, 129 I, and 239 Pu-TRU <1y were identified. In all cases, there are reasonably achievable pathways to regulatory compliance, although in some cases additional R&D is merited to verify the chemical speciation of these isotopes and to develop and demonstrate potential treatment technologies for this application. Whether or not additional off-gas controls (beyond common operations such as HEPA filtration and oxygen and moisture control) are needed for any of these regulated or volatile radionuclides depends on the (a) type of facility (NRC-regulated or DOE), (b) used fuel process rate, (c) used fuel burnup and composition, (d) speciation and retention of volatile radionuclides in the process and in the cell gas cleanup system, (e) site-specific parameters such as location, meteorology, stack height, and site boundaries, and (f) levels of conservatism and safety factors used in assessing compliance to air emissions regulations. Performance of this assessment revealed several areas where information is lacking or additional research is required in order to better determine if or what kinds of off-gas control might be needed. First, and most significantly, the understanding of the chemical speciation and physical form and partitioning of iodine during electrochemical processing operations is lacking and prevents the ability to accurately assess the potential iodine mitigation requirements. Future research in this area should be multifaceted and include thermodynamic modeling of iodine speciation in different process steps, experiments to quantify the kinetics of vapor-phase and melt-phase transitions, bench-scale experiments to determine the potential chemical and physical form of iodine emissions from the electrorefining process, and verification of iodine behavior with experiments utilizing operational facilities. Similarly, an improved understanding of iodine behavior in the environment after release from the facility stack will be required to refine dose estimations, as particulate and vapor-phase emissions result in significantly different doses to the MEI.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Co-Firing Switchgrass and Waste Coal in A Power Plant: A Techno-Economic and Life Cycle Evaluation for The Ohio River Valley (SWITCH) (Final Technical Report for Ohio State/FE0032204)

Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2017

Microstructure Investigations of U{sub 3}Si{sub 2} Irradiated by Heavy Ions at LWR Temperatures

Searching for a nuclear fuel material with enhanced accident tolerance compared to the conventional UO{sub 2} fuel is one of the key objectives of the accident tolerant fuel (ATF) campaign. Having both high thermal conductivity and high uranium load, U{sub 3}Si{sub 2} is expected to provide lower operating temperature/stored energy and advantageous neutron economy as a light water reactor (LWR) fuel material. Therefore, U{sub 3}Si{sub 2} has been regarded as a promising candidate fuel material by the ATF community. To evaluate the qualification of U{sub 3}Si{sub 2} as an ATF fuel in LWRs, its fuel performance during both steady-state operation and power transients must be well understood. As a typical nuclear fuel material applied in research reactors, the fuel performance of U{sub 3}Si{sub 2} at low temperatures (<300 deg. C) has been extensively studied through both experimental and computational approaches. However, under LWR conditions, the temperature of U{sub 3}Si{sub 2} can go beyond 600 deg. C. In that case, the references collected in U{sub 3}Si{sub 2}'s applications in research reactors are inadequate for the validation of U{sub 3}Si{sub 2} as an LWR ATF. Experimental efforts that are dedicated to the LWR conditions must be made to help examine U{sub 3}Si{sub 2}'s qualifications as well as provide valuable references for the development related models in advanced fuel performance code. Gaseous fission products accumulate in nuclear fuel during operation and form fission gas bubbles. The evolution of those fission gas bubbles results in increase of volume (swelling), degradation of thermal conductivity, and eventually fission gas release, compromising the integrity and performance of fuel elements in multiple aspects. Hence, fission gas behavior is one of the most important components of fuel performance. In-pile irradiation and corresponding post-irradiation examinations (PIEs) undoubtedly provide most reliable information on the actual performance of a nuclear fuel. However, the high cost and long lead time involved in in-pile irradiation limit its wide applications. On the other hand, heavy ion irradiation is capable of simulating the neutron effects on materials, especially the behavior of energetic fission fragments in nuclear fuel materials, to a considerable extent. Therefore, heavy ion irradiation was used in this study to investigate the microstructural evolution of U{sub 3}Si{sub 2} under LWR-temperature irradiation, focusing on the difference from low temperature irradiation and fission gas behavior.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Videos, photos, and AI-derived grain size data associated with “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization”

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 “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization” under review. This data package includes five data types: 1) raw photos and videos from drone survey and walking smartphone surveys; 2) images derived from raw videos; 3) manual labeling of reference scales; 4) metadata for all images and photo resolution derived from artificial intelligence (AI) models or manual labels, 5) grain size data obtained from AI models for all photos, 6) metadata and grain size data after quality control, 7) summaries of sample efficiency for all data, and 8) computational fluid dynamics (CFD) data used to support hydro-biogeochemical (HBGC) parameter estimation. Such data is used to 1) demonstrate significant improvements in accuracy, efficiency, and quality control for grain size data collection with the help of AI models, 2) study the spatial heterogeneity of grain size and observation reproducibility based on tens of thousands of data points generated by the AI models, and 3) evaluate the impacts of grain size heterogeneity on key HBGC parameters across sediment-to-reach and hourly-to-yearly scales. In particular, the data package contains 116 folders and 179696 files. The files include 41 videos in .mov format, 64047 photos in .jpg format, 13541 video-derived photos in .png format, 12747 segmentation mask data in .tif format, 12747 segmentation data in .json format, 24771 .csv files that with metadata and grain size for each individual photo as well as water depth and velocity data from CFD and observation, 51791 .txt files of raw AI predicted labels, and 11 flight record data in .srt format. The summary for all metadata and grain size statistics information is included in “Scales_V3_NG.csv” and “Statistics_V3_NG.csv”. The summary for data that pass data quality control (QC) level 0-2 is included in “QCStatistics_V3_NG.csv”. The QC level 0 represents photos whose photo resolution is positive, excluding photos that miss reference scale. The QC level 1 means reference scale circularity uncertainty is less than 5% for smartphone images while representing photo resolution is larger than 0.44 mm/pixel for drone images. The QC level 2 means excluding photos whose grain number is less than 100, a minimum number of grains recommended by classic literature. The summary for each video’s name, length, frame rates, survey area, grain number, survey efficiency, etc. can be found in “QCSummary_V3_NG.csv”. The summary for site name, GPS coordinates, and number of images at each site can be found in “SitesSummary_V3_*.csv” files. Overall computational efficiency summary is reported in Table 4 of accompanying manuscript. Additionally, the nitrate concentration data used in this work was downloaded from an existing dataset published on ESS-DIVE (Boat-Dragged Sensor Hanford Reach.csv; Conner A. et al., 2020). We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Port of Benton, and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the data were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate data collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Influence of Correlations on the Thermal Performance Modeling of Parabolic Trough Collectors

The influence of correlations on the thermal performance modeling of parabolic trough collectors was analyzed in this work. A versatile model for a parabolic trough collector was developed that allows one- and two-dimensional analysis and enables the use of correlations to calculate thermophysical properties and convection heat transfer coefficients. The model also allows the use of constant values for properties and/or coefficients obtained from the evaluation correlations at a specific temperature. The effect of each correlation was evaluated independently, and the results were compared with a reference case that considered a two-dimensional approach and used all the correlations. For the analyzed cases, the correlation for the absorber emittance has the strongest impact on the collector efficiency, leading to a lower error when used. Based on the results, a one-dimensional model approach considering a correlation for the absorber emittance leads to efficiency errors below 3% for collector lengths of up to 243.6 m. Compared with the reference case, a one-dimensional approach using all correlations for a collector with a length of 500 m, and operating with an inlet temperature of 773 K, can result in errors around 9%. However, using constant values for properties and heat transfer coefficients could lead to errors of up to 50%. Multiple thermal models for parabolic trough collectors proposed in the literature rely on a one-dimensional approach, estimated values for the heat transfer coefficients, and constant thermophysical properties. The errors associated with those approaches are analyzed and quantified in this work as a function of the collector length and operation temperature.

absorber emittance↗
DOE OSTI2021

Non-destructive evaluation of specific surface area of porous powder systems using experimental and virtual air permeametry

The correlation of flow-permeable surface area (FSSA) of porous initiator powder to its performance is well-established. More specifically, with age, such powders tend to coarsen (i.e., lose surface area), with an accompanying deterioration in performance. Commercially available permeametry apparatuses, such as that from Fisher Scientific or a more modern version from Micromeritics suffers from a few drawbacks, including: (1) the need to work with a fixed mass equivalent of 1 cm 3 of solid material; (2) the need to re-compact the material to monitor aging effects (which can introduce unwanted errors in the derived results); (3) a superfluous design that involves a reference plug, and for the older Fisher Scientific model, the need to eyeball water meniscus height that can lead to inaccuracies; (4) calibrated and tested only for samples packed in cylindrical geometries.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Neutron Multiplicity Counting Moments for Fissile Mass Estimation in Scatter-Based Neutron Detection Systems

Neutron multiplicity counting (NMC) techniques are widely used for nuclear materials accountability and international safeguards applications to quantitatively evaluate characteristic properties pertaining to fissile material. Mathematical models for NMC moments have been previously derived for systems that use capture-based detectors; however, these models are not applicable when scatter-based detectors are used because of “neutron cross talk.” Neutron cross talk occurs when a single neutron scatters and deposits energy above threshold into multiple detectors causing spurious increase in multiplicity counts; this, in turn, has caused fissile mass to be overestimated when not treated. In this paper, we propose new mathematical models derived from point kinetics to correct for neutron cross-talk effects up to any arbitrary order N, where N denotes the maximum number of counts a single neutron can cause. The new models were used to estimate the fissile mass of plutonium metal and oxide samples with effective 240 Pu mass ranging from 2.5 to 250 g. The adequacy of the models was confirmed using simulations of a conceptual scatter-based neutron multiplicity counter (e.g., organic scintillators) using MCNPX v2.7e with the PoliMi fission event generating extension. The fissile mass estimates with no correction for neutron cross-talk events yielded an average relative deviation from the true 240 Pu eff mass of 55.94% and 84.56% for metal and oxide samples, respectively. When neutron cross-talk events of order N = 2 are included in the model, the fissile mass estimates yielded an average relative deviation of 11.89% for metal and 13.21% for oxide samples. Accounting for neutron cross-talk events of order N = 3 resulted in fissile mass estimates with an average relative deviation of 9.58% and 10.51% for metal and oxide samples, respectively. These mass estimates were compared to a reference case (i.e., no neutron crosstalk effects) that yielded an average relative deviation of 6.81% and 4.77% for metal and oxide samples, respectively. In conclusion, the discrepancy between the estimates from the proposed model and the reference case is attributed to the assumed value of N, which sets a finite upper bound on the order of cross-talk events the model treats (i.e., the model for N = 3 assumes that a neutron will never cause more than three counts).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

What Is the Reference? An Examination of Alternatives to the Reference Sources Used in IES TM-30-15

A study was undertaken to document the role of the reference illuminant in the IES TM-30-15 method for evaluating color rendition. TM-30-15 relies on a relative reference scheme; that is, the reference illuminant and test source always have the same correlated color temperature (CCT). The reference illuminant is a Planckian radiator, model of daylight, or combination of those two, depending on the exact CCT of the test source. Three alternative reference schemes were considered: 1) either using all Planckian radiators or all daylight models; 2) using only one of ten possible illuminants (Planckian, daylight, or equal energy), regardless of the CCT of the test source; 3) using an off-Planckian reference illuminant (i.e., a source with a negative Duv). No reference scheme is inherently superior to another, with differences in metric values largely a result of small differences in gamut shape of the reference alternatives. While using any of the alternative schemes is more reasonable in the TM-30-15 evaluation framework than it was with the CIE CRI framework, the differences still ultimately manifest only as changes in interpretation of the results. References are employed in color rendering measures to provide a familiar point of comparison, not to establish an ideal source.

CAM02-UCS↗