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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
NASA NTRS1981

Evaluation of HCMM satellite data for estuarine tidal circulation patterns and thermal inertia soil moisture measurements

Digital thermal maps of the Cooper River (SC) and the Potomac River estuaries were prepared from heat capacity mapping radiometer (HCMR) tapes. Tidal phases were correctly interpreted and verified. Synoptic surface circulation patterns were charted by location thermal fronts and water mass boundaries within the estuaries. Thermal anomalies were detected adjacent of a conventional power plant on the Potomac. Under optimum conditions, estuaries as small as the Cooper River can be monitored for generalized thermal/tidal circulation patterns by the HCMM-type IR sensors. The HCMM thermal inertia approach to estimating soil moisture at the Luverne (MN) test site was found to be unsatisfactory as a NESS operational satellite technique because of cloud cover interference. Thermal-IR data show similar structure of the Baltimore and Washington heat islands when compared to NOAA AVHRR thermal-IR data. Thermal anomalies from the warm water discharge water of a nuclear power plant were mapped in Lake Anna, Virginia.

Wiesnet, D. R.↗
NASA NTRS1989

Connection between energy relations of solids and molecules

The universal energy relation, discovered for metallic and covalent solids as well as nuclear matter, is tested for diatomic molecules. It is found that it applies well to covalent diatomic bonds, but that ionic diatomic bonds are in a distinct class. A simple extension of the universal binding energy relation that includes the effects of ionicity ensues. It yields accurate prediction of spectroscopic data for both ionic and covalent bonds in 150 molecules. The form of the covalent part is given by the universal relation, suggesting an intimate relationship between the energetics of solids and diatomic molecules.

Smith, John R.↗
DOE OSTI2021

Quantitative Risk Analysis of High Safety Significant Safety-related Digital Instrumentation and Control Systems in Nuclear Power Plants using IRADIC Technology

This report documents the activities performed by Idaho National Laboratory (INL) during fiscal year (FY) 2021 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) Risk Assessment project. In FY-2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, and secure DI&C technologies for digital upgrades/designs. An integrated risk assessment technology for the DI&C systems (IRADIC technology) was proposed for this strategy, which aims to (1) provide a best-estimate risk-informed capability to quantitatively and accurately estimate the safety margin obtained from plant modernization, especially for the High Safety Significant Safety-related (HSSSR) DI&C systems, (2) develop an advanced risk assessment technology to support transition from analog to DI&C technologies for nuclear industry, (3) assure the long-term safety and reliability of vital HSSSR DI&C systems, (4) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals and deal with the expensive licensing justifications from regulatory insights, the IRADIC technology is instructive for nuclear vendors and utilities to effectively lower the costs associated with digital compliance and speed industry advances by: (1) defining an integrated risk-informed analysis process for DI&C upgrade, including hazard analysis, reliability analysis, and consequence analysis, (2) applying systematic and risk-informed tools to address common cause failures (CCFs) and quantify responding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the individual level, system level, and plant level, (4) providing insights and suggestions on designs to manage the risks; thus, to support the development, licensing, and deployment of advanced DI&C technologies on nuclear power plant (NPPs). In this report, an approach for performing software CCF analysis, given limited data, is developed and demonstrated using a case study of a highly redundant digital reactor trip system. Consequence analysis is also performed based on different accident scenarios. Results indicate that plant modernization including the improvement of HSSSR DI&C systems will make great benefits to plant safety by providing more safety margins to accident management. In addition, a novel approach is proposed in this report for the quantification of software hazards when sufficient operational and testing data available. The method incorporates software development quality as well as strong analysis techniques to identify and link software defects to potential failure modes. The approach includes both semantic and test-based analysis to detect failures that can exist in different stages of the software development life cycle. This method is applied to an advanced human system interface relevant to reactor trip safety developed from the APR 1400 design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Experimental differential cross sections, level densities, and spin cutoffs as a testing ground for nuclear reaction codes

Proton double-differential cross sections from 59 Co(α,p) 62 Ni, 57 Fe(α,p) 60 Co, 56 Fe( 7 Li,p) 62 Ni, and 55 Mn( 6 Li,p) 60 Co reactions have been measured with 21-MeV α and 15-MeV lithium beams. Cross sections have been compared against calculations with the empire reaction code. Different input level density models have been tested. It was found that the Gilbert and Cameron [A. Gilbert and A. G. W. Cameron, Can. J. Phys. 43, 1446 (1965)] level density model is best to reproduce experimental data. Level densities and spin cutoff parameters for 62 Ni and 60 Co above the excitation energy range of discrete levels (in continuum) have been obtained with a Monte Carlo technique. Furthermore, excitation energy dependencies were found to be inconsistent with the Fermi-gas model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

The role of the Heisenberg principle in constrained molecular dynamics model

In this study, we implement the Heisenberg principle into the Constrained Molecular Dynamics model with a similar approach to the Pauli principle using the one-body occupation probability $\bar{f}_i$. Results of the modified and the original model with comparisons to data are given. The binding energies and the radii of light nuclei obtained with the modified model are more consistent with the experimental data than the original one. The collision term and the density distribution are tested through a comparison to p+ 12 C elastic scattering data. Some simulations for fragmentation and superheavy nuclei production are also discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

TP89 - SIRZ Decomposition Spectral Estimation

The primary objective of this test plan is to provide X-ray CT measurements of known materials for the purposes of generating and testing MicroCT and EDS spectral estimates. These estimates are to be used in subsequent Ze/RhoE decomposition analyses of acquired data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

A User Guide to PARET/ANL (Rev.2)

PARET was originally created in 1969 at what is now Idaho National Laboratory (INL), to analyze reactivity insertion events in research and test reactor cores cooled by light or heavy water, with fuel composed of either plates or pins. The use of PARET is also appropriate for fuel assemblies with curved fuel plates when their radii of curvatures are large with respect to the fuel plate thickness. The PARET/ANL version of the code has been developed at Argonne National Laboratory (ANL) under the sponsorship of the U.S. Department of Energy/NNSA since the inception of the Reactor Conversion Program. Since Reduced Enrichment for Research and Test Reactors (RERTR) began in 1978, PARET/ANL has been benchmarked to experimental data including SPERT testing, and used to determine the expected transient behavior of a large number of reactors regardless of enrichment both inside and outside the Reactor Conversion Program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Gear Test Assembly - Status Report For FY2019

The final stages of pre-sodium commissioning were completed for the Gear Test Assembly (GTA) in late 2018 and all the components were moved to building 308 for final preparations for insertion into the Mechanisms Engineering Test Loop (METL). The GTA was fully assembled in the experimental test assembly workstation and all supporting electrical and hardware systems were installed on the METL Mezzanine. The GTA was installed in Test Vessel 1 after performing a final systems check, and the vessel and article were raised to operating temperature and held for two weeks to bake-out any moisture present in the components. Test Vessel 1 was filled with sodium and a purification process was completed using the cold trap system. When the sodium was sufficiently clean, Test Vessel 1 was isolated from the rest of METL, and experimental operation of the GTA commenced. The experimental operations consisted of rotating two shafts using Parker servomotors to apply a prototypic torque of a fuel handling mechanism removing and inserting a sodium fast reactor fuel assembly. This removing and inserting motion was repeated until the system seized, indicating component degradation of either the gears or the bearings in the test gearbox. A total of 19,600 cycles were completed, corresponding to the removal and insertion of 9,800 fuel assemblies. The system was shut down and then prepared for removal. The Flexicask System was successfully used to remove the GTA from Test Vessel 1 while keeping both vessel and article inert during the process. The GTA was installed in the Carbonation System, where the process of slowly reacting the sodium away using moist CO 2 has been started. Once the GTA is fully cleaned, it will be disassembled and the gears will undergo the same NDE process performed before testing to quantify the wear that occurred. A report on this, along with the data analysis from the experimental operations will be submitted in late 2019.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Report to NCSP on FY21 DANCE and NEUANCE measurements of 233 U(η, γ)

The experiment was performed by the end of the CY20 runcycle at LANSCE. Due to transportation issues the material arrived at LANL on 1st December. Two 233 U samples, of 20 mg and 10 mg were produced at LANL by stippling, which has proved a robust, cost-effective method for producing actinide samples in the range of 1-20 mg in a small (<1 cm) diameter with very high efficiency. The 20 mg sample was placed inside NEUANCE on FP14 on 11th December, was measured over 10 days, and the 10 mg sample was placed in the beam for 1 day. The rest of the beam time was used to measure radioactive γ sources for calibration, background measurements and tests to define the 233 U windows required during the data taking, also some measurements were done with a 235 U sample to cross-check the performance and the systematics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Temperature Effect over Gas Bubble Evolution in Uranium-10 wt.% Molybdenum alloy Irradiated by Swift Xe Ions

Results from post-irradiation examination (PIE) of U-10Mo binary metallic fuel irradiated by 84 MeV Xe ions at two different temperatures (450°C & 275°C) have been evaluated and reported. The main goal of this study was to understand gas bubble formation (due to accumulation of Xe gas) and corresponding size evolution dependent upon net Xe deposition at two different temperatures, for the U-10Mo fuel samples. From the post ion irradiation examination analysis, it can be concluded that at 450°C the Xe gas bubbles seems to coarsen more easily compared to 275°C. The results of ion irradiation testing can provide initial data that may be beneficial for fuel system down-selections, and for the development and validation of fuel performance models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

FY21 Status Report on Creep Rupture Testing at ANL to Support the Development of Alloy 709 Code Case

This report provides an update on the status of the creep rupture testing on the first commercial heat of Alloy 709 in support of the Alloy 709 Code Case development. Creep tests were performed in air on the lever-arm load frames in the Mechanical and Environmental Testing Laboratory at Argonne National Laboratory (ANL). In FY21, the focus was on the age-hardened ESR-1150°C material. Twenty two tests were initiated, among which ten were completed. This report presents the data from the completed tests. Metallographic characterization of the fractured specimens were performed and the results are included. The creep data enabled the preliminary analysis of the creep behavior of this material. The characterization showed the effect of test temperature and stress on the deformation microstructure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Adaptive Sampling Algorithms for Probabilistic Risk Assessment of Nuclear Simulations

Nuclear simulations are often computationally expensive, time-consuming, and high-dimensional with respect to the number of input parameters. Thus exploring the space of all possible simulation outcomes is infeasible using finite computing resources. During simulation-based probabilistic risk analysis, it is important to discover the relationship between a potentially large number of input parameters and the output of a simulation using as few simulation trials as possible. This is a typical context for performing adaptive sampling where a few observations are obtained from the simulation, a surrogate model is built to represent the simulation space, and new samples are selected based on the model constructed. The surrogate model is then updated based on the simulation results of the sampled points. In this way, we attempt to gain the most information possible with a small number of carefully selected sampled points, limiting the number of expensive trials needed to understand features of the simulation space. We analyze the specific use case of identifying the limit surface, i.e., the boundaries in the simulation space between system failure and system success. In this study, we explore several techniques for adaptively sampling the parameter space in order to reconstruct the limit surface. We focus on several adaptive sampling schemes. First, we seek to learn a global model of the entire simulation space using prediction models or neighborhood graphs and extract the limit surface as an iso-surface of the global model. Second, we estimate the limit surface by sampling in the neighborhood of the current estimate based on topological segmentations obtained locally. Our techniques draw inspirations from topological structure known as the Morse-Smale complex. We highlight the advantages and disadvantages of using a global prediction model versus local topological view of the simulation space, comparing several different strategies for adaptive sampling in both contexts. One of the most interesting models we propose attempt to marry the two by obtaining a coarse global representation using prediction models, and a detailed local representation based on topology. Our methods are validated on several analytical test functions as well as a small nuclear simulation dataset modeled after a simplified Pressurized Water Reactor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Irradiation Tests Supporting LEU Conversion of Very High Power Research Reactors in the US

The US fuel development team is developing a high density uranium-molybdenum alloy monolithic fuel to enable conversion of five high-power research reactors. Previous irradiation tests have demonstrated promising behavior for this fuel design. A series of future irradiation tests will enable selection of final fuel fabrication process and provide data to qualify the fuel at moderately-high power conditions for use in three of these five reactors. The remaining two reactors, namely the Advanced Test Reactor and High Flux Isotope Reactor, require additional irradiation tests to develop and demonstrate the fuel’s performance with even higher power conditions, complex design features, and other unique conditions. This paper reviews the program’s current irradiation testing plans for these moderately-high irradiation conditions and presents conceptual testing strategies to illustrate how subsequent irradiation tests will build upon this initial data package to enable conversion of these two very-high power research reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

A709 Qualification Plan Update and Mechanical Properties Data Assessment

This report provides a summary of the development effort for the qualification of Alloy 709, an advanced austenitic stainless steel, in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code, Section III, Division 5, High Temperature Reactors. It provides an assessment of the mechanical properties data generated to date from the tensile, creep, fatigue and creep-fatigue tests of the precipitation-treated Alloy 709 from two commercial heats in plate product form. It was concluded that the mechanical properties of Alloy 709 with the precipitation treatment continued to outperform those of Type 316 stainless steel. This affirms the recommendation to Code qualification this alloy as a replacement for Type 316 stainless steel to support the objective of reducing the construction and operating costs to incentivize advanced reactor deployment. The data also demonstrated that the precipitation treatment is effective in enhancing the creep-fatigue resistance of Alloy 709 while maintaining a significant creep strength advantage over Type 316 stainless steel. This report also provides an update to the test conditions for the creep, fatigue and creep-fatigue test matrices in order to cover the Code Case data package more effectively. Finally, it is recommended to continue the Alloy 709 Code Case Testing Program to develop the data package needed for the determination of the material-specific design parameters for inclusion in the Alloy 709 Code Case.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Solid Secondary Waste Form Testing Activities for the Integrated Disposal Facility Performance Assessment Support - 17567

Solid secondary waste (SSW) that will be generated at the Waste Treatment and Immobilization Plant (WTP) and from other activities at the Hanford site is destined for disposal at the Integrated Disposal Facility (IDF). Construction of the IDF was undertaken based on a Performance Assessment (PA) performed in 2001. In 2016, a SSW data package was prepared to support the development of an updated PA (2017 IDF PA). There are many inputs required to support the IDF PA. Data needs were identified based on experience from the previous PAs and from the development of conceptual models and modeling approaches to be applied for the 2017 PA. Interactions with the IDF PA team and the inventory data package developer helped to focus detailed efforts on a few key waste streams, contaminants of concern, and disposal configurations that are expected to be the primary contributors to the dose resulting from SSW disposed at the IDF. The key waste streams include: High Efficiency Particulate Air (HEPA) filters, ion exchange resins, granular activated carbon, and Ag-mordenite. The key parameters addressed in the 2016 data package include: saturated hydraulic conductivity, moisture characteristic curves, effective diffusion coefficient, distribution coefficient and porosity. The IDF PA team also identified a set of key contaminants that are expected to be the primary concern for the PA calculations (Tc-99, I-129, Cs-137, Sr-90, uranium isotopes (and total uranium), chromium, mercury and nitrate). These contaminants were the focus of the SSW data package. Specific formulations had not been identified for cementitious materials that will be used to encapsulate or stabilize SSW, and no IDF-specific experiments had been conducted to obtain the data for the PA. Thus, for the 2016 SSW data package, recommended property values were provided for a range of representative candidate materials based on a review of existing literature. However, starting in FY17, IDF-specific experiments will be performed for Hanford SSW expected to contribute most significantly to the dose for the IDF. This paper will summarize the information obtained for the 2016 data package and the plans for further testing to refine key inputs for the IDF PA. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

The effect of aluminum additions on the oxidation resistance of U 3 Si 2

The effect of aluminum additions to U 3 Si 2 is investigated in this paper as a means to improve the oxidation resistance of this nuclear fuel form. Four U-Si-Al compositions have been synthesized and characterized using scanning electron microscopy, energy dispersive spectroscopy, and x-ray diffraction. The onsets of breakaway oxidation are identified in air thermal ramp tests using thermogravimetric analysis. The final oxidation products following 1000° C air exposure are identified using x-ray diffraction and compared to those of UO 2 and U metal oxidized in the same manner. Finally, thermogravimetric data acquired in this study indicates that increasing amounts of Al in U 3 Si 2 further delays the onset of breakaway oxidation, providing enhanced oxidation resistance in air. Al 2 O 3 formation on U 3 Al 2 Si 3 is observed following a heat treatment performed at 500° C in air, demonstrating the potential of Al additions to improve the oxidation resistance of U 3 Si 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Measurement of the 252 Cf ⁢(sf) prompt fission neutron spectrum utilizing 12 C ⁡(𝑛, 𝑛) and 9 Be ⁢(𝑛, 𝑛) neutron scattering reference measurements

The 252 Cf spontaneous fission (sf), prompt fission neutron spectrum (PFNS) is a fundamental quantity for nuclear physics measurements of neutron-emitting reactions. This energy distribution of neutrons emitted from fission has been considered a neutron data standard for decades and has been utilized as a reference for neutron detection efficiency, validation of Monte Carlo simulations, benchmarking of dosimetry standards, and more. A significant portion of the global collection of nuclear data on neutron-induced reactions is correlated with the 252 Cf ⁢(sf) PFNS. Despite the reliance on this quantity by the nuclear physics community, the historical collection of 252 Cf PFNS measurements display systematic disagreements that are not understood or easily explained. These experimental discrepancies could potentially bias the 252 Cf PFNS Standard evaluation. On top of this, these past experiments frequently employed correlated experimental measurement or analysis methods. The artificial intelligence (AI)/machine learning (ML)-informed californium chi-nuclear data experiment (AIACHNE) project was formed to (a) investigate these discrepancies utilizing AI/ML methods to identify outlying regions of literature data, assign these regions to features of the experiment itself, and perform an improved evaluation of the 252 Cf PFNS and (b) perform a new experimental measurement of this quantity designed to improve upon the existing literature database. Here, in this work, we report on the AIACHNE 252 Cf PFNS experiment utilizing a new analysis method uncorrelated with all previous measurements: neutron efficiency determinations based on elastic neutron scattering on 12 C and 9 Be . This new method provides an independent test of the existing literature data and evaluation of the 252 Cf ⁢(sf) PFNS. The method is described with detailed covariance quantification procedures, as well as a direct discussion of the sources of uncertainty described as requirements in the “Templates” series of papers. The 252 Cf ⁢(sf) PFNS reported in this work agrees well with the overall shape of the existing standard PFNS evaluation as well as many literature measurements, thus verifying the current evaluation utilizing new techniques. However, the results suggest that there are deficiencies in the angle-differential 12 C and 9 Be ⁢(𝑛, 𝑛) evaluated nuclear data, which produce unphysical structures in the reported result. While these structures are relatively minor, they become obvious because of the high statistical precision of the data and the expected smooth continuity of the 252 Cf ⁢(sf) PFNS.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Machine learning-powered data cleaning for LEGEND: a semi-supervised approach using affinity propagation and support vector machines

Neutrinoless double-beta decay ($0\nu\beta\beta$) is a rare nuclear process that, if observed, will provide insight into the nature of neutrinos and help explain the matter-antimatter asymmetry in the Universe. The large enriched germanium experiment for neutrinoless double-beta decay (LEGEND) will operate in two phases to search for $0\nu\beta\beta$. The first (second) stage will employ 200 (1000) kg of High-Purity Germanium (HPGe) enriched in 76 Ge to achieve a half-life sensitivity of 10 27 (10 28 ) years. In this study, we present a semi-supervised data-driven approach to remove non-physical events captured by HPGe detectors powered by a novel artificial intelligence model. We utilize affinity propagation to cluster waveform signals based on their shape and a support vector machine to classify them into different categories. We train, optimize, and test our model on data taken from a natural abundance HPGe detector installed in the Full Chain Test experimental stand at the University of North Carolina at Chapel Hill. We demonstrate that our model yields a maximum sacrifice of physics events of $0.024 ^{+0.004}_{-0.003} \%$ after data cleaning. Our model is being used to accelerate data cleaning development for LEGEND-200 and will serve to improve data cleaning procedures for LEGEND-1000.

artificial intelligence↗