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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

$\mathcal{R}$ -matrix analysis of η + nat Cl reactions relevant to molten-salt reactor designs [Abstract]

Performed with support from the U.S. Nuclear Criticality Safety Program in an effort to provide improved chlorine cross section and corresponding covariance data, the R-matrix analysis of neutron induced reactions for two stable chlorine isotopes, 35,37 Cl, was performed in the energy range of thermal up to 1.2 MeV. Starting from the repository of the ENDF/B-VIII.0 library and following recent measurement campaigns, this work represents a significant improvement in the evaluation of the ( η , p ) reaction channel. The evaluation methodology uses the $\mathcal{R}$ -matrix code SAMMY to generate a set of Reich-Moore resonance parameters. As predicted by recently measured 35 Cl( η , p ) data, the presented evaluation features a dramatic increase in the magnitude of the ( η , p ) reaction channel over the ENDF/B-VIII.0 and previous nuclear data ENDF/B released libraries. Together with details of the evaluation procedure, the impact of the updates in the outgoing proton emissions on reactivity coefficients for different molten-salt reactor designs is presented and discussed.

charged-particle↗
DOE OSTI2023

A New Era of Discovery: The 2023 Long-Range Plan for Nuclear Science (V.1.2)

Nuclear science is the investigation of how protons and neutrons are formed from elementary particles and how the forces between those particles produce both nuclei and the vast variety of nuclear phenomena that occur in the universe. It has evolved into a broad field that addresses profound scientific questions: Where does the mass of visible matter come from? How do stars ignite, live, and die? How do nuclei illuminate the search for new laws of nature? This science points the way to using nuclei to build new technologies that benefit society. The 2015 Nobel Prize in physics was shared by nuclear physicists Art McDonald and Takaaki Kajita for the discovery of neutrino oscillations, which confirmed that neutrinos have mass. Our progress on big questions like this one since 2015 has been remarkable owing to new experimental tools, theoretical breakthroughs, powerful computational techniques, and the talented people who make these innovations possible. Focusing on these new tools, the Facility for Rare Isotope Beams (FRIB) at Michigan State University is already producing exciting results on decays of never-before-produced isotopes a year after it was completed on time and on budget. The energy upgrade of the Continuous Electron Beam Accelerator Facility (CEBAF) at the Thomas Jefferson National Accelerator Facility (Jefferson Lab) was also completed on schedule and on budget—new data from this facility are revealing the spectrum, structure, and dynamics of protons, neutrons, nuclei, and mesons. On the theory front, we can now calculate the distribution of quarks inside the proton from first principles. The implementation of artificial intelligence (AI) and machine learning (ML) techniques has led to improved data analysis and increased efficiency in running experiments and theoretical calculations. The impact of nuclear science goes beyond expanding the frontiers of knowledge about matter in the universe. We simultaneously develop a STEM work force that advances the security, technology, health, and wealth of our nation. Some connections are obvious. Expert scientists trained to work with radioactive nuclei are in demand in nuclear security arenas and are highly sought after by various government agencies and private industries. Graduate students and postdoctoral fellows (postdocs) obtain extensive computational, modeling, and data science skills that are similarly in high demand. Less obvious but equally important is the connection between these trained scientists and success in other professions, including medicine, energy, and entrepreneurial pursuits. The workforce that enables discovery in nuclear science also makes breakthroughs in technologies with tremendous impact on the nation’s economic advancement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

NRC Reactor Operating Experience Analysis and Trend Summary: 2024 Update

This report presents a summary of the Nuclear Regulatory Commission’s (NRC’s) reactor operating experience analyses with data through 2024 as well as the reliability and frequency trends identified in the 2024 update reports for the component performance studies, loss-of-offsite power analysis, initiating events analysis, and system studies provided on the NRC Reactor Operating Experience Results and Databases website (https://nrcoe.inl.gov/).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Expanded analysis of machine learning models for nuclear transient identification using TPOT

Industries around the world are becoming more and more data driven. The nuclear field is no exception with several different applications being proposed. One popular area of research is the use of machine learning in transient detection. This paper seeks to build upon a previous study which made use of the AutoML package TPOT to train traditional machine learning models to classify transient events occurring with a reactor. Synthetic data was once again collected using a GPWR reactor simulator. Data on 12 different events was collected using 15 different initial conditions. Here, a dataset consisting of over 100,000 data points was compiled and used to train 7 different machine learning models using a pre-defined TPOT dictionary with 12 different preprocessing techniques. Three of the trained models were able to produce validation results in the 90s with the expanded dataset. Once the models were trained, it was possible to look into where during the simulation, misclassifications occurred. Using these three models, analysis was done to determine if TPOT could be used to train models that were effective if important features were missing. The results from this were positive with the newly trained models scoring close to the original models. Finally, to conclude this study, the three high performing models were retrained using different random states to see if there was any major variation when different states were used.

42 ENGINEERING↗
DOE OSTI2021

Constraints on effective field theory couplings using 311.2 days of LUX data

We report here the results of an Effective Field Theory (EFT) WIMP search analysis using LUX data. We build upon previous LUX analyses by extending the search window to include nuclear recoil energies up to $\sim$180 keV$_{nr}$, requiring a reassessment of data quality cuts and background models. In order to use a binned Profile Likelihood statistical framework, the development of new analysis techniques to account for higher-energy backgrounds was required. With a 3.14$\times10^4$ kg$\cdot$day exposure using data collected between 2014 and 2016, we set 90\% C.L. exclusion limits on non-relativistic EFT WIMP couplings to neutrons and protons, providing the most stringent constraints on a significant fraction of the possible EFT WIMP interactions. Additionally, we report world-leading exclusion limits on inelastic EFT WIMP-nucleon recoils.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Contributions to the BeEST sterile neutrino search

Sterile neutrinos are hypothetical right-handed leptons that have been postulated as extensions to the Standard Model to help explain the origin of neutrino masses and the matter-antimatter asymmetry in the Universe. Sterile neutrinos with keV-scale masses are also a promising candidate for dark matter. LLNL and the Colorado School of Mines are developing an experiment to search for sterile neutrinos by measuring the \Beryllium-7 Electron capture in Superconducting Tunnel junctions (STJs)" (the \BeEST" Experiment). When 7 Be implanted into STJ radiation detectors decays by electron capture, the neutrino escapes and the energy of the recoiling 7 Li nucleus can be measured with high accuracy. Using conservation of energy and momentum, the mass of the emitted neutrino can then be found. Sterile keV neutrinos would generate additional peaks in the spectrum, and the experiment uses high-resolution STJs to observe such a potential signal. During my internship, I contributed to different aspects of the BeEST experiment. I designed a UHV setup for X-ray spectroscopy analysis with STJs. It will allow high-resolution X-ray spectroscopy of different materials to examine the broadening in the BeEST spectra, the origins of which are unknown but may be related to material effects inside the STJ detectors. The design accounts for the specific demands of the BeEST project, but provides a degree of flexibility that makes it useful for other potential STJ projects. Additionally, to test the accuracy of the electronics and data analysis routine, an arbitrary waveform generator (AWG) will be used to generate simulated spectra that contain sterile neutrino signals of a specified mass and admixture. For this I programmed an AWG to output random STJ signals whose amplitudes follow the appropriate user-de ned probability distribution. The AWG signals can be input into the 32-channel preamplifier to simulate any spectrum of interest and test the uniformity of the amplifier chain, as well as the sensitivity of the data analysis.

42 ENGINEERING↗
DOE OSTI2023

Improving Fission Products at CARIBU: Near Field Detection (Q1/FY23 Quarterly Progress Report)

We performed a branching ratio measurement of the most intense gamma rays in the decay of 111Ag. The sample was harvested at Argonne National Laboratory and measured at Texas A&M with the same technique as we used in our previous measurements. We made two samples and were able to measure both of them. The data is currently under analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

2025 TEM Workshop

The TEM Data Management Workshop will take place on August 26 from 9 a.m. to 12 p.m. MT, and will be held virtually on TEAMS. The primary goal of this workshop is to engage NSUF users and stakeholders in discussions about the data needs for the utilization of AI and ML in the analysis of TEM data. Key topics to be covered include data storage, data sharing, data tagging, metadata inclusion, standardized data formats, data augmentation, and annotated training datasets. Additionally, the workshop will provide valuable insights into resources such as the Nuclear Research Data System (NRDS) for data storage and sharing, as well as open-source codes for data analysis.

Bachhav, Mukesh↗
DOE OSTI2026

Direct inference of nuclear equation-of-state parameters from gravitational-wave observations

The observation of neutron star mergers with gravitational waves (GWs) has provided a new method to constrain the dense-matter equation of state (EOS) and to better understand its nuclear physics. However, inferring nuclear microphysics from GW observations necessitates the sampling of EOS model parameters that serve as input for each EOS used during the GW data analysis. The sampling of the EOS parameters requires solving the Tolman–Oppenheimer–Volkoff (TOV) equations a large number of times—a process that slows down each likelihood evaluation in the analysis on the order of a few seconds. Here, we employ emulators for the TOV equations built using multilayer perceptron neural networks to enable direct inference of nuclear EOS parameters from GW strain data. Our emulators allow us to rapidly solve the TOV equations, taking in EOS parameters and outputting the associated tidal deformability of a neutron star in only a few tens of milliseconds. We implement these emulators in PyCBC to directly infer the EOS parameters using the event GW170817, providing posteriors on these parameters informed solely by GWs. We benchmark these runs against analyses performed using the full TOV solver and find that the emulators achieve speed ups of nearly two orders of magnitude, with negligible differences in the recovered posteriors. Additionally, we constrain the slope and curvature of the symmetry energy at the 90% upper credible interval to be $L$ sym ≲ 106 MeV and $K$ sym ≲ 26 MeV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2000

A Bridge Health Monitoring Method Using the Hilbert-Huang Transform: A Case Study

We have developed a new method for nondestructive instrument method to monitor the health of a bridge. This new method is based on a transient test load and simple data collection. The nuclear of the method is the new invented nonstationary and nonlinear time series analysis method, the Empirical Mode Decomposition and Hilbert Spectral Analysis. The final decision on the health of the bridge structure is based on the nonlinear characteristic of the data, and on the comparison between the free and the forced vibration frequencies. Thus this alternative method enjoys many advantages: (1) no a priori data required, (2) simple data collection, and (3) minimum traffic disruption. Results from a case study of the Shing-Nan Bridge in Hou-Wei will be reported.

Huang, Norden E.↗
DOE OSTI2022

Alternative analysis of the MINERVE ZPR oscillation experiments

Delayed neutrons are of fundamental importance in the field of nuclear reactor dynamics and control. However, the precursor yield fraction for a given nuclear reactor are dependent on the properties of the reactor. Thus, in-pile experiments, such as oscillation experiments are conducted in order to measure those values. In this work, an alternative analysis of the piston oscillation experiments that have been conducted in the MINERVE reactor in 2013 is performed. A new method which evolves effective terms that cancel out undesired drifts of the flux during the experiments is presented. The evaluation of the uncertainty on the values of the response function is also presented. Moreover, the effective delayed neutron fraction β{sub eff} is evaluated and is compared to results in previous works. As the analysis has led to an estimation of β{sub eff} with a large uncertainty, it has been deduced that the oscillation experiments that have been conducted in MINERVE are not a reliable method of experimentation to determine the value of β{sub eff} in the reactor and that the noise experiments are better suited for that purpose.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Understanding the Fluorination of Disordered Rocksalt Cathodes through Rational Exploration of Synthesis Pathways

Here, we have designed and tested several synthesis routes targeting a highly fluorinated disordered rocksalt (DRX) cathode, Li 1.2 Mn 0.4 Ti 0.4 O 1.6 F 0.4 , with each route rationalized by thermochemical analysis. Precursor combinations were screened to raise the F chemical potential and avoid the formation of LiF, which inhibits fluorination of the targeted DRX phase. MnF 2 was used as a reactive source of F, and Li 6 MnO 4 , LiMnO 2 , and Li 2 Mn 0.33 Ti 0.66 O 3 were tested as alternative Li sources. Each synthesis procedure was monitored using a multi-modal suite of characterization techniques including X-ray diffraction, nuclear magnetic resonance, thermogravimetric analysis, and differential scanning calorimetry. From the resulting data, we advance the understanding of oxyfluoride synthesis by outlining the key factors limiting F solubility. At low temperatures, MnF 2 consistently reacts with the Li source to form LiF as an intermediate phase, thereby trapping F in strong Li-F bonds. LiF can react with Li 2 TiO 3 to form a highly lithiated and fluorinated DRX (Li 3 TiO 3 F); however, MnO is not easily incorporated into this DRX phase. Although higher temperatures typically increase solubility, the volatility of LiF above its melting point (848 °C) inhibits fluorination of the DRX phase. Based on these findings, metastable synthesis techniques are suggested for future work on DRX fluorination.

36 MATERIALS SCIENCE↗
DOE OSTI2022

RESULTS OF A VIRTUAL ROUND ROBIN STUDY TO ESTIMATE PROBABILITY OF DETECTION FOR DISSIMILAR METAL WELDS

This paper presents efforts to overcome challenges with empirical probability of detection (POD) estimations in the nuclear power industry through the utilization of a novel virtual flaw method. A virtual round robin (VRR) study was conducted under the Program for Investigation Of NDE by International Collaboration (PIONIC), organized by the United States Nuclear Regulatory Commission (NRC) utilizing data generated by the virtual flaw method. Analysis of results from the VRR was performed by teams from Pacific Northwest National Laboratory (PNNL), Electric Power Research Institute (EPRI), and Aalto University. Empirically derived POD estimations are presented, and challenges associated with obtaining these estimations are discussed. The virtual flaw method is introduced and some details of its implementation for the VRR activity are described. Results from POD analysis of the VRR data by PNNL, EPRI, and Aalto University are presented and a discussion regarding differences in analysis results is provided. Finally, potential future efforts to improve the application of the virtual flaw method and its estimation of POD are discussed.

Probability of detection, Dissimilar Metal Weld, P↗
NASA NTRS1963

THE BOMB-PRODUCED RADIATION BELT

Analysis of data concerning radiation belt formed by a high-altitude nuclear explosion on july 9, 1962

MAGNETICALLY TRAPPED PARTICLE↗
DOE OSTI2020

Reaction History Uncertainty Propagation from Flux to α and from Time to α [Slides]

We discuss uncertainty propagation in reaction history data from underground nuclear tests. γ reaction history detectors measured flux as a function of time. After data analysis we report α as a function of time. Flux uncertainty and time uncertainty propagation into α uncertainty are discussed in detail. Discretization of the formulas is discussed.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

UNESE Data Analysis - Disko Elm Gas Transport Characteristics (NA-22 Quarterly Report)

Two research papers describing gas transport studies in subsurface containment environments appropriate for underground nuclear explosions were revised and accepted for publication in the peer-reviewed journals, Nature – Scientific Reports and Journal of Geophysical Research. The Nature – Scientific Reports paper is a primary deliverable and describes the gas-transport experiment performed in P Tunnel (NNSS) and 1) subsequent analysis of field data as part of the UNESE program. The Journal of Geophysical Research paper describes an experiment, supported mainly by DARPA and led by researchers at Weston Geophysical and New Mexico Tech., with 2) analyses supported by this project to evaluate the ability of SF6 gas tracer to track xenon gas migration under conditions related to a previous UNESE experiment. Two new tasks consider 3) evaluation of detonation heating and multiphase flow on arrival of xenon at the surface and 4) the impact of surface or Langmuir adsorption of gases being transported through pores and along fractures.

58 GEOSCIENCES↗
DOE OSTI2020

Evaluating the Utility of Permethylated Polysaccharide Solution NMR Data for Characterization of Insoluble Plant Cell Wall Polysaccharides

Plant cell wall polysaccharide analysis encompasses the utilization of a variety of analytical tools, including gas and liquid chromatography, mass spectrometry (MS), and nuclear magnetic resonance (NMR) spectroscopy. These methods provide complementary data, which enable confident structural proposals of the many complex polysaccharide structures that exist in the complex matrices of plant cell walls. However, cell walls contain fractions of varying solubilities, and a few techniques are available that can analyze all fractions simultaneously. We have discovered that permethylation affords the complete dissolution of both soluble and insoluble polysaccharide fractions of plant cell walls in organic solvents such as chloroform or acetonitrile, which can then be analyzed by a number of analytical techniques including MS and NMR. In this work, NMR structure analysis of 10 permethylated polysaccharide standards was undertaken to generate chemical shift data providing insights into spectral changes that result from permethylation of polysaccharide residues. This information is of especial relevance to the structure analysis of insoluble polysaccharide materials that otherwise are not easily investigated by solution-state NMR methodologies. The preassigned NMR chemical shift data is shown to be vital for NMR structure analysis of minor polysaccharide components of plant cell walls that are particularly difficult to assign by NMR correlation data alone. With the assigned chemical shift data, we analyzed the permethylated samples of destarched, alcohol-insoluble residues of switchgrass and poplar by two-dimensional NMR spectral profiling. Thus, we identified, in addition to the major polysaccharide components, two minor polysaccharides, namely, <5% 3-linked arabinoxylan (switchgrass) and <2% glucomannan (poplar). In particular, the position of the arabinose residue in the arabinoxylan of the switchgrass sample was confidently assigned based on chemical shift values, which are highly sensitive to local chemical environments. Furthermore, the high resolution afforded by the 1H NMR spectra of the permethylated switchgrass and poplar samples allowed facile relative quantitative analysis of their polysaccharide composition, utilizing only a few milligrams of the cell wall material. As a result, the concepts herein developed will thus facilitate NMR structure analysis of insoluble plant cell wall polysaccharides, more so of minor cell wall components that are especially challenging to analyze with current methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗