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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Development, Testing, and Validation of Fabry-Pérot Cavity Acoustic Sensors for Microreactor Applications

Nuclear microreactors are a unique reactor design which may allow for the nuclear energy industry to tap into unconventional markets, and their modularity presents some advantages over larger, conventional reactor designs. For nuclear microreactors to be economically viable, on-line structural health monitoring may be necessary to reduce operation and maintenance costs with lower power production. Optical fiber sensors, and specifically optical Fabry-Pérot cavities (FPCs), may present the opportunity to monitor vibrational frequencies of microreactor components during operation, enabling identification of the location and severity of potential damage. In this work, FPCs were designed and fabricated with materials which may be able to survive in the extremely harsh environment of nuclear microreactors. The FPCs were bonded to metal test specimens to monitor their vibrational frequencies, along with a reference piezoelectric accelerometer. Euler-Bernoulli theory was used to calculate the fundamental modes and mode-shapes to compare with experimentally measured frequency spectra. The peak frequencies detected with the FPC and piezoelectric accelerometer, and theoretical modes, all agreed well for the first four fundamental modes (within 5%). Furthermore, when the FPC and accelerometer were co-located on the test specimen, their peak frequencies all agreed within 1%.

Birri, Tony↗
DOE OSTI2021

Physics‐based iterative reconstruction for dual‐source and flying focal spot computed tomography

Purpose For single‐source helical Computed Tomography (CT), both Filtered‐Back Projection (FBP) and statistical iterative reconstruction have been investigated. However, for dual‐source CT with flying focal spot (DS‐FFS CT), a statistical iterative reconstruction that accurately models the scanner geometry and acquisition physics remains unknown to researchers. Therefore, our purpose is to present a novel physics‐based iterative reconstruction method for DS‐FFS CT and assess its image quality. Methods Our algorithm uses precise physics models to reconstruct from the native cone‐beam geometry and interleaved dual‐source helical trajectory of a DS‐FFS CT. To do so, we construct a noise physics model to represent data acquisition noise and a prior image model to represent image noise and texture. In addition, we design forward system models to compute the locations of deflected focal spots, the dimension, and sensitivity of voxels and detector units, as well as the length of intersection between x‐rays and voxels. The forward system models further represent the coordinated movement between the dual sources by computing their x‐ray coverage gaps and overlaps at an arbitrary helical pitch. With the above models, we reconstruct images by an advanced Consensus Equilibrium (CE) numerical method to compute the maximum a posteriori estimate to a joint optimization problem that simultaneously fits all models. Results We compared our reconstruction with Siemens ADMIRE, which is the clinical standard hybrid iterative reconstruction (IR) method for DS‐FFS CT, in terms of spatial resolution, noise profile, and image artifacts through both phantoms and clinical scan datasets. Experiments show that our reconstruction has a higher spatial resolution, with a Task‐Based Modulation Transfer Function (MTF task ) consistently higher than the clinical standard hybrid IR. In addition, our reconstruction shows a reduced magnitude of image undersampling artifacts than the clinical standard. Conclusions By modeling a precise geometry and avoiding data rebinning or interpolation, our physics‐based reconstruction achieves a higher spatial resolution and fewer image artifacts with smaller magnitude than the clinical standard hybrid IR.

Wang, Xiao↗
DOE OSTI2024

A Particle Method for the Multispecies Landau Equation

Abstract The multispecies Landau collision operator describes the two-particle, small scattering angle or grazing collisions in a plasma made up of different species of particles such as electrons and ions. Recently, a structure preserving deterministic particle method (Carrillo et al. in J. Comput. Phys. 7:100066, 2020) has been developed for the single species spatially homogeneous Landau equation. This method relies on a regularization of the Landau collision operator so that an approximate solution, which is a linear combination of Dirac delta distributions, is well-defined. Based on a weak form of the regularized Landau equation, the time dependent locations of the Dirac delta functions satisfy a system of ordinary differential equations. In this work, we extend this particle method to the multispecies case, and examine its conservation of mass, momentum, and energy, and decay of entropy properties. We show that the equilibrium distribution of the regularized multispecies Landau equation is a Maxwellian distribution, and state a critical condition on the regularization parameters that guarantees a species independent equilibrium temperature. A convergence study comparing an exact multispecies Bobylev-Krook-Wu (BKW) solution to the particle solution shows approximately 2nd order accuracy. Important physical properties such as conservation, decay of entropy, and equilibrium distribution of the particle method are demonstrated with several numerical examples.

Mathematics↗
DOE OSTI2021

Coastal-Fog Microphysics Using In-Situ Observations and GOES-R Retrievals

Here, the objective of this work is to evaluate GOES-R based fog conditions occurred during the C-FOG (Toward Improving Coastal Fog Prediction) field campaign. C-FOG is designed to advance understanding of fog formation, development, and dissipation over coastal environments to improve its predictability. The project took place along coastlines and open water environments of Eastern Canada (Nova Scotia, NS and the Island of Newfoundland, NL) during August-October of 2018 where environmental conditions play an important role for late season’s fog formation. During the C-FOG field campaign, instruments were located at the Ferryland Supersite, NL, with 2 main sites, and five satellite sites, as well as on the Research Vessel (R/V) Hugh R. Sharp. Key measurement instruments included a Gondola carrying a CDP (cloud droplet probe) and a BCP (backscatter cloud probe) was used for measuring droplet spectra from 1-75 µm on the R/V. A LPM (laser precipitation monitor) with 100 µm-1 cm size range and an OPC (optical particle counter) with 0.3-17 µm at 16 spectral channels provided information for fog and drizzle discrimination. Remote sensing platforms (e.g. profiling microwave radiometer, PMWR), Ceilometer, Lidar), meteorological towers, tethered balloons, and GOES-R products (e.g. fog coverage and droplet size and liquid water path) were used to evaluate fog over horizontal and vertical dimensions. Results suggest that effective radius, phase, liquid water path, and liquid water content values obtained from GOES-R and PMWR were comparable to ground based in-situ observations. It is concluded that integration of observations and nowcasting products may help improve short term local fog predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Multi-arrival infrasound from meteoroids: Fragmentation signatures versus propagation effects in a fine-scale layered atmosphere

Infrasonic signatures of meteoroid fragmentation are frequently ambiguous: do multiple arrivals signify a complex breakup or merely the distorting effects of a layered atmosphere? Resolving this ambiguity is critical for accurate energy estimates and source reconstruction. In this study, we address this challenge by analyzing a unique regional dataset of well-constrained meteoroid events observed by the Southern Ontario Meteor Network and the co-located Elginfield Infrasound Array. We employ pseudo-differential parabolic equation (PPE) simulations to quantify how fine-scale gravity-wave structures in the stratosphere and lower thermosphere modify acoustic waveforms at ranges <300 km. Our modeling reveals that while fine-scale layering can stretch signals and generate diffuse oscillatory tails, it does not produce discrete, high-amplitude pulse splitting at ranges below ∼140 km. By applying these results to the rare multi-arrival event 20060305, we demonstrate that its distinct double arrival at 100 km range is inconsistent with atmospheric multipathing and provides definitive evidence of separate fragmentation episodes. These findings establish new diagnostic criteria for separating source physics from propagation artifacts, improving the reliability of infrasound as a monitoring tool for natural bolides, space debris re-entries, and catastrophic launch failures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Collective effect of thermal plumes on temperature fluctuations in a closed Rayleigh–Benard convection cell

Here, we report a systematic study of the collective effect of thermal plumes on the probability density function (PDF) P(δT) of temperature fluctuations δT(t) in turbulent Rayleigh-Benard convection. By decomposing δT(t) into four basic fluctuation modes associated with single and multiple warm and cold plumes and a turbulent background, we derive an analytic form of P(δT) based on the convolutions of the five independent modes. To test the derived form of P(δT) in the multiple-plume regions, where the thermal plumes are heavily populated, we conduct time series measurements of temperature fluctuations in two convection cells; one is a vertical thin disk and the other is an upright cylinder of aspect ratio unity. For a given normalized position in most regions of the convection cell, all of the measured PDFs P(δT) for different Rayleigh numbers fall onto a single master curve, once δT is normalized by its rms value σ T . It is found that the measured P(δT / σT ) at different locations along the symmetric horizontal and vertical axes of the convection cells can all be well described by the derived form of P(δT / σT ). The fitted values of the parameters associated with the number of plumes in multiple plume clusters and their relative strengths and degrees of intermittency are closely linked to the spatial distribution of thermal plumes and local dynamics of the large-scale circulation in a closed convection cell. Our work thus provides a unified theoretical approach for understanding scalar PDFs in a turbulent field, which is very useful not only for the present study but also for the study of many turbulent mixing problems of practical interest.

42 ENGINEERING↗
DOE OSTI2023

Study of Alfvén eigenmode stability in Quasi-Poloidal Stellarator (QPS) plasma using a Landau closure model

The aim of this study is to analyze the linear stability of Alfvén eigenmodes (AE) in the QPS device heated by a tangential neutral beam injector (NBI). The analysis is performed using the gyro-fluid code FAR3d, that solves the reduced MHD equations for the thermal plasma coupled with moments of the kinetic equation for the energetic particles (EP). The AE stability is calculated in several operational regimes of the tangential NBI: EP β between 0.001 and 0.1, EP energy between 12 and 180 keV and different radial locations of the beam. The analysis is performed for vacuum and finite β equilibria as well as QPS configurations with two and three periods. The EP β threshold in the vacuum case is 0.001 and the AE frequency is lower as the energy of the EP population decreases. Toroidal Alfvén eigenmodes with f = 80–120 kHz and elliptical AE between f = 120–350 kHz are triggered between the middle-outer plasma region ($r/a \gt 0.5$). The AE stability improves in the simulations with finite β equilibria and three period configurations with respect to the vacuum case with two periods because the continuum gaps are slender, leading to a higher threshold of the EP β, above 0.03 for the AEs triggered by the helical mode families. Helical effects are not strong enough to destabilize Helical Alfvén eigenmodes, the AEs with the largest growth rates are triggered by the n = 1 and n = 2 toroidal families.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Crystal structures of a dodecameric multicopper oxidase from Marinithermus hydrothermalis

We report multicopper oxidases (MCOs) represent a diverse family of enzymes that catalyze the oxidation of either an organic or a metal substrate with concomitant reduction of dioxygen to water. These enzymes contain variable numbers of cupredoxin domains, two, three or six per subunit, and rely on four copper ions, a single type I copper and three additional copper ions organized in a trinuclear cluster (TNC), with one type II and two type III copper ions, to catalyze the reaction. Here, two crystal structures and the enzymatic characterization of Marinithermus hydrothermalis MCO, a two-domain enzyme, are reported. This enzyme decolorizes Congo Red dye at 70°C in the presence of high halide concentrations and may therefore be useful in the detoxification of industrial waste that contains dyes. In two distinct crystal structures, MhMCO forms the trimers seen in other two-domain MCOs, but differs from these enzymes in that four trimers interact to create a dodecamer. This dodecamer of MhMCO forms a closed ball-like structure and has implications for the sequestration of bound divalent metal ions as well as substrate accessibility. In each subunit of the dodecameric structures, a Trp residue, Trp351, located between the type I and TNC sites exists in two distinct conformations, consistent with a potential role in facilitating electron transfer in the enzyme.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Direct Numerical Simulation of Involute Channel Turbulence

A direct numerical simulation (DNS) study was performed on turbulent flow in the high flux isotope reactor involute channel geometry to develop a numerical database and determine the differences compared with a flat parallel channel. The varying channel curvature along the walls was studied for differences in mean profiles. Parameters of interest include streamwise velocity, turbulent kinetic energy (TKE), and turbulence dissipation rate, as well as Reynolds stresses and turbulence transport terms. Profile sampling was carried out at 10 locations along the span of the involute. Additional DNS studies were performed on smaller domains of comparable curvature to the involute domain: a high curvature channel (high circular), a low curvature channel (low circular), and a flat channel (flat). Here, each of these four cases was compared against each other and to other DNS studies performed on parallel flows. The results indicate that the bulk involute channel flow does not differ significantly from a flat parallel channel flow and that the curvature of the walls does not significantly alter the mean flow parameters. However, the regions of the involute channel near the side walls exhibit relatively low magnitude twin recirculation structures driven toward the side walls from the centerline of the channel, which warrants further study.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Beam correction for multi-pass arcs in FFA@CEBAF: status update

This work examines the multi-pass steering of six electron beams in an FFA arc ranging from approximately 10.5 GeV to 22 GeV. Shown here is an algorithm based on singular value decomposition (SVD) to successfully steer all six beams through the arc given precise knowledge of all beam positions at each of one hundred and one diagnostic locations with one hundred individual corrector magnets: that is successive application of SVD to different 100 × 101 response matrices—one for each beam energy. Further, a machine learning scheme is developed which only requires knowledge of the energy-averaged beam position at each location to provide equivalent steering. Extension of this scheme to other beam optics quantities as well as transverse and longitudinal coupling is explored.

Accelerator Physics↗
DOE OSTI2021

Notice of Submittal – 2020 Radionuclide Air Emissions Report for Los Alamos National Laboratory

Enclosed is the Calendar Year 2020 Radionuclide Air Emissions Report for the Los Alamos National Laboratory (LANL). The submittal is in compliance with 40 CFR 61 Subpart H. The highest effective dose equivalent to any member of the public from LANL operations in 2020 is 0.29 millirem. This maximally exposed individual location is a business at 132 DP Road, Los Alamos, NM. The annual dose is well below the EPA standard of 10 millirem per year as established in Subpart H.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Effect of Mo precursors in Microwave-assisted Methane Dehydroaromatization over Mo/HZSM5 catalysts

Natural gas flaring occurs in remote shale regions due to limited pipeline takeaway capacity. The conversion of the associated natural gas into aromatics in modular microwave reactors is a viable alternative to monetize the wasted gas. Microwaves offer rapid, selective heating in compact reactor systems that can enable on-demand chemical production at the well-site. Mo-HZSM-5 catalysts are widely used for aromatic production, but the location and nature of the active sites are still under debate. This study focuses on the use of 6 different Mo precursors to elucidate insights into the Mo properties that are desirable for BTX production. The catalysts were characterized by different methods (XPS, TPR, Raman, etc) to determine differences in Mo catalytic properties that may affect performance and understand these differences through performance testing under microwave at 700C for methane dehydroaromatization. Metal precursors that enable a better distribution of Mo into the pores and over the surface lead to improved benzene yield, whereas those that limited Mo to primarily the surface suffer rapid deactivation and low benzene yields. Additionally, strong Lewis acidity that arises from the sodium containing precursor drastically shifts the product selectivity towards dehydrogenation, which produces more ethylene and carbon. This catalyst had the highest deactivation constant of all catalysts tested.

gas flaring reduction↗
DOE OSTI2022

On the similarity of hillslope hydrologic function: a clustering approach based on groundwater changes

Abstract. Hillslope similarity is an active topic in hydrology because of its importance in improving our understanding of hydrologic processes and enabling comparisons and paired studies. In this study, we propose a holistic bottom-up hillslope clustering based on a region's integrative hydrodynamic response quantified by the seasonal changes in groundwater levels ΔP. The main advantage of the ΔP clustering is its ability to capture recharge and discharge processes. We test the performance of the ΔP clustering by comparing it to seven other common hillslope clustering approaches. These include clustering approaches based on the aridity index, topographic wetness index, elevation, land cover, and machine-learning that jointly integrate multiple data. We assess the ability of these clustering approaches to identify and categorize hillslopes with similar static characteristics, hydroclimate, land surface processes, and subsurface dynamics in a mountainous watershed – the East River – located in the headwaters of the Upper Colorado River Basin. The ΔP clustering performs very well in identifying hillslopes with six out of the nine characteristics studied. The variability among clusters as quantified by the coefficient of variation (0.2) is less in the ΔP and the machine learning approaches than in the others (> 0.3 for TWI, elevation, and land cover). We further demonstrate the robustness of the ΔP clustering by testing its ability to predict hillslope responses to wet and dry hydrologic conditions, of which it performs well when based on average conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Twenty Years of Collaborative Materials Exercises by the Nuclear Forensics International Technical Working Group

The Collaborative Materials Exercise (CMX) series are a critical mechanism used to advance the ITWG's mission of identifying, developing and promoting the best practices of nuclear forensics. These exercises are not designed to test laboratory performance, but as learning experiences that provide opportunities for participants to test and demonstrate state-of-the-practice to the global scientific and law enforcement communities. They are run as mock nuclear forensic investigations under realistic scenarios, with timelines and conditions designed to mimic actual operations. These situations provide the relatively unique opportunity for the appropriate governmental agencies to exercise their collective response to a nuclear security incident. Utilizing well-characterized materials of a known history and origin that are taken from specific process locations within the nuclear fuel cycle, these 'real world' materials are used to fully consider the potential significance of process-derived heterogeneities and characteristics that might be used by investigators to derive useful information such as intended use, point of loss of control, process history or origin. While individual laboratory results are kept confidential, a summary of the major outcomes of each exercise is published in the open literature. The ITWG has carried out six CMXs since 1999. The sixth (CMX-6) and largest (21 participants) was completed in June 2019. Each CMX has contributed demonstrably to advancements in the state of practice and the emergence of novel techniques in nuclear forensic science.

Schwantes, Jon M.↗
DOE OSTI2022

Multimodel ensemble predictions of precipitation using bayesian neural networks

Multimodel ensembling improves predictions and considers model uncertainties. In this study, we present a Bayesian Neural Network (BNN) ensemble approach for large-scale precipitation predictions based on a set of climate models. BNN infers spatiotemporally varying model weights and biases through the calibration against observations. This ensemble scheme of BNN sufficiently leverages individual model skill for accurate predictions as well as provides interpretability about which models contribute more to the ensemble prediction at which locations and times to inform model development. Additionally, BNN accurately quantifies epistemic uncertainty to avoid overconfident projections. We demonstrate BNN’s superior prediction performance to three state-of-the-art ensemble approaches and discuss its interpretability and uncertainty quantification.

Fan, Patrick↗
DOE OSTI2022

Multimodel Ensemble Predictions of Precipitation using Bayesian Neural Networks

Multimodel ensembling improves predictions and considers model uncertainties. In this study, we present a Bayesian Neural Network (BNN) ensemble approach for large-scale precipitation predictions based on a set of climate models. BNN infers spatiotemporally varying model weights and biases through the calibration against observations. This ensemble scheme of BNN sufficiently leverages individual model skill for accurate predictions as well as provides interpretability about which models contribute more to the ensemble prediction at which locations and times to inform model development. Additionally, BNN accurately quantifies epistemic uncertainty to avoid overconfident projections. We demonstrate BNN’s superior prediction performance to three state-of-the-art ensemble approaches and discuss its interpretability and uncertainty quantification.

Fan, Patrick↗
DOE OSTI2023

Energy Data from Heat Pumps Installed in Juneau, AK

Heat pumps offer a great low carbon emission method to heat homes. Thermalize Juneau 2021 was a clean energy campaign that helped homeowners in Juneau, Alaska install heat pumps into their homes. Juneau is located near the climactic limit of many heat pumps, and we were interested in how well the heat pumps can function in cold climates. This was done by using Sense meters to remotely monitor the energy usage of 10 homes with heat pumps. The Sense meters are small devices that connect to the electrical panel and monitor the energy use of multiple appliances through machine learning. First, we recorded the energy usage of a heat pump in the lab using both the Sense meter and the existing lab datalogger. Both recorded very similar energy usage data which confirmed that the Sense meter can accurately measure the fluctuations in the heat pump energy use. Next, we looked at the energy data from the Sense meters in the homes with heat pumps and paired it with local weather data to see how well the heat pumps functioned in the cold weather.

Alaska↗