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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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Brought to Light. I. Quantification of Disk Substructure in Dwarf Early-type Galaxies

Dwarf early-type galaxies (ETGs) display a rich diversity in their photometric, structural, and dynamical properties. In this work, we address their structural complexity by studying with deep imaging a sample of nine dwarf ETGs from the Virgo galaxy cluster, characterized by having faint disk features such as bars and spiral arms, that lie mostly hidden within the bright diffuse light of the galaxies. We present a new, robust method that aims to identify and extract the disk substructure embedded in these dwarf ETGs. The method consists in an iterative procedure that gradually separates a galaxy image into two components: the bright, dominant, diffuse component, and the much fainter, underlying disk component. By applying it to the dwarf ETG sample, we quantify their disk substructure and find that its relative contribution to the total galaxy light ranges between 2.2% and 6.4% within two effective radii. We test the reliability of the method, and prove that it is accurate in recovering the disk substructure we introduce in mock galaxy images, even at low disk-to-total light fractions of a few percent. As a potential application of the method, we perform a Fourier analysis on the extracted disk substructures and measure the orientation, length, and strength of the bars, as well as the pitch angle and strength of the spiral arms. We also briefly discuss a scenario based on the numerical simulations presented in our companion paper, Brought to Light II: Smith et al., in which we investigate the origins of the substructure in such dwarf systems.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1973

Ratio maps of iron ore deposits Atlantic City district, Wyoming

Preliminary results of a spectral rationing technique are shown for a region at the southern end of the Wind River Range, Wyoming. Digital ratio graymaps and analog ratio images have been produced for the test site, but ground truth is not yet available for thorough interpretation of these products. ERTS analog ratio images were found generally better than either ERTS single-channel images or high altitude aerial photos for the discrimination of vegetation from non-vegetation in the test site region. Some linear geological features smaller than the ERTS spatial resolution are seen as well in ERTS ratio and single-channel images as in high altitude aerial photography. Geochemical information appears to be extractable from ERTS data. Good preliminary quantitative agreement between ERTS-derived ratios and laboratory-derived reflectance ratios of rocks and minerals encourage plans to use lab data as training sets for a simple ratio gating logic approach to automatic recognition maps.

Vincent, R. K.↗
NASA NTRS1979

A seasonal climate model for earth

A simple seasonal climate model for earth is developed on the basis of a few terms extracted from monthly and zonally averaged climatic data fields represented in latitude by Legendre polynomials and in time by Fourier series. This simple, physically motivated model accounts for the gross features of the present zonally averaged seasonal climate (root mean square error of two deg C). The sensitivities of the seasonal model and a corresponding mean annual model are approximately equal if ice and snow lines (for albedo purposes) are attached to certain mean-annual and instantaneous isotherms. More dynamics (in particular, cryospheric) are needed in the seasonal model to explain the relationship between glacial rhythms and changes in the earth's orbital elements.

North, G. R.↗
NASA NTRS1990

Parameter identification of aeroelastic modes of rotary wings from transient time histories

A novel moving-block technique is presented for parameter-identification tasks concerning the aeroelastic modes of rotary wings, using a least-squares solver in the time domain to estimate dampings and eigenvector components. The least-squares moving-block (LSMB) technique is shown to yield superior estimates to those of the previous moving-block technique for four different analytical test cases. An additional advantage of the LSMB approach is its ability to estimate eigenvector components with good accuracy; this feature is useful in assessing the coupling of the different modes. The method can also be used to perform periodic modal identification, and is applicable to experimental data for the extraction of modal information.

Amrani, Ahmed Omar↗
NASA NTRS1990

Advanced-technology space station study: Summary of systems and pacing technologies

The principal system features defined for the Advanced Technology Space Station are summarized and the 21 pacing technologies identified during the course of the study are described. The descriptions of system configurations were extracted from four previous study reports. The technological areas focus on those systems particular to all large spacecraft which generate artificial gravity by rotation. The summary includes a listing of the functions, crew requirements and electrical power demand that led to the studied configuration. The pacing technologies include the benefits of advanced materials, in-orbit assembly requirements, stationkeeping, evaluations of electrical power generation alternates, and life support systems. The descriptions of systems show the potential for synergies and identifies the beneficial interactions that can result from technological advances.

Butterfield, A. J.↗
NASA NTRS2000

The Athena Raman Spectrometer

Raman spectroscopy provides a powerful tool for in situ mineralogy, petrology, and detection of water and carbon. The Athena Raman spectrometer is a microbeam instrument intended for close-up analyses of targets (rock or soils) selected by the Athena Pancam and Mini-TES. It will take 100 Raman spectra along a linear traverse of approximately one centimeter (point-counting procedure) in one to four hours during the Mars' night. From these spectra, the following information about the target will extracted: (1) the identities of major, minor, and trace mineral phases, organic species (e.g., PAH or kerogen-like polymers), reduced inorganic carbon, and water-bearing phases; (2) chemical features (e.g. Mg/Fe ratio) of major minerals; and (3) rock textural features (e.g., mineral clusters, amygdular filling and veins). Part of the Athena payload, the miniaturized Raman spectrometer has been under development in a highly interactive collaboration of a science team at Washington University and the University of Alabama at Birmingham, and an engineering team at the Jet Propulsion Laboratory. The development has completed the brassboard stage and has produced the design for the engineering model.

Wang, Alian↗
DOE OSTI2021

Unexpected inverse correlations and cooperativity in ion-pair phase transfer

Liquid/liquid extraction is one of the most widely used separation and purification methods, where a forefront of research is the study of transport mechanisms for solute partitioning and the relationships that these have to solution structure at the phase boundary. To date, organized surface features that include protrusions, water-fingers, and molecular hinges have been reported. Many of these equilibrium studies have focused upon small-molecule transport – yet the extent to which the complexity of the solute, and the competition between different solutes, influence transport mechanisms have not been explored. Here we report molecular dynamics simulations that demonstrate that a metal salt (LiNO 3 ) can be transported via a protrusion mechanism that is remarkably similar to that reported for H 2 O by tri-butyl phosphate (TBP), a process that involves dimeric assemblies. Yet the LiNO 3 out-competes H 2 O for a bridging position between the extracting TBP dimer, which in-turn changes the preferred transport pathway of H 2 O. Examining the electrolyte concentration dependence on ion-pair transport unexpectedly reveals an inverse correlation with the extracting surfactant concentration. As [LiNO 3 ] increases, surface adsorbed TBP becomes a limiting reactant in correlation with an increased negative surface charge induced by excess interfacial NO 3 – , however the rate of transport is enhanced. Within the highly dynamic interfacial environment, we hypothesize that this unique cooperative effect may be due to perturbed surface organization that either decreases the energy of formation of transporting protrusion motifs or makes it easier for these self-assembled species to disengage from the surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Component-based SHGC determination of BIPV glazing for product comparison

Building-integrated photovoltaic (BIPV) systems are intrinsically designed to generate electricity and to provide at least one building-related function. When BIPV modules act as glazing products in windows, skylights or curtain walls, their ability to control the transmission of solar energy into the building must be characterised by a Solar Heat Gain Coefficient (SHGC) or g value (also known as Total Solar Energy Transmittance – TSET – or “solar factor”). For the comparison of BIPV glazing products consisting of one PV laminate and possibly further, conventional glazing layers separated by gas-filled cavities, the procedures documented in international standards for architectural glazing (e.g. ISO 9050 and EN 410) form a suitable starting point. Easily implemented modifications to these procedures are proposed to take both optical inhomogeneity (if relevant) and extraction of electricity from BIPV glazing units into account. Geometrically complex glazing and shading devices, and light-scattering glazing layers, are outside the scope of the proposed methodology; SHGC determination for obliquely incident solar radiation is also excluded. For these cases, the experimental calorimetric approach documented in [ISO 19467:2017; ISO 19467-2:2021] is recommended. The paper also presents results and conclusions from an implementation exercise and sensitivity study carried out by participants of the IEA-PVPS Task 15 on BIPV. The cell coverage ratio in the PV laminate, the thermal resistance offered by the glazing configuration, the choice of boundary conditions and the effect of extracting electricity were all identified as parameters which significantly affect the SHGC value determined for a given type of BIPV glazing. A practicable approach to accommodate the great variety of dimensions typical for BIPV glazing is also proposed. These findings should pave the way for modifying the existing component-based standards for architectural glazing to take the specific features of BIPV glazing into account.

14 SOLAR ENERGY↗
DOE OSTI2025

Lowering the barrier to access information-rich transient kinetic data for machine learning methods

Transient kinetic data contain a wealth of information about intrinsic features of a catalyst as well as the reaction mechanism. Currently, high volume transient data is underutilized, and data science methods could both increase the value of information that can be extracted from this data, integrate experimental with theoretical data sources, and accelerate the pace of catalyst technology advancement. Transient kinetic characterizations with simple probe molecules exhibiting reversible adsorption, irreversible adsorption and bulk-surface diffusion are presented as training components for similar experiments with more complex surface reactions. In conclusion, by increasing the availability and accessibility of transient kinetic data through details of its structure and acquisition, we aim to decrease the barrier for data scientists to apply machine learning methods to this valuable data source.

Catalysis↗
DOE OSTI2025

Revisiting the assignment of atomic charges in metal oxides based on core-level x-ray photoelectron spectra: The case of Ti in SrTiO3(001)

We demonstrate that assigning formal charges to transition metal (TM) cations based on core-level (CL) x-ray photoemission binding energies in oxides leads to physically inconsistent pictures of electronic structure. O 2p–TM 3d hybridization is well known to result in significant covalency in TM–O bonds, thereby reducing TM cation charges from their fully ionic values. However, the ionic bonding model remains the working paradigm for assigning TM CL features, and the resulting cation charges are often taken to be representative of the material under study. Here, we show that a more physically meaningful way to assign charges is to extract information about charge distributions utilizing Dirac–Hartree–Fock theory to calculate CL spectra from first principles and then use the resulting wave functions to determine charges based on orbital occupancies. TM cation charges can also be determined using density functional theory and Bader population analysis. We illustrate these two methods using the Ti 2p spectrum for SrTiO3(001) and show that the agreement between them is excellent. Significantly, the resulting Ti charge is considerably lower than the formal charge. The high degree of similarity between the Ti 2p spectrum for SrTiO3 and those for the rutile and anatase polymorphs of TiO2 suggests that the charge densities surrounding Ti in the latter materials are similar to that in SrTiO3. Taking a broader perspective, oxides containing other first-row transition metals also exhibit covalent character, leading to TM cation charges lower than the analogous fully ionic values in these materials as well.

Chambers, Scott A. (ORCID:000000025415043X)↗
DOE OSTI2023

Feature Interpretability

The feature interpretability code is a python module that interprets and analyzes neural networks trained on hydrodynamic simulation output in the form of numpy arrays. The code takes trained neural networks and extracts internal model states in the form of images. Additionally, tools for covariance analysis of network weights and predictions are provided. This code is built on the TensorFlow and PyTorch python libraries, and includes trained networks and example input data for demonstration purposes.

Callis, Skylar↗
DOE OSTI2018

Smart Particle Collector with Real Time Spectroscopic Analysis

Facilities manufacturing materials for nuclear weapons programs release particulate matter to the environment. Particle collections from suspected facilities can help assess proliferation programs. SRNL designs and manufactures unique particle collectors for a variety of applications. The goal of this project is to develop new technologies to develop and manufacture smart particle collectors. Significant engineering advances to the collector were made using the Racetrack, an experimental breadboard setup based on the ACE 1.0 collector. Preliminary experimental results suggest significant improvement in the particle collection efficiency. The new prototype collector, “ESP-EV1”, relies on a two-stage collection region, with higher wire corona currents and voltages. Preliminary results also suggest that it is possible to extract nanoparticulates from a sample containing material from 100 nm to 10 micron-sized particulates. This project also developed new tools for spectroscopic validation of a sample and unique smart features for the collection system.

42 ENGINEERING↗
DOE OSTI2025

FPGA-Based Spill Regulation System for the Muon Delivery Ring at Fermilab

The Muon to Electron Experiment (\acrshort{Mu2e}) requires a uniform beam profile from the Muon Delivery Ring to meet their experimental needs. A specialized Spill Regulation System (\acrshort{SRS}) has been developed to help achieve consistent spill uniformity. The system is based on a custom-designed carrier board featuring an Arria 10 SoC, capable of executing real-time feedback control. The FPGA processes beam pulses of approximately 200 ns every 1.695 microseconds, allowing for continuous monitoring of the extracted spill intensity through fast bunch integration. The system directly controls three quadrupole magnets, which work in conjunction with sextupole magnets to achieve third-order resonant extraction. Furthermore, the board interfaces with Fermilab s Accelerator Control Network (ACNET), enabling operators to modify spill regulation settings in real-time via the control network while providing diagnostic waveforms. These waveforms help operators monitor the process and fine-tune the feedback mechanisms. This paper presents an overview of the board's architecture and its initial progress toward regulating beam extraction. This initial version of the regulation system aims to evaluate baseline performance to inform future system improvements.

Berlioz, Jose Rene [Fermilab]↗
DOE OSTI2024

Identifying Interaction Location in SuperCDMS Detectors

The Super Cryogenic Dark Matter Search (SuperCDMS) experiment uses silicon and germanium particle detectors operated at temperatures of ∼ 30 mK to search for Weakly Interacting Massive Particles (WIMPs), which are candidate dark matter particles that interact weakly with nuclei in the detectors. In operating these detectors, it is required not only to measure the energy of the interaction between the WIMP and the nuclei, but also to reconstruct where the interaction occurred, as the location can be used to separate background interactions from signal and to correct for variations with the location of the energy response. In this project, we, as a team from the University of Minnesota, aim to address the problem of accurately reconstructing the locations of interactions in the SuperCDMS detectors using machine learning methods. The dataset we provided here includes interactions at thirteen different locations from test data taken at the University of Minnesota. For each interaction, a set of parameters was extracted from the signals from each of the five sensors. These parameters represent information known to be sensitive to interaction location, including the relative timing between pulses in different channels, and features like the pulse shape. The relative amplitudes of the pulses are also relevant but due to instabilities in amplification during the test, this data is not included. The parameters included for each interaction are described in our project document. For more details, feel free to check our Github page: https://fair-umn.github.io/FAIR-UMN-CDMS/

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1973

Task 10: an ERTS Experiment for Mapping Iron Compounds, 1383

The author has identified the following significant results. Preliminary results of a spectral ratioing technique are shown for a region at the southern end of the Wind River Range, Wyoming. Digital ratio graymaps and analog ratio images have been produced for the test site, but ground truth is not yet available for thorough interpretation of these products. ERTS-1 analog ratio images were found generally better than either ERTS-1 single channel images or high altitude aerial photos for the discrimination of vegetation from non-vegetation in the test site region. Some linear geological features smaller than the ERTS-1 spatial resolution are seen as well in ERTS-1 ratio and single channel images as in high altitude aerial photography. Geochemical information appears to be extractable from ERTS-1 data. Good preliminary quantitative agreement between ERTS-1 derived ratios and laboratory derived reflectance ratios of rocks and minerals encourage plans to use lab data as training sets for a simple ratio gating logic approach to automatic recognition maps. Empirical atmospheric corrections indicate that atmospheric corrections are needed to make the ratio method, and possibly other types of data processing, consistent over large geographical and temporal displacements.

Vincent, R. K.↗
NASA NTRS2018

Smallholder Crop Area Mapped with Wall-To-Wall WorldView Sub-Meter Panchromatic Image Texture: A Test Case for Tigray, Ethiopia

Global food production in the developing world occurs within sub-hectare fields that are difficult to identify with moderate resolution satellite imagery. Knowledge about the distribution of these fields is critical in food security programs. We developed a semi-automated image segmentation approach using wall-to-wall sub-meter imagery with high-performance computing to map crop area (CA) throughout Tigray, Ethiopia that encompasses over 41,000 km (exp 2). Multiple processing streams were tested to minimize mapping error while applying five unique smoothing kernels to capture differences in land surface texture associated to CA. Typically, very-small fields (mean < 2 ha) have a smooth image roughness compared to natural scrub/shrub woody vegetation at the ~1m scale and these features can be segmented in panchromatic imagery with multi-level histogram thresholding. Multi-temporal very-high resolution (VHR) panchromatic imagery with multi-spectral VHR are sufficient in extracting critical CA information needed in food security programs. A 2011 to 2015 CA map was produced, using over 3000 WorldView-1 panchromatic images wall-to-wall in 1/2 deg mosaics for Tigray, Ethiopia. CA was evaluated with nearly 3000 WorldView-2 2m multispectral 250 X 250 m image subsets by seven expert interpretations, and with in-situ global positioning system photography. CA estimates ranged from 32 to 41% in sub regions of Tigray with median maximum per bin commission and omission errors of 11% and 1% respectively, with most of the error occurring in bins <15%. This empirical, simple, and low direct cost approach via U.S. government license agreement to access commercial VHR data, could be a viable big-data high-performance computing methodology to extract wall-to-wall CA for other regions of the world that have very-small agriculture fields with similar image texture."

Ethiopia↗
NASA NTRSDate not supplied

Implementation of Machine Learning Methods for Crater-Based Navigation

Terrain Relative Navigation methods require surface feature detectors to gain information from images used to improve on-board state estimates. This paper presents the development of a crater detection method based on Machine Learning that can extract data from optical images with different crater shapes and sizes, under varying lighting conditions. This work includes an automated capability for generating labeled training data and iterative testing of the neural network-based crater detector. Preliminary results are included to quantify the detector’s accuracy compared to a known crater catalog, given a set of real lunar images from the Lunar Reconnaissance Orbiter.

Sofia G Catalan↗
DOE OSTI2026

Reducing systematic bias in machine learning applications to J/ψ signal extraction in high-energy nuclear physics

Machine learning techniques are increasingly used in high-energy nuclear physics because they can exploit multivariate correlations more efficiently than conventional cut-based analyses. A central challenge is the construction of training samples that faithfully reproduce the detector response observed in data. Signal samples are usually derived from detector simulations; therefore, mismatches between simulation and data can degrade classifier performance and introduce systematic biases. This work presents two practical correction procedures, namely cumulative distribution function (CDF) mapping and a shift-and-scale transformation, to align simulated signal features with those measured in data. Their performance is demonstrated with $J$/$\psi$ yield measurements in $\sqrt{s_{nn}}$ = 200 GeV Ru+Ru and Zr+Zr collisions recorded by STAR. A set of self-consistency tests shows that these procedures substantially suppress the systematic bias associated with data-simulation discrepancies in machine-learning-based signal extraction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗