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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 NTRS2002

Near-Infrared Spectrophotometry of Phobos and Deimos

We have observed the leading and trailing hemispheres of Phobos from 1.65 to 3.5 microns and Deimos from 1.65 to 3.12 microns near opposition. We find the trailing hemisphere of Phobos to be brighter than its leading hemisphere by 0.24 +/- 0.06 magnitude at 1.65 microns and brighter than Deimos by 0.98 +/- 0.07 magnitude at 1.65 microns. We see no difference larger than observational uncertainties in spectral slope between the leading and trailing hemispheres when the spectra are normalized to 1.65 microns. We find no 3-micron absorption feature due to hydrated minerals on either hemisphere to a level of approx. 5-10% on Phobos and approx. 20% on Deimos. When the infrared data are joined to visible and near-IR data obtained by previous workers, our data suggest the leading (Stickney-dominated) side of Phobos is best matched by T-class asteroids. The spectral slope of the trailing side of Phobos and leading side of Deimos are bracketed by the D-class asteroids. The best laboratory spectral matches to these parts of Phobos are mature lunar soils and heated carbonaceous chondrites. The lack of 3-micron absorption features on either side of Phobos argues against the presence of a large interior reservoir of water ice according to current models of Phobos' interior.

Rivkin, A. S.↗
NASA NTRS2002

Near-Infrared Spectrophotometry of Phobos and Deimos

We have observed the leading and trailing hemispheres of Phobos from 1.65 to 3.5 microns and Deimos from 1.65 to 3.12 microns near opposition. We find the trailing hemisphere of Phobos to be brighter than its leading hemisphere by 0.24 +/- 0.06 magnitude at 1.65 microns and brighter than Deimos by 0.98 +/- 0.07 magnitude at 1.65 microns. We see no difference larger than observational uncertainties in spectral slope between the leading and trailing hemispheres when the spectra are normalized to 1.65 microns. We find no 3-microns absorption feature due to hydrated minerals on either hemisphere to a level of approx. 5 - 10% on Phobos and approx. 20% on Deimos. When the infrared data are joined to visible and near-IR data obtained by previous workers, our data suggest the leading (Stickney-dominated) side of Phobos is best matched by T-class asteroids. The spectral slope of the trailing side of Phobos and leading side of Deimos are bracketed by the D-class asteroids. The best laboratory spectral matches to these parts of Phobos are mature lunar soils and heated carbonaceous chondrites. The lack of 3-microns absorption features on either side of Phobos argues against the presence of a large interior reservoir of water ice according to current models of Phobos' interior.

Rivkin, A. S.↗
NASA NTRS1990

Unidentified ions in comets

Optical spectra were taken of comets Halley, West, and Brorsen-Metcalf in the wavelength region 3200 to 6400 A. These spectra were offset approximately 10(exp -5) to 10(exp -6) km tailward from the nucleus so that the features detected were all ions with the exception of a very small residual C2 emission at 5165 A. The full labeled tail spectrum of comet Halley is given. While most of the features detected are attributable to CO(+), H2O(+), CO2(+), CH(+), and OH(+), there are three moderately strong bands in the spectra of comets Halley and Brorsen-Metcalf which remain unidentified. These features were not detected in comet West. All three spectra in the 4800 to 5400 A region are presented, Brorsen-Metcalf is the gassiest of the three. The central wavelengths of the unidentified features are 4930, 5300, and 6000 A. In an effort to identify the ions responsible for these features as well as to confirm previous identifications, laboratory spectra of ions were compared with the comet spectra. H2O(+) and CO(+) are known to have extensive emission in the 4800 to 6200 A region. Therefore, the possibility that these unidentified features are due to H2O(+) and CO(+) was investigated. A search for the following bands was conducted: H2O(+) (11-0), H2O(+) (12-0), H2O(+) (13-1), CO(+) (1-1), and CO(+) (0-0). CO(+) (1-1) and CO(+) (0-0) were previously identified and are present in all the spectra examined. The H2O(+) (11-0) band was identified. Comparison of the H2O(+) (11-0) synthetic spectrum with comet Brorsen-Metcalf data is presented. The relative fluxes of the blended H2O(+) lines in the synthetic spectrum match those of the cometary data. After eliminating H2O(+) and CO(+) as significant contributors to the stronger unidentified features, spectra of ions which are not yet identified in the optical region of comets were compared to the data. These ions are NH(+), CS(+), and C2(+). None of these ions appears to be a significant contributor to the optical spectra of these three comets. In conclusion, H2O(+) (11-0) was unabiguously identified in cometary optical spectra. No other molecular ion for which there are laboratory spectra can explain the unidentified features found in the ion tails of comets Halley and Brorsen-Metcalf.

Engel, Lisa↗
DOE OSTI2020

The Human Phenotype Ontology in 2021

The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for phenotype exchange. The HPO has grown steadily since its inception due to considerable contributions from clinical experts and researchers from a diverse range of disciplines. Here, we present recent major extensions of the HPO for neurology, nephrology, immunology, pulmonology, newborn screening, and other areas. For example, the seizure subontology now reflects the International League Against Epilepsy (ILAE) guidelines and these enhancements have already shown clinical validity. We present new efforts to harmonize computational definitions of phenotypic abnormalities across the HPO and multiple phenotype ontologies used for animal models of disease. These efforts will benefit software such as Exomiser by improving the accuracy and scope of cross-species phenotype matching. The computational modeling strategy used by the HPO to define disease entities and phenotypic features and distinguish between them is explained in detail. We also report on recent efforts to translate the HPO into indigenous languages. Finally, we summarize recent advances in the use of HPO in electronic health record systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Origin of insulating and nonferromagnetic SrRuO 3 monolayers

The electro-magnetic properties of ultrathin epitaxial ruthenate films have long been the subject of debate. Here we combine experimental with theoretical investigations of (SrTiO 3 ) 5 -(SrRuO 3 ) n -(SrTiO 3 ) 5 (STO 5 -SRO n -STO 5 ) heterostructures with n = 1 and 2 unit cells, including extensive atomic-resolution scanning-transmission-electron-microscopy imaging, electron-energy-loss-spectroscopy chemical mapping, as well as transport and magneto-transport measurements. The experimental data demonstrate that the STO 5 -SRO 2 -STO 5 heterostructure is nearly stoichiometric, metallic, and ferromagnetic with T C ~ 128 K, even though it lacks the characteristic bulk-SRO octahedral tilts and matches the cubic STO structure. In contrast, the STO 5 -SRO 1 -STO 5 heterostructure features Ru-Ti intermixing in the RuO 2 layer, also without octahedral tilts, but is accompanied by a loss of metallicity and ferromagnetism. Density-functional-theory calculations show that stoichiometric n = 1 and n = 2 heterostructures are metallic and ferromagnetic with no octahedral tilts, while non-stoichiometry in the Ru sublattice in the n = 1 case opens an energy gap and induces antiferromagnetic ordering. Furthermore, the results indicate that the observed non-stoichiometry is the cause of the observed loss of metallicity and ferromagnetism in the n = 1 case.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1988

Modal analysis applied to circular, rectangular, and coaxial waveguides

Recent developments in the analysis of various waveguide components and feedhorns using Modal Analysis (Mode Matching Method) are summarized. A brief description of the theory is presented, and the important features of the method are pointed out. Specific examples in circular, rectangular, and coaxial waveguides are included, with comparisons between the theory and experimental measurements. Extensions to the methods are described.

Hoppe, D. J.↗
NASA NTRS1987

Image-analysis techniques for determination of morphology and kinematics in arctic sea ice

SAR data have been used to study sea ice with respect to its motion and formation/deformation. With the prospect of the Alaska SAR Facility development in the near future, there is a great need for robust and efficient sea-ice analysis techniques. This paper presents a sea-ice motion analysis technique that can be used for: (1) local motion analysis of a selected ice patch, and (2) a global ice motion over the entire image area. In order to meet the operational speed requirement (over fifty images per day) a sea-ice motion analysis technique has been developed which requires very little human interaction. The proposed technique uses a subset of easily distinguishable features to predict global motion characteristics. The developed technique is applied to two pairs of SEASAT SAR images, one pair with a minor motion of 'ice pack' and another with a larger and discontinuous motion of 'fast ice'. The new approach enables the development of a set of computer-aided tools for feature selection and registration and the implementation of an optimal search strategy for automatic template matching via a motion prediction model.

Lee, Meemong↗
NASA NTRS2008

Pattern-Recognition System for Approaching a Known Target

A closed-loop pattern-recognition system is designed to provide guidance for maneuvering a small exploratory robotic vehicle (rover) on Mars to return to a landed spacecraft to deliver soil and rock samples that the spacecraft would subsequently bring back to Earth. The system could be adapted to terrestrial use in guiding mobile robots to approach known structures that humans could not approach safely, for such purposes as reconnaissance in military or law-enforcement applications, terrestrial scientific exploration, and removal of explosive or other hazardous items. The system has been demonstrated in experiments in which the Field Integrated Design and Operations (FIDO) rover (a prototype Mars rover equipped with a video camera for guidance) is made to return to a mockup of Mars-lander spacecraft. The FIDO rover camera autonomously acquires an image of the lander from a distance of 125 m in an outdoor environment. Then under guidance by an algorithm that performs fusion of multiple line and texture features in digitized images acquired by the camera, the rover traverses the intervening terrain, using features derived from images of the lander truss structure. Then by use of precise pattern matching for determining the position and orientation of the rover relative to the lander, the rover aligns itself with the bottom of ramps extending from the lander, in preparation for climbing the ramps to deliver samples to the lander. The most innovative aspect of the system is a set of pattern-recognition algorithms that govern a three-phase visual-guidance sequence for approaching the lander. During the first phase, a multifeature fusion algorithm integrates the outputs of a horizontal-line-detection algorithm and a wavelet-transform-based visual-area-of-interest algorithm for detecting the lander from a significant distance. The horizontal-line-detection algorithm is used to determine candidate lander locations based on detection of a horizontal deck that is part of the lander.

Huntsberger, Terrance↗
NASA NTRSDate not supplied

Classifying Agnostic Biosignatures using Raman, VNIR, and Elemental Data

How can we use our current wealth of terrestrial data, encompassing biogenic and abiogenic systems, to determine the distinguishing properties of life? SCOBI (Statistical Classification of Biosignature Information) uses machine learning techniques to algorithmically identify combinations of measurements that are “indicative of life”. A set of ~1000 observations, comprising elemental abundance, isotopic fractionation, VNIR reflectance, and (in progress) Raman spectra, have been assembled from existing literature and databases. The observations cover systems classified as “indicative alive” (e.g., cells, vegetation), “indicative non-alive” (e.g., fossils, teeth), “mixed indicative” (e.g., soil, pond water), or “non-indicative” (e.g., rocks, meteorites). VNIR data was preprocessed by linear interpolation from 400-2100 nm and smoothed with a Savitzky-Golay filter. To limit the amount of Earth-biochemistry-specific (non-agnostic) information included, the first five spectral features extracted were number of peaks, number of troughs, mean reflectance, mean peak width, and broadest peak width. To help further emphasize agnostic biosignatures, Earth-specific features such as chlorophylls have been manually flagged so that feature importance with and without them can be compared. Classifiers including k-nearest neighbors (KNN), Gaussian Naïve Bayes (GNB), logistic regression (LR), random forest (RF), and support vector machine (SVM) were implemented, as was a combination voting classifier. Performance metrics included false positive rates, false negative rates, and AUC with 50-50 test/train splits (Monte Carlo simulations). Key takeaways from this stage, prior to the inclusion of Raman spectra, are (1) the overall success rate of 0.933 AUC was most heavily influenced by the elemental abundance data; and (2) VNIR reflectance had the lowest classification performance with 0.52 AUC (58% of objects correctly classified). The next steps are to complete integration of Raman spectral data and to improve the approach to pre-processing and feature extraction for both types of spectral data, such as automated baseline removal, whole spectrum matching, and dimensionality reduction.

Biosignatures↗
NASA NTRS1988

A knowledge-based object recognition system for applications in the space station

A knowledge-based three-dimensional (3D) object recognition system is being developed. The system uses primitive-based hierarchical relational and structural matching for the recognition of 3D objects in the two-dimensional (2D) image for interpretation of the 3D scene. At present, the pre-processing, low-level preliminary segmentation, rule-based segmentation, and the feature extraction are completed. The data structure of the primitive viewing knowledge-base (PVKB) is also completed. Algorithms and programs based on attribute-trees matching for decomposing the segmented data into valid primitives were developed. The frame-based structural and relational descriptions of some objects were created and stored in a knowledge-base. This knowledge-base of the frame-based descriptions were developed on the MICROVAX-AI microcomputer in LISP environment. The simulated 3D scene of simple non-overlapping objects as well as real camera data of images of 3D objects of low-complexity have been successfully interpreted.

Dhawan, Atam P.↗
NASA NTRS1988

Topological numbering of features on a mesh

Assume a nxn binary image is given containing horizontally convex features; i.e., for each feature, each of its row's pixels form an interval on that row. The problem of assigning topological numbers to such features is considered; i.e., assign a number to every feature f so that all features to the left of f have a smaller number assigned to them. This problem arises in solutions to the stereo matching problem. A parallel algorithm to solve the topological numbering problem in O(n) time on an nxn mesh of processors is presented. The key idea of the solution is to create a tree from which the topological numbers can be obtained even though the tree does not uniquely represent the to the left of relationship of the features.

Atallah, Mikhail J.↗
DOE OSTI2024

Progressive Dynamics for Cloth and Shell Animation

We propose Progressive Dynamics, a coarse-to-fine, level-of-detail simulation method for the physics-based animation of complex frictionally contacting thin shell and cloth dynamics. Progressive Dynamics provides tight-matching consistency and progressive improvement across levels, with comparable quality and realism to high-fidelity, IPC-based shell simulations [Li et al. 2021] at finest resolutions. Together these features enable an efficient animation-design pipeline with predictive coarse-resolution previews providing rapid design iterations for a final, to-be-generated, high-resolution animation. In contrast, previously, to design such scenes with comparable dynamics would require prohibitively slow design iterations via repeated direct simulations on high-resolution meshes. We evaluate and demonstrate Progressive Dynamics's features over a wide range of challenging stress-tests, benchmarks, and animation design tasks. Here Progressive Dynamics efficiently computes consistent previews at costs comparable to coarsest-level direct simulations. Its matching progressive refinements across levels then generate rich, high-resolution animations with high-speed dynamics, impacts, and the complex detailing of the dynamic wrinkling, folding, and sliding of frictionally contacting thin shells and fabrics.

Computer Science↗
NASA NTRS1972

Star sensor/mapper with a self deployable, high-attenuation light shade for SAS-B

A star sensor/mapper to determine positional data for the small astronomy satellites was tested to detect stars of plus 4 visual magnitude. It utilizes two information channels with memory so that it can be used with a low-data-rate telemetry system. One channel yields star amplitude information; the other yields the time of star occurrence as the star passes across an N-slit reticle/photomultiplier detector system. Some of the features of the star sensor/mapper are its low weight of 6.5 pounds, low power consumption of 0.4 watt, bandwidth switching to match the satellite spin rate, optical equalization of sensitivity over the 5-by-10 deg field of view, and self-deployable sunshade. The attitude determination accuracy is 3 arc minutes. This is determined by such parameters as the reticle configuration, optical train, and telemetry readout. The optical and electronic design of the star sensor/mapper, its expansion capabilities, and its features are discussed.

Schenkel, F. W.↗
DOE OSTI2025

A Computational Framework to design 3D stiffness gradient acoustic metamaterials for impedance matching

Acoustic waves play a crucial role in various applications, including medical imaging, non-destructive testing, and sonar systems. One of the significant challenges in these applications is impedance matching, which is essential for minimizing reflections and maximizing the transfer of acoustic energy between different media. Acoustic metamaterials offer a promising solution to this challenge. In addition to impedance control, gradient stiffness can enhance structural efficiency and enable spatial control of wave propagation, making it a valuable feature in acoustic metamaterial design. In this pa- per, we present our developed computational method to design 3D stiffness gradient acoustic metamaterials for impedance matching. The key steps in our approach include generating initial designs using a periodic covariance function to provide unit cells that are both periodic on the boundaries and randomly formed inside the unit cell. Furthermore, we integrated manufacturing constraints into the design process, ensuring that the structures are interconnected for fabrication. We propose two computational optimization algorithms: GenUnit, based on a non-dominated sorting genetic algorithm (NSGA-II), and MLMatch, which leverages differentiable machine learning. The two approaches are not separate contributions but complementary com- ponents of a unified framework. GenUnit requires no training data and directly interfaces with physics-based simulations, making it highly accurate but slower for large-scale exploration. In contrast, MLMatch is data-hungry during training but, once trained, enables near-instantaneous inference and broad design-space coverage. Together, they form a hybrid strategy: ML- Match rapidly explores the global design space, and GenUnit provides local refinement with high-fidelity accuracy. This balance between training cost, inference time, and precision is the motivation for including both methods in the same study. We applied this dual-algorithm framework to generate two metallic-based metamaterial designs that match the acoustic impedance of water while exhibiting a controlled gradient in stiffness (from stiff to soft). The stiffness gradient is particularly advantageous in applications where one side of the structure must interface with soft or sensitive surfaces, such as human tissue or delicate components. Here, this work paves the way for improved materials in various acoustic applications, particularly in ultrasound devices, by providing better impedance.

Metamaterial↗
DOE OSTI2026

Dara: Automated Multiple-Hypothesis Phase Identification and Refinement from Powder X-ray Diffraction

Powder X-ray diffraction (XRD) is a foundational technique for characterizing crystalline materials. However, the reliable interpretation of XRD patterns, particularly in multiphase systems, remains a manual and expertise-demanding task. As a characterization method that only provides structural information, multiple reference phases can often be fit to a single pattern, leading to potential misinterpretation when alternative solutions are overlooked. To ease humans’ efforts and address the challenge, we introduce Dara (data-driven automated Rietveld analysis), a framework designed to automate the robust identification and refinement of multiple phases from powder XRD data. Dara performs an exhaustive tree search over all plausible phase combinations within a given chemical space and validates each hypothesis using the BGMN Rietveld refinement routine. Key features include structural database filtering, automatic clustering of isostructural phases during tree expansion, and peak-matching-based scoring to identify promising phases for refinement. When ambiguity exists, Dara generates multiple hypothesis which can then be decided between by human experts or with further characterization tools. By enhancing the reliability and accuracy of phase identification, Dara enables scalable analysis of realistic complex XRD patterns and provides a foundation for integration into multimodal characterization workflows, moving toward fully self-driving materials discovery.

Biological databases↗
DOE OSTI2022

Multiomic atlas with functional stratification and developmental dynamics of zebrafish cis -regulatory elements

Zebrafish, a popular organism for studying embryonic development and for modeling human diseases, has so far lacked a systematic functional annotation program akin to those in other animal models. To address this, we formed the international DANIO-CODE consortium and created a central repository to store and process zebrafish developmental functional genomic data. Our data coordination center (https://danio-code.zfin.org) combines a total of 1,802 sets of unpublished and re-analyzed published genomic data, which we used to improve existing annotations and show its utility in experimental design. We identified over 140,000 cis-regulatory elements throughout development, including classes with distinct features dependent on their activity in time and space. We delineated the distinct distance topology and chromatin features between regulatory elements active during zygotic genome activation and those active during organogenesis. Finally, we matched regulatory elements and epigenomic landscapes between zebrafish and mouse and predicted functional relationships between them beyond sequence similarity, thus extending the utility of zebrafish developmental genomics to mammals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Design and implementation of a prototype infrared video bolometer (IRVB) in MAST Upgrade

A prototype infrared video bolometer (IRVB) was successfully deployed in the Mega Ampere Spherical Tokamak Upgrade (MAST Upgrade or MAST-U), the first deployment of such a diagnostic in a spherical tokamak. The IRVB was designed to study the radiation around the lower x-point, another first in tokamaks, and has the potential to estimate emissivity profiles with spatial resolution beyond what is achievable with resistive bolometry. The system was fully characterized prior to installation on MAST-U, and the results are summarized here. After installation, it was verified that the actual measurement geometry in the tokamak qualitatively matches the design; this is a particularly difficult process for bolometers and was done using specific features of the plasma itself. The installed IRVB measurements are consistent both with observations from other diagnostics, including magnetic reconstruction, visible light cameras, and resistive bolometry, as well as with the IRVB-designed view. Early results show that with conventional divertor geometry and only intrinsic impurities (for example, C and He), the progression of radiative detachment follows a similar path to that observed for large aspect ratio tokamaks: The peak of the radiation moves along the separatrix from the targets to the x-point and high-field side midplane with a toroidally symmetric structure that can eventually lead to strong effects on the core plasma inside the separatrix.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

The role of the turbulence driving mode for the initial mass function

Turbulence is a critical ingredient for star formation, yet its role for the initial mass function (IMF) is not fully understood. Here we perform magnetohydrodynamical (MHD) simulations of star cluster formation including gravity, turbulence, magnetic fields, stellar heating, and outflow feedback to study the influence of the mode of turbulence driving on IMF. We find that simulations that employ purely compressive turbulence driving (COMP) produce a higher fraction of low-mass stars as compared to simulations that use purely solenoidal driving (SOL). The characteristic (median) mass of the sink particle (protostellar) distribution for COMP is shifted to lower masses by a factor of ∼1.5 compared to SOL. Our simulation IMFs capture the important features of the observed IMF form. We find that turbulence-regulated theories of the IMF match our simulation IMFs reasonably well in the high-mass and low-mass range, but underestimate the number of very low-mass stars, which form towards the later stages of our simulations and stop accreting due to dynamical interactions. Our simulations show that for both COMP and SOL, the multiplicity fraction is an increasing function of the primary mass, although the multiplicity fraction in COMP is higher than that of SOL for any primary mass range. We find that binary mass ratio distribution is independent of the turbulence driving mode. The average specific angular momentum of the sink particles in SOL is a factor of 2 higher than that for COMP. Overall, we conclude that the turbulence driving mode plays a significant role in shaping the IMF.

79 ASTRONOMY AND ASTROPHYSICS↗