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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Synthesis and thermal stability of carborane containing phosphazenes

Carborane substituted polyphosphazenes were prepared by the thermal polymerization of phenyl-carboranyl penta chlorocyclotriphosphazene. Successive isothermal vacuum pyrolyses were conducted on the polymer and examined for structural changes by infrared spectroscopy. The degradation products were ascertained by gas chromatography-mass spectrometric analysis. It was found that the presence of the carborane group improves the thermal stability of the polymer by retarding the ring chain equilibrium processes of decomposition.

Fewell, L. L.↗
NASA NTRS1987

Coherent structures

In order to develop more quantitative measures of coherent structures that would have comparative value over a range of experiments, it is essential that such measures be independent of the observer. It is only through such a general framework that theories with a fundamental predictive value can be developed. The triple decomposition phi = bar-phi + phi(c) + phi(r) (where bar-phi is the mean, phi(c) is the coherent part, and phi(r) is the random part of any turbulent field phi) serves this purpose. The equations of motion for the mean and coherent flow fields, based on the triple decomposition, are presented and modeling methods for the time-averaged and phase-averaged Reynolds stress are discussed.

Speziale, Charles G.↗
NASA NTRS1998

Toward a More Robust Pruning Procedure for MLP Networks

Choosing a proper neural network architecture is a problem of great practical importance. Smaller models mean not only simpler designs but also lower variance for parameter estimation and network prediction. The widespread utilization of neural networks in modeling highlights an issue in human factors. The procedure of building neural models should find an appropriate level of model complexity in a more or less automatic fashion to make it less prone to human subjectivity. In this paper we present a Singular Value Decomposition based node elimination technique and enhanced implementation of the Optimal Brain Surgeon algorithm. Combining both methods creates a powerful pruning engine that can be used for tuning feedforward connectionist models. The performance of the proposed method is demonstrated by adjusting the structure of a multi-input multi-output model used to calibrate a six-component wind tunnel strain gage.

Stepniewski, Slawomir W.↗
NASA NTRS2014

Bulge Growth and Quenching Since Z=2.5 in Candels/3D-HST

Exploiting the deep high-resolution imaging of all 5 CANDELS fields, and accurate redshift informationprovided by 3D-HST, we investigate the relation between structure and stellar populations fora mass-selected sample of 6764 galaxies above 1010 M, spanning the redshift range 0.5 z 2.5.For the first time, we fit 2-dimensional models comprising a single Sersic fit and two-component (i.e.,bulge + disk) decompositions not only to the H-band light distributions, but also to the stellar massmaps reconstructed from resolved stellar population modeling. We confirm that the increased bulgeprominence among quiescent galaxies, as reported previously based on rest-optical observations, remainsin place when considering the distributions of stellar mass. Moreover, we observe an increaseof the typical Sersic index and bulge-to-total ratio (with median BT reaching 40-50) among starforminggalaxies above 1011 M. Given that quenching for these most massive systems is likely tobe imminent, our findings suggest that significant bulge growth precedes a departure from the starformingmain sequence. We demonstrate that the bulge mass (and ideally knowledge of the bulge andtotal mass) is a more reliable predictor of the star-forming versus quiescent state of a galaxy thanthe total stellar mass. The same trends are predicted by the state-of-the-art semi-analytic model bySomerville et al. In the latter, bulges and black holes grow hand in hand through merging andordisk instabilities, and AGN-feedback shuts off star formation. Further observations will be requiredto pin down star formation quenching mechanisms, but our results imply they must be internal to thegalaxies and closely associated with bulge growth.

Quenching↗
NASA NTRS2005

Energy Finite Element Analysis for Computing the High Frequency Vibration of the Aluminum Testbed Cylinder and Correlating the Results to Test Data

The Energy Finite Element Analysis (EFEA) is a finite element based computational method for high frequency vibration and acoustic analysis. The EFEA solves with finite elements governing differential equations for energy variables. These equations are developed from wave equations. Recently, an EFEA method for computing high frequency vibration of structures either in vacuum or in contact with a dense fluid has been presented. The presence of fluid loading has been considered through added mass and radiation damping. The EFEA developments were validated by comparing EFEA results to solutions obtained by very dense conventional finite element models and solutions from classical techniques such as statistical energy analysis (SEA) and the modal decomposition method for bodies of revolution. EFEA results have also been compared favorably with test data for the vibration and the radiated noise generated by a large scale submersible vehicle. The primary variable in EFEA is defined as the time averaged over a period and space averaged over a wavelength energy density. A joint matrix computed from the power transmission coefficients is utilized for coupling the energy density variables across any discontinuities, such as change of plate thickness, plate/stiffener junctions etc. When considering the high frequency vibration of a periodically stiffened plate or cylinder, the flexural wavelength is smaller than the interval length between two periodic stiffeners, therefore the stiffener stiffness can not be smeared by computing an equivalent rigidity for the plate or cylinder. The periodic stiffeners must be regarded as coupling components between periodic units. In this paper, Periodic Structure (PS) theory is utilized for computing the coupling joint matrix and for accounting for the periodicity characteristics.

Vlahopoulos, Nickolas↗
NASA NTRS2009

Highly Scalable Matching Pursuit Signal Decomposition Algorithm

Matching Pursuit Decomposition (MPD) is a powerful iterative algorithm for signal decomposition and feature extraction. MPD decomposes any signal into linear combinations of its dictionary elements or atoms . A best fit atom from an arbitrarily defined dictionary is determined through cross-correlation. The selected atom is subtracted from the signal and this procedure is repeated on the residual in the subsequent iterations until a stopping criterion is met. The reconstructed signal reveals the waveform structure of the original signal. However, a sufficiently large dictionary is required for an accurate reconstruction; this in return increases the computational burden of the algorithm, thus limiting its applicability and level of adoption. The purpose of this research is to improve the scalability and performance of the classical MPD algorithm. Correlation thresholds were defined to prune insignificant atoms from the dictionary. The Coarse-Fine Grids and Multiple Atom Extraction techniques were proposed to decrease the computational burden of the algorithm. The Coarse-Fine Grids method enabled the approximation and refinement of the parameters for the best fit atom. The ability to extract multiple atoms within a single iteration enhanced the effectiveness and efficiency of each iteration. These improvements were implemented to produce an improved Matching Pursuit Decomposition algorithm entitled MPD++. Disparate signal decomposition applications may require a particular emphasis of accuracy or computational efficiency. The prominence of the key signal features required for the proper signal classification dictates the level of accuracy necessary in the decomposition. The MPD++ algorithm may be easily adapted to accommodate the imposed requirements. Certain feature extraction applications may require rapid signal decomposition. The full potential of MPD++ may be utilized to produce incredible performance gains while extracting only slightly less energy than the standard algorithm. When the utmost accuracy must be achieved, the modified algorithm extracts atoms more conservatively but still exhibits computational gains over classical MPD. The MPD++ algorithm was demonstrated using an over-complete dictionary on real life data. Computational times were reduced by factors of 1.9 and 44 for the emphases of accuracy and performance, respectively. The modified algorithm extracted similar amounts of energy compared to classical MPD. The degree of the improvement in computational time depends on the complexity of the data, the initialization parameters, and the breadth of the dictionary. The results of the research confirm that the three modifications successfully improved the scalability and computational efficiency of the MPD algorithm. Correlation Thresholding decreased the time complexity by reducing the dictionary size. Multiple Atom Extraction also reduced the time complexity by decreasing the number of iterations required for a stopping criterion to be reached. The Course-Fine Grids technique enabled complicated atoms with numerous variable parameters to be effectively represented in the dictionary. Due to the nature of the three proposed modifications, they are capable of being stacked and have cumulative effects on the reduction of the time complexity.

Christensen, Daniel↗
DOE OSTI2025

Kernel Manifolds: Nonlinear‐Augmentation Dimensionality Reduction Using Reproducing Kernel Hilbert Spaces

This paper generalizes recent advances on quadratic manifold (QM) dimensionality reduction by developing kernel methods-based nonlinear-augmentation dimensionality reduction. QMs, and more generally feature map-based nonlinear corrections, augment linear dimensionality reduction with a nonlinear correction term in the reconstruction map to overcome approximation accuracy limitations of purely linear approaches. While feature map-based approaches typically learn a least squares optimal polynomial correction term, we generalize this approach by learning an optimal nonlinear correction from a user-defined reproducing kernel Hilbert space. Our approach allows one to impose arbitrary nonlinear structure on the correction term, including polynomial structure, and includes feature map and radial basis function-based corrections as special cases. Furthermore, our method has relatively low training cost and has monotonically decreasing error as the latent space dimension increases. In conclusion, we compare our approach to proper orthogonal decomposition and several recent QM approaches on data from several example problems.

kernel methods↗
DOE OSTI2025

Infrared spectral signatures of interfacial water at TiO 2 –electrolyte interfaces from deep potential molecular dynamics

Vibrational spectroscopy is a powerful tool for probing water at oxide–electrolyte interfaces, but its molecular interpretation can be challenging. Here, we employ deep potential long-range molecular dynamics simulations with layer-resolved spectral analysis to investigate the microscopic origins of the infrared (IR) response of water at the interface with anatase TiO 2 (101), a prototypical oxide surface. The calculated interfacial spectra exhibit characteristic modifications compared to bulk water IR spectra, including enhanced intensities, a red shifted and broadened stretching band, and a higher-frequency shoulder, in qualitative agreement with experiments. Spectral decomposition shows that these signatures originate mainly from the first interfacial water layer, dominated by surface-bound H 2 O at Ti 5C sites, with secondary contributions from the second layer. A moderate salt concentration (0.4 M NaCl) leaves both the interfacial structure and the spectra essentially unchanged, while tuning the pH strongly modulates the spectral intensity. We establish a scaling relation linking the spectral intensity to the surface water dissociation fraction and the dipole moment, both governed by interfacial electric fields. These findings provide a microscopic framework for interpreting IR spectra of oxide–electrolyte interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1975

Stabilization of large-scale systems - A spinning flexible spacecraft

Stabilization of high-order constant systems by multilevel control is proposed in the framework of the decomposition-aggregation method for stability analysis of large-scale systems. An 11-order linear model of a spinning flexible spacecraft is stabilized by the method using both the passive and the active stabilization devices. The method can take advantage of the special structural features of the model to provide the best estimate of the stability region for an important parameter which couples the wobble and the spin motion of the spacecraft.

Siljak, D. D.↗
NASA NTRS1983

Synthesis and thermal stability of carborane-containing phosphazenes

Carborane-substituted polyphosphazenes were prepared by the thermal polymerization of phenyl-carboranyl pentachlorocylotriphosphazene. Successive isothermal vacuum pyrolyses were conducted on the polymer and examined for structural changes by infrared spectroscopy. The degradation products were ascertained by gas chromatography-mass spectrometric analysis. It was found that the presence of the carborane group improves the thermal stability of the polymer by retarding the ring-chain equilibrium processes of decomposition. Previously announced in STAR as A83-21034

Fewell, L. L.↗
NASA NTRS2010

Alternative Modal Basis Selection Procedures for Nonlinear Random Response Simulation

Three procedures to guide selection of an efficient modal basis in a nonlinear random response analysis are examined. One method is based only on proper orthogonal decomposition, while the other two additionally involve smooth orthogonal decomposition. Acoustic random response problems are employed to assess the performance of the three modal basis selection approaches. A thermally post-buckled beam exhibiting snap-through behavior, a shallowly curved arch in the auto-parametric response regime and a plate structure are used as numerical test articles. The results of the three reduced-order analyses are compared with the results of the computationally taxing simulation in the physical degrees of freedom. For the cases considered, all three methods are shown to produce modal bases resulting in accurate and computationally efficient reduced-order nonlinear simulations.

Przekop, Adam↗
NASA NTRS2012

Alternative Modal Basis Selection Procedures For Reduced-Order Nonlinear Random Response Simulation

Three procedures to guide selection of an efficient modal basis in a nonlinear random response analysis are examined. One method is based only on proper orthogonal decomposition, while the other two additionally involve smooth orthogonal decomposition. Acoustic random response problems are employed to assess the performance of the three modal basis selection approaches. A thermally post-buckled beam exhibiting snap-through behavior, a shallowly curved arch in the auto-parametric response regime and a plate structure are used as numerical test articles. The results of a computationally taxing full-order analysis in physical degrees of freedom are taken as the benchmark for comparison with the results from the three reduced-order analyses. For the cases considered, all three methods are shown to produce modal bases resulting in accurate and computationally efficient reduced-order nonlinear simulations.

Przekop, Adam↗
NASA NTRS1981

Structure of correlation tensors in homogeneous anisotropic turbulence

The theory of isotropic tensors, developed by Robertson (1940), Batchelor (1946), and Chandrasekhar (1951), is extended to cover the general case of turbulence with a pseudo-vector-preferred direction, without assuming mirror-reflection invariance. Attention is focused on two-point-correlation functions, and it is shown that the form of the decomposition into proper and pseudo-tensor contributions is restricted by the homogeneity requirement. The somewhat unexpected result that the vector- and pseudo-vector-preferred-direction cases yield different results is presented: A pseudo-vector-preferred direction allows the correlation matrix one more functional degree of freedom than does the proper vector case. An explicit form of the two-point-correlation tensor in the presence of a uniform mean magnetic field is presented which may be appropriate for use in analysis of magnetic fluctuations in plasma containment devices or the interplanetary medium. A procedure for determining the magnetic helicity from experimental data is presented.

Matthaeus, W. H.↗
NASA NTRS1983

The Correlation of Structural, Chemical, and Electronic Properties of Small Metal Particles and Their Alloys

The low pressure interaction of CO with small Ru particles supported on ultrahigh vacuum (UHV) cleaved mica was studied using flash thermal desorption, Auger electron microscopy, transmission electron microscopy, and transmission electron diffraction. Average particle sizes for these experiments varied between 1.2 and 16 nm. A careful search for CO decomposition on the Ru particles revealed no evidence of dissociaiton over a temperature range and pressure range of 300 to 550 C and 10 to the minus 11th power to 10 to the minus 6th millibar, respectively. Cas and heat treatments caused significant morphological changes and dispersion in the Ru particles, which affected CO desorptiom These effects were dependent on the particle size.

Source record↗
DOE OSTI2026

Chemical bonding, phase stability and magnetic property in Sm 2 Fe 17 X 3 (X=H, C, N): A first-principles perspective

As a promising alternative to Nd–Fe–B magnets, the critical rare earth free Sm 2 Fe 17 X 3 (X = C, N) exhibits potential for high-performance magnets. However, their poor phase stability remains a major obstacle to developing bulk magnets. We investigated the phase stability and intrinsic magnetic properties of Sm 2 Fe 17 X 3 (X = H, C, N) using first-principles calculations and chemical bond analysis. The formation energies are negative, while the decomposition energies are −1.53, 0.348, and −0.74 eV per formula unit for X = H, C, and N, respectively, which is responsible for the weak thermal stability. Our chemical bond analysis reveals that the bonding asymmetry between Sm–X and Fe–X interactions creates local structural distortions and degrades the phase stability of Sm 2 Fe 17 X 3 . The project Crystal Orbital Hamilton Population (-pCOHP) analysis indicates that the Sm–X bonding remains positive up to the Fermi level, indicating stable bonding interactions. Here, in contrast, the Fe–X bonding becomes negative near the Fermi level, signifying anti-bonding contributions that reduce structural stability. Interstitial atoms X expand the lattice and enhance Fe magnetic moments, but Fe–X bonding suppresses neighboring Fe moments. Electron transfer from Sm to X modifies the valence state of Sm and the crystal field at the site, contributing to enhanced magnetocrystalline anisotropy in Sm 2 Fe 17 X 3 . Among the interstitial elements, carbon and nitrogen—with their larger atomic radius and higher electronegativity—induce greater lattice expansion and form stronger bonds with neighboring Sm and Fe atoms compared to hydrogen. Consequently, Sm 2 Fe 17 X 3 (X = C and N) exhibits better phase stability and significant improvement in magnetic properties.

Chemical bonding↗
DOE OSTI2025

Unconventional low temperature decomposition of a saturated hydrocarbon over atomically-dispersed titanium-aluminum-boron catalyst

Sonochemically-synthesized atomically-dispersed titanium-aluminum-boron nanopowder (TiAlB NP) exhibits a remarkable low-temperature catalytic activation of aliphatic C-H bonds at 750 K followed by C-C bond activation thus emerging as a potent low-cost alternative to expensive platinum group metals. Here, the model saturated hydrocarbon, exo-tetrahydrodicyclopentadiene (C10H16), undergoes catalytic decomposition on TiAlB NPs in a chemical microreactor to produce 1,3-cyclopentadiene (c-C5H6), cyclopentene (c-C5H8), and molecular hydrogen (H2) as detected in situ via isomer-selective, single-photon ionization time-of-flight mass spectrometry. Extensive electronic structure theory calculations on model clusters of the catalyst decode a unique synergy among the atomic constituents of the catalyst and chemical bonding in this stepwise, retro Diels Alder reaction: Ti, although insensitive to C-H activation in its metallic state, initiates the catalysis via chemisorption of the hydrocarbon, adjacent B centers readily abstract hydrogen atoms and store them during the catalytic cycle, while Al stabilizes the catalyst structure yet providing space for critical docking sites for the departing hydrocarbons.

Biswas, Souvick↗
NASA NTRS1987

Octree based automatic meshing from CSG models

Finite element meshes derived automatically from solid models through recursive spatial subdivision schemes (octrees) can be made to inherit the hierarchical structure and the spatial addressability intrinsic to the underlying grid. These two properties, together with the geometric regularity that can also be built into the mesh, make octree based meshes ideally suited for efficient analysis and self-adaptive remeshing and reanalysis. The element decomposition of the octal cells that intersect the boundary of the domain is emphasized. The problem, central to octree based meshing, is solved by combining template mapping and element extraction into a procedure that utilizes both constructive solid geometry and boundary respresentation techniques. Boundary cells that are not intersected by the edge of the domain boundary are easily mapped to predefined element topology. Cells containing edges (and vertices) are first transformed into a planar polyhedron and then triangulated via element extractors. The modeling environments required for the derivation of planar polyhedra and for element extraction are analyzed.

Perucchio, Renato↗
NASA NTRS1987

Geometrical and topological issues in octree based automatic meshing

Finite element meshes derived automatically from solid models through recursive spatial subdivision schemes (octrees) can be made to inherit the hierarchical structure and the spatial addressability intrinsic to the underlying grid. These two properties, together with the geometric regularity that can also be built into the mesh, make octree based meshes ideally suited for efficient analysis and self-adaptive remeshing and reanalysis. The element decomposition of the octal cells that intersect the boundary of the domain is discussed. The problem, central to octree based meshing, is solved by combining template mapping and element extraction into a procedure that utilizes both constructive solid geometry and boundary representation techniques. Boundary cells that are not intersected by the edge of the domain boundary are easily mapped to predefined element topology. Cells containing edges (and vertices) are first transformed into a planar polyhedron and then triangulated via element extractor. The modeling environments required for the derivation of planar polyhedra and for element extraction are analyzed.

Saxena, Mukul↗