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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 505 records · Page 28

The deep structure of lunar basins - Implications for basin formation and modification

Models for the crustal structure in the vicinity of nine impact basins, from an inversion of gravity and topographic data from the lunar nearside are presented. The models display a low-density nonmare crustal layer and a mare basalt layer, both of variable thicknesses. Assuming that topography in mare areas is isostatically compensated before the emplacement of mare basalts and that compensation of mare basalt units may be neglected, a decomposition of the gravity anomaly into contributions from Moho relief and mare fill is permitted. Minimum values for mare basalt thicknesses are obtained but because mare basalts and mantle material are similar in density, the thicknesses of the nonmare crust are estimated. An important constraint is the crustal thickness inferred from the Apollo 12 and 14 landing sites from seismic observations. The crustal thickness model indicates that the crust is thinner beneath each of the major nearside basins than in surrounding areas. New bounds on the volume of material ejected from each basin are derived. The geological implications of structural differences among basins for the processes of basin formation and modification are evaluated as functions of time on the moon.

Bratt, S. R.↗

Molecular structures of residual solvent in polyacrylonitrile based electrolytes: Implications for conductivity and stability

Lithium-ion batteries increasingly play significant roles in modern technologies; however, increased energy density also raises concerns about electrolyte safety. Traditional electrolytes that use volatile organic solvents face risks of thermal runaways and fires from electrode shorting. In response, polymer-based solid electrolytes have been developed for replacement. Polyacrylonitrile (PAN) is a promising fire-resistant component for electrolyte fabrication, but its limited solubility necessitates using low-volatility solvents, which are notoriously difficult to remove in subsequent drying processes. Here, we use femtosecond two-dimensional infrared spectroscopy to provide an in-depth understanding of how residual solvent from processing affects the molecular structures and dynamics within a polymer electrolyte. To this end, linear and nonlinear infrared spectroscopies are employed to interrogate the molecular interactions in PAN-based electrolytes containing various contents of N,N-dimethylformamide (DMF). We show that the amount of DMF within the PAN electrolyte affects the Li+ structure. Further, the coordination can proceed through the carbonyl group and/or the amide nitrogen to form antiparallel structures with the nitrile groups of PAN through dipole–dipole interactions. The free motion of DMF is drastically inhibited upon interaction with Li+ and PAN, which decreases the ionic conductivity and potentially affects the stability (resistance toward removal and chemical decomposition). These findings have implications for the design and processing of solid polymer electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A CFD study of complex missile and store configurations in relative motion

An investigation was conducted from May 16, 1990 to August 31, 1994 on the development of computational fluid dynamics (CFD) methodologies for complex missiles and the store separation problem. These flowfields involved multiple-component configurations, where at least one of the objects was engaged in relative motion. The two most important issues that had to be addressed were: (1) the unsteadiness of the flowfields (time-accurate and efficient CFD algorithms for the unsteady equations), and (2) the generation of grid systems which would permit multiple and moving bodies in the computational domain (dynamic domain decomposition). The study produced two competing and promising methodologies, and their proof-of-concept cases, which have been reported in the open literature: (1) Unsteady solutions on dynamic, overlapped grids, which may also be perceived as moving, locally-structured grids, and (2) Unsteady solutions on dynamic, unstructured grids.

Baysal, Oktay↗

Carbon Structure Hazard Control

Carbon composite structures are widely used in virtually all advanced technology industries for a multitude of applications. The high strength-to-weight ratio and resistance to aggressive service environments make them highly desirable. Automotive, aerospace, and petroleum industries extensively use, and will continue to use, this enabling technology. As a result of this broad range of use, field and test personnel are increasingly exposed to hazards associated with these structures. No single published document exists to address the hazards and make recommendations for the hazard controls required for the different exposure possibilities from damaged structures including airborne fibers, fly, and dust. The potential for personnel exposure varies depending on the application or manipulation of the structure. The effect of exposure to carbon hazards is not limited to personnel, protection of electronics and mechanical equipment must be considered as well. The various exposure opportunities defined in this document include pre-manufacturing fly and dust, the cured structure, manufacturing/machining, post-event cleanup, and post-event test and/or evaluation. Hazard control is defined as it is applicable or applied for the specific exposure opportunity. The carbon exposure hazard includes fly, dust, fiber (cured/uncured), and matrix vapor/thermal decomposition products. By using the recommendations in this document, a high level of confidence can be assured for the protection of personnel and equipment.

Yoder, Tommy↗

Preparation and Characterization of YBa 2 Cu 4 O 8 Superconductor

Solid-state reaction of appropriate amounts of Y 2 O 3 , BaCOs, and CuO for 2 h at 800°C in flowing oxygen with a total pressure of 2.7 x 10 2 Pa (2 mm Hg), followed by cooling and annealing at 750°C for 10 h in oxygen at ambient pressure, has produced orthorhombic YBa 2 Cu 4 O 8 (124) as the main phase with YBa 2 Cu 3 O x (123) as an impurity phase. After the as-calcined powder was annealed in oxygen at 800°C for 24 h under ambient pressure, the phase purity improved considerably. Calcined 124 powder was pressed into pellets and rapidly annealed at temperatures from 870°C to 935°C. At these temperatures, the 124 decomposed into 123. The superconducting transition temperature, T c , of the annealed samples depended upon the annealing temperature and atmosphere. The decomposed samples have been characterized by low field RF SQUID magnetometer and high resolution transmission electron microscopy.

36 MATERIALS SCIENCE↗

A component decomposition model for evaluating atmospheric effects in remote sensing

A radiance value of a target pixel recorded by a remote sensor can be decomposed into three components: (1) attenuated target signature, (2) pure atmospheric radiation, and (3) the contribution made by the ground through the atmospheric scattering process. Given the meteorological and optical parameters of a layer-structured atmosphere, its transmittance and radiance distribution can be accurately calculated with a plane-parallel radiative transfer model. For a uniform surface, the ground contribution can be obtained by comparing radiances for an atmosphere over a black but nonemitting surface and the same atmosphere with an underlying ground of given albedo or temperature. For an inhomogeneous surface, the first two components remain the same as long as the surface is a plane. The third may be estimated using the locally averaged top-of-atmosphere radiance. An atmospheric point spread function is calculated by a Monte Carlo approach and is used for retrieving the ground signature through a deconvolution procedure.

Li, S.↗

Elastic continua in high frequency excitation field

The response of elastic continua to high-frequency excitations is decomposed in two parts: 'slow' motion which practically remains unchanged during a vanishingly small period of time, and 'fast' motions whose mean value during this period is negligible but whose energy contribution is essential. After such a decomposition the 'slow' and 'fast' motions become non-linearly coupled by the corresponding governing equations. This coupling leads to an additional 'effective' potential energy which changes the 'mean' stiffness characteristics. The results can be used for dynamical stiffening of flexible structural elements, for a temporary increase of their stiffness in the course of occasional loads to prevent buckling or wrinkling.

Zak, M.↗

Constraint elimination in dynamical systems

Large space structures (LSSs) and other dynamical systems of current interest are often extremely complex assemblies of rigid and flexible bodies subjected to kinematical constraints. A formulation is presented for the governing equations of constrained multibody systems via the application of singular value decomposition (SVD). The resulting equations of motion are shown to be of minimum dimension.

Singh, R. P.↗

A New Method for Nonlinear and Nonstationary Time Series Analysis and Its Application to the Earthquake and Building Response Records

A new method for analyzing nonlinear and nonstationary data has been developed. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum, Example of application of this method to earthquake and building response will be given. The results indicate those low frequency components, totally missed by the Fourier analysis, are clearly identified by the new method. Comparisons with Wavelet and window Fourier analysis show the new method offers much better temporal and frequency resolutions.

Huang, Norden E.↗

Applications of the Hilbert-Huang Transform

A new method, the Hilbert-Huang Transform, has been developed for analyzing nonlinear and nonstationary data. The key part of the method is the Empirical Mode Decomposition with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An M is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies'as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. With this technique we can examine the detailed dynamics characteristics of a nonlinear system through the instantaneous frequency rather than harmonics. Thus it constitutes a new view of the nonlinear dynamics. Examples of classic nonlinear equations and other nonlinear and nonstationary data sets will be used as examples to illustrate the advantage of the application of this new data analysis method.

Huang, Norden E.↗

A New Method for Nonlinear and Nonstationary Time Series Analysis: The Empirical Mode Decomposition Method

A new method for analyzing nonlinear and nonstationary data has been developed. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. Classical nonlinear system models are used to illustrate the roles played by the nonlinear and nonstationary effects in the energy-frequency-time distribution.

Huang, Norden E.↗

Applications of Hilbert Spectral Analysis for Speech and Sound Signals

A new method for analyzing nonlinear and nonstationary data has been developed, and the natural applications are to speech and sound signals. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time, which give sharp identifications of imbedded structures. This method invention can be used to process all acoustic signals. Specifically, it can process the speech signals for Speech synthesis, Speaker identification and verification, Speech recognition, and Sound signal enhancement and filtering. Additionally, as the acoustical signals from machinery are essentially the way the machines are talking to us. Therefore, the acoustical signals, from the machines, either from sound through air or vibration on the machines, can tell us the operating conditions of the machines. Thus, we can use the acoustic signal to diagnosis the problems of machines.

Huang, Norden E.↗

Fused filament fabrication of thermoplastic polyurethane composites with microencapsulated phase-change material

Here, the present study examines the thermal energy storage (TES) effectiveness and printability of microencapsulated phase-change material (MEPCM) combined with thermoplastic polyurethane (TPU) for fused filament fabrication (FFF). Two formulations were assessed: 24D MEPCM, which changes phase at 24 ° C, compounded with TPU pellets and 43D MEPCM, which changes phase at 43 ° C, integrated with TPU powder. These combinations are designed to evaluate the effectiveness of the form of the TPU (pellets versus powder) in the FFF process. The investigation includes a comprehensive analysis of thermal characteristics, encompassing phase-change temperature, latent heat of fusion, thermal conductivity, and thermal decomposition, which are assessed through differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). Additionally, mechanical properties, including stress-strain behavior, are examined to evaluate material suitability for TES applications, while microstructural visualization is used to provide deeper insights into material performance, structural integrity, and the quality of printed components. The 24D MEPCM and TPU pellets formulation experienced a significant loss of approximately 39.6% of PCM during filament extrusion and printing, resulting in a reduced effective latent heat. Therefore, further characterization of the pellet formulation was discontinued due to excessive leakage. In contrast, the 43D MEPCM and TPU powder formulation demonstrated minimal PCM loss, with the 60 wt.% composition achieving an effective latent heat of 132 J/g. This value represents the highest effective latent heat currently documented in the literature for PCM-polymer-composite materials produced using an FFF-based additive manufacturing process.

25 ENERGY STORAGE↗

Goated: goal-oriented tensor decompositions in python

SAND2026-20464O Goated performs goal-oriented tensor decompositions in Python, enabling efficient compression of multi-dimensional simulation data. It extends common tensor decomposition methods by incorporating domain-specific knowledge, such as conservation laws in physics, through a penalty term in the optimization process. This approach improves data compression and modeling accuracy across various applications, including physics simulations, by using specialized algorithms and structure-aware subroutines to accelerate solver performance. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗

Closed-form solutions of performability

Methods which yield closed form performability solutions for continuous valued variables are developed. The models are similar to those employed in performance modeling (i.e., Markovian queueing models) but are extended so as to account for variations in structure due to faults. In particular, the modeling of a degradable buffer/multiprocessor system is considered whose performance Y is the (normalized) average throughput rate realized during a bounded interval of time. To avoid known difficulties associated with exact transient solutions, an approximate decomposition of the model is employed permitting certain submodels to be solved in equilibrium. These solutions are then incorporated in a model with fewer transient states and by solving the latter, a closed form solution of the system's performability is obtained. In conclusion, some applications of this solution are discussed and illustrated, including an example of design optimization.

Meyer, J. F.↗

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.↗

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.↗

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.↗