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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Minimum-mass design of filamentary composite panels under combined loads: Design procedure based on simplified buckling equations

An analytical procedure is presented for designing hat stiffened and corrugated panels made of composite material and subjected to longitudinal (in the direction of the stiffeners) compression and shear loadings. The procedure is based on nonlinear mathematical programming techniques and a simplified set of buckling equations. Design requirements considered are buckling, strength, and extensional and shear stiffness. The effects of specified thickness, variation of cross-section dimensions, stiffness requirements, local buckling boundary conditions, and the effect of combined compression and shear loadings are shown.

Stroud, W. J.↗
NASA NTRS1992

Multi-layer holographic bifurcative neural network system for real-time adaptive EOS data analysis

Optical data processing techniques have the inherent advantage of high data throughout, low weight and low power requirements. These features are particularly desirable for onboard spacecraft in-situ real-time data analysis and data compression applications. The proposed multi-layer optical holographic neural net pattern recognition technique will utilize the nonlinear photorefractive devices for real-time adaptive learning to classify input data content and recognize unexpected features. Information can be stored either in analog or digital form in a nonlinear photorefractive device. The recording can be accomplished in time scales ranging from milliseconds to microseconds. When a system consisting of these devices is organized in a multi-layer structure, a feed forward neural net with bifurcating data classification capability is formed. The interdisciplinary research will involve the collaboration with top digital computer architecture experts at the University of Southern California.

Liu, Hua-Kuang↗
NASA NTRS1993

Multi-layer holographic bifurcative neural network system for real-time adaptive EOS data analysis

Optical data processing techniques have the inherent advantage of high data throughout, low weight and low power requirements. These features are particularly desirable for onboard spacecraft in-situ real-time data analysis and data compression applications. the proposed multi-layer optical holographic neural net pattern recognition technique will utilize the nonlinear photorefractive devices for real-time adaptive learning to classify input data content and recognize unexpected features. Information can be stored either in analog or digital form in a nonlinear photofractive device. The recording can be accomplished in time scales ranging from milliseconds to microseconds. When a system consisting of these devices is organized in a multi-layer structure, a feedforward neural net with bifurcating data classification capability is formed. The interdisciplinary research will involve the collaboration with top digital computer architecture experts at the University of Southern California.

Liu, Hua-Kuang↗
NASA NTRS1990

Design of QMF (Quadrature Mirror Filter) in spatial domain and edge encoding

Simoncelli and Adelson have extended the one dimensional Quadrature Mirror Filter (QMF) to two dimensions with hexagon symmetry and three dimensional spatio-temporal extensions with rhombic-duodecahedray symmetry. Jain and Crochiere presented an excellent QMF design technique in the time domain. It is proposed to extend the design of a two dimensional QMF over a rectangular lattice in the spatial domain based primarily on the extension of the idea of Jain and Crochiere. In addition, the design will investigate the use of two dimensional Z-transformations. Since this proposed QMF is intended for the applications in image processing, all the important and interesting engineering issues will be addressed throughout the development phase. The design of a two dimensional QMF is discussed. The motivation is to achieve an extremely high data compression ratio. It is entirely possible to achieve dramatic results when pattern recognition techniques are employed. The final goal is the demonstration of extremely high data compression ratios using NASA pictures.

Wang, Paul P.↗
NASA NTRS1987

Spectral feature design for data compression in high dimensional multispectral data

Data transmission loads of high dimensional remote sensor systems can be greatly reduced by applying generalized Karhunen-Loeve transform as a feature design technique. Two spectral feature design approaches based upon the generalized K-L transform are developed to compress information effectively. Six sets of field data from Kansas and North Dakota on three different dates each are used to test the methods. Spatially, temporally and spatially/temporally combined data sets are formed in this paper to test the robustness property of the schemes. The probability of correct classification using Landsat MSS, Thematic Mapper bands and the proposed bands are found and compared. The comparison shows that the results are improved by the proposed methods, and they appear to be satisfactorily robust. The overall data compression ratio in this paper is about 100/16, i.e., about 6 to 1 with no loss in classification accuracy.

Chen, C.-C. Thomas↗
NASA NTRS1999

Exploratory Investigation into the Durability of Beneficial Cold Worked Fastener Hole in Aluminum

Cold working fastener holes in aluminum alloys is a widely used technique in the aerospace industry for improving the fatigue performance of structures. A compressive tangential stress introduced in the material during the cold working of the hole reduces the natural tendency of the material to crack at the holes under cyclic tensile loading. It is a lucrative technique for the aerospace industry in that it provides an increase in performance without any weight cost.

Johnson, W. S.↗
NASA NTRS1989

Context dependent prediction and category encoding for DPCM image compression

Efficient compression of image data requires the understanding of the noise characteristics of sensors as well as the redundancy expected in imagery. Herein, the techniques of Differential Pulse Code Modulation (DPCM) are reviewed and modified for information-preserving data compression. The modifications include: mapping from intensity to an equal variance space; context dependent one and two dimensional predictors; rationale for nonlinear DPCM encoding based upon an image quality model; context dependent variable length encoding of 2x2 data blocks; and feedback control for constant output rate systems. Examples are presented at compression rates between 1.3 and 2.8 bits per pixel. The need for larger block sizes, 2D context dependent predictors, and the hope for sub-bits-per-pixel compression which maintains spacial resolution (information preserving) are discussed.

Beaudet, Paul R.↗
DOE OSTI2022

An Algorithmic and Software Pipeline for Very Large Scale Scientific Data Compression with Error Guarantees

Efficient data compression is becoming increasingly critical for storing scientific data because many scientific applications produce vast amounts of data. This paper presents an end-to-end algorithmic and software pipeline for data compression that guarantees both error bounds on primary data (PD) and derived data, known as Quantities of Interest (QoI).We demonstrate the effectiveness of the pipeline by compressing fusion data generated by a large-scale fusion code, XGC, which produces tens of petabytes of data in a single day. We demonstrate that the compression is conducted by setting aside computational resources known as staging nodes, and does not impact the simulation performance. For efficient parallel I/O, the pipeline uses ADIOS2, which many codes such as XGC already use for their parallel I/O. We show that our approach can compress the data by two orders of magnitude while guaranteeing high accuracy on both the PD and the QoIs. Further, the amount of resources required by compression is a few percent of the resources required by simulation while ensuring that the compression time for each stage is less than the corresponding simulation time.This pipeline consists of three main steps. The first step decomposes the data using domain decomposition into small subdomains. Each subdomain is then compressed independently to achieve a high level of parallelism. The second step uses existing techniques that guarantee error bounds on the primary data for each subdomain. The third step uses a post-processing optimization technique based on Lagrange multipliers to reduce the QoI errors for data corresponding to each subdomain. The Lagrange multipliers generated can be further quantized or truncated to increase the compression level. All of the above characteristics of our approach make it highly practical to apply on-the-fly compression while guaranteeing errors on QoIs that are critical to the scientists.

Banerjee, Tania↗
DOE OSTI2023

Measurement of femtosecond dynamics of ultrafast electron beams through terahertz compression and time-stamping

Visualizing ultrafast dynamics at the atomic scale requires time-resolved characterization with femtosecond temporal resolution. For fully relativistic electron bunch probes, existing techniques for single-shot ultrafast electron diffraction (UED) are limited by the achievable electron probe bunch length, charge, and timing jitter. We present the first experimental demonstration of dual-fed THz-driven compression and time-stamping that enables electron probes with improved temporal resolution. This technique utilizes two counter-propagating quasi-single-cycle THz pulses generated from two OH-1 organic crystals coupled into an optimized THz compressor structure. We demonstrate electron bunch compression and time-of-arrival jitter suppression by a factor of 3 paving the way toward unique opportunities for UED time-resolved measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Characterization of anisotropic mechanical properties of polymer composites from a hybrid additive manufacturing-compression molding process using x-ray computer tomography

In this study, anisotropic stiffness tensors were reconstructed based on fiber orientation distributions obtained from X-ray computer tomography (xCT). A preform was manufactured via a big area additive manufacturing (BAAM) system with carbon fiber (CF) filled acrylonitrile butadiene styrene (ABS). The tailored preform from additive manufacturing (AM) was used in the compression molding (CM) process to produce a low-void high-performance thermoplastic composite panel. An xCT technique was employed to detect the fiber orientations in CF/ABS composites manufactured via three different methods: AM from BAAM, extrusion compression molding (ECM), and AM-CM. The anisotropic stiffness tensor was obtained from the composite panel manufactured via the three manufacturing methods (AM, ECM, and AMCM). A micromechanics theory was used to obtain the orthotropic stiffness tensors of the composite panels and compared with the experimental values. The predicted stiffness tensors of AM and AM-CM composite panels were used to study the deformation characteristics of a steering wheel during airbag deployment by performing finite element analysis (FEA). The approach developed in this study can be utilized for evaluating high-performance composites.

Pokkalla, Deepak↗
NASA NTRS2001

Solar-Powered Refrigeration System

A solar powered vapor compression refrigeration system is made practicable with thermal storage and novel control techniques. In one embodiment, the refrigeration system includes a photovoltaic panel, a variable speed compressor, an insulated enclosure. and a thermal reservoir. The photovoltaic (PV) panel converts sunlight into DC (direct current) electrical power. The DC electrical power drives a compressor that circulates refrigerant through a vapor compression refrigeration loop to extract heat from the insulated enclosure. The thermal reservoir is situated inside the insulated enclosure and includes a phase change material. As heat is extracted from the insulated enclosure, the phase change material is frozen, and thereafter is able to act as a heat sink to maintain the temperature of the insulated enclosure in the absence of sunlight. The conversion of solar power into stored thermal energy is optimized by a compressor control method that effectively maximizes the compressor's usage of available energy. A capacitor is provided to smooth the power voltage and to provide additional current during compressor start-up. A controller monitors the rate of change of the smoothed power voltage to determine if the compressor is operating below or above the available power maximum, and adjusts the compressor speed accordingly. In this manner, the compressor operation is adjusted to convert substantially all available solar power into stored thermal energy.

Ewert, Michael K.↗
NASA NTRS2002

Solar Powered Refrigeration System

A solar powered vapor compression refrigeration system is made practicable with thermal storage and novel control techniques. In one embodiment, the refrigeration system includes a photovoltaic panel, a variable speed compressor, an insulated enclosure, and a thermal reservoir. The photovoltaic (PV) panel converts sunlight into DC (direct current) electrical power. The DC electrical power drives a compressor that circulates refrigerant through a vapor compression refrigeration loop to extract heat from the insulated enclosure. The thermal reservoir is situated inside the insulated enclosure and includes a phase change material. As heat is extracted from the insulated enclosure, the phase change material is frozen, and thereafter is able to act as a heat sink to maintain the temperature of the insulated enclosure in the absence of sunlight. The conversion of solar power into stored thermal energy is optimized by a compressor control method that effectively maximizes the compressor's usage of available energy. A capacitor is provided to smooth the power voltage and to provide additional current during compressor start-up. A controller monitors the rate of change of the smoothed power voltage to determine if the compressor is operating below or above the available power maximum, and adjusts the compressor speed accordingly. In this manner, the compressor operation is adjusted to convert substantially all available solar power into stored thermal energy.

Michael K Ewert↗
NASA NTRS2002

Solar-Powered Refrigeration System

A solar powered vapor compression refrigeration system is made practicable with thermal storage and novel control techniques. In one embodiment, the refrigeration system includes a photovoltaic panel, a variable speed compressor, an insulated enclosure, and a thermal reservoir. The photovoltaic (PV) panel converts sunlight into DC (direct current) electrical power. The DC electrical power drives a compressor that circulates refrigerant through a vapor compression refrigeration loop to extract heat from the insulated enclosure. The thermal reservoir is situated inside the insulated enclosure and includes a phase change material. As heat is extracted from the insulated enclosure, the phase change material is frozen, and thereafter is able to act as a heat sink to maintain the temperature of the insulated enclosure in the absence of sunlight. The conversion of solar power into stored thermal energy is optimized by a compressor control method that effectively maximizes the compressor's usage of available energy. A capacitor is provided to smooth the power voltage and to provide additional current during compressor start-up. A controller monitors the rate of change of the smoothed power voltage to determine if the compressor is operating below or above the available power maximum, and adjusts the compressor speed accordingly. In this manner, the compressor operation is adjusted to convert substantially all available solar power into stored thermal energy.

Michael K Ewert↗
NASA NTRS1985

High-speed compressible flow and other advection-dominated problems of fluid dynamics

Finite element methods are described for modeling high speed compressible flows with strong advection, problems important to aerodynamics. The situations are characterized by high pressure and temperature gradients, transients and the appearance of discontinuities, factors which require mesh refinement during computations. Techniques are developed for temporal and spatial discretization of a model problem. Several observations are made regarding the explicit and implicit features of the calculations, the use of the Lax-Wendroff scheme to produce a mass-matrix for obtaining accurate results for transients, methods of performing stability analyses, and simplification techniques. Examples are provided of solving the nonlinear shallow-water equations and describing compressible flows, particularly transonic flows. Domain splitting is defined for improving the calculations at each time step and in different parts of the flow regime while simultaneously advancing the calculations towards a solution.

Zienkiewicz, O. C.↗
DOE OSTI2025

Homomorphic data compression for real time photon correlation analysis

The construction of highly coherent X-ray sources, combined with next-generation detectors that are larger and faster, has enabled new research opportunities across the scientific landscape. Among the techniques that benefit most from these advancements is X-ray photon correlation spectroscopy (XPCS), where faster acquisition unlocks the ability to study faster dynamics within samples. However, faster acquisition on larger detectors also introduces unprecedented challenges for online data processing and offline data storage. Such challenges are particularly prominent for XPCS, where real time analyses require simultaneous calculation of all the previously acquired data in the time series. We present a homomorphic compression scheme to effectively reduce the computational time and memory space required for XPCS analysis. Leveraging similarities in the mathematical expression between a matrix-based compression algorithm and the correlation calculation, our approach allows direct operation on the compressed data without their decompression. The offline compression scheme extends storage capacity by a factor of 40 while preserving key features in the lossy compressed data. Meanwhile, the online compression scheme reduces the computational time to below 1 ms, enabling real time calculation of the correlation functions at kHz framerate. Our demonstration of a homomorphic compression of scientific data provides an effective solution to the big data challenge at coherent light sources. Beyond the example shown in this work, the framework can be extended to facilitate real-time operations directly on a compressed data stream for other techniques.

36 MATERIALS SCIENCE↗
NASA NTRS1975

Solution of the three-dimensional compressible, laminar, and turbulent boundary-layer equations with comparisons to experimental data

A technique for solving three-dimensional boundary-layer flows is presented. The governing equations are transformed to obtain a nondimensional form and a similarity-type transform is defined for the normal coordinate and velocity. The resulting equation is solved in an iterative mode using a finite difference technique suggested by Dwyer (1968). A simple mean field turbulence model is discussed and numerical data obtained in a test case are compared with experimental data.-

Harris, J. E.↗
NASA NTRS1986

Compression-Failure Mechanisms in Composite Laminates

Failure mechanisms observed using transparent fiberglass/epoxy birefringent materials. Technique based on use of transparent fiberglass/epoxy birefringent material. Transparency allows visual observation of location of initial laminate failure and of subsequent failure propagation; birefringence allows laminate stress distribution to be observed during test and also after test if permanent residual stresses occur. Nondestructive technique developed to observe failure as it develops and as propagates within laminate.

Shuart, M. J.↗
NASA NTRS1989

Zonal multigrid solution of compressible flow problems on unstructured and adaptive meshes

The simultaneous use of adaptive meshing techniques with a multigrid strategy for solving the 2-D Euler equations in the context of unstructured meshes is studied. To obtain optimal efficiency, methods capable of computing locally improved solutions without recourse to global recalculations are pursued. A method for locally refining an existing unstructured mesh, without regenerating a new global mesh is employed, and the domain is automatically partitioned into refined and unrefined regions. Two multigrid strategies are developed. In the first, time-stepping is performed on a global fine mesh covering the entire domain, and convergence acceleration is achieved through the use of zonal coarse grid accelerator meshes, which lie under the adaptively refined regions of the global fine mesh. Both schemes are shown to produce similar convergence rates to each other, and also with respect to a previously developed global multigrid algorithm, which performs time-stepping throughout the entire domain, on each mesh level. However, the present schemes exhibit higher computational efficiency due to the smaller number of operations on each level.

Mavriplis, Dimitri J.↗