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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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We present a novel data compression technique, called recursive interleaved entropy coding, that is based on recursive interleaving of variable-to-variable length binary source codes.
An adaptive algorithm for intraframe compression of NTSC composite color video signal is described. With an average of 80 percent compression (1.6 bits/pixel) and a bit error rate of 0.0001, excellent broadcast quality pictures were obtained. This is confirmed by a subjective evaluation of processed pictures by five viewers. The algorithm and the results of the subjective evaluation are given in this paper.
The feasibility of simulating propulsion-induced aerodynamic effects on scaled aircraft models in wind tunnels employing Magnetic Suspension and Balance Systems. The investigation concerned itself with techniques of generating exhaust jets of appropriate characteristics. The objectives were to: (1) define thrust and mass flow requirements of jets; (2) evaluate techniques for generating propulsive gas within volume limitations imposed by magnetically-suspended models; (3) conduct simple diagnostic experiments for techniques involving new concepts; and (4) recommend experiments for demonstration of propulsion simulation techniques. Various techniques of generating exhaust jets of appropriate characteristics were evaluated on scaled aircraft models in wind tunnels with MSBS. Four concepts of remotely-operated propulsion simulators were examined. Three conceptual designs involving innovative adaptation of convenient technologies (compressed gas cylinders, liquid, and solid propellants) were developed. The fourth innovative concept, namely, the laser-assisted thruster, which can potentially simulate both inlet and exhaust flows, was found to require very high power levels for small thrust levels.
This viewgraph presentation discusses turbulence modeling requirements, development philosophy, and approach; two major areas of concentration (high speed and low speed turbulence modeling); high speed turbulence modeling; compressibility effects; turbulence models adapted to USA code; M = 9.2 flat plate flow; Mach 7.05 flow over axisymmetric flare; Mach 8.6 flow over cold wall edge; low speed turbulence modeling; turbulence models being assessed; turbulence model deck structure and integration with Navier-Stokes solver; nonlinear algebraic-stress model; rotation modified k-epsilon model; and Reynolds stress model.
Matrix methods for solving integral equations via direct solve LU factorization are presently limited to weeks to months of very expensive supercomputer time for problems sizes of several hundred thousand unknowns. This report presents matrix LU factor solutions for electromagnetic scattering problems for problem sizes to one million unknowns with thousands of right hand sides that run in mere days on PC level hardware. This EM solution is accomplished by utilizing the numerical low rank nature of spatially blocked unknowns using the Adaptive Cross Approximation for compressing the rank deficient blocks of the system Z matrix, the L and U factors, the right hand side forcing function and the final current solution. This compressed matrix solution is applied to a frequency domain EM solution of Maxwell's equations using standard Method of Moments approach. Compressed matrix storage and operations count leads to orders of magnitude reduction in memory and run time.
A method for real-time detection of dust devils at a given location is based on identifying the abrupt, temporary decreases in atmospheric pressure that are characteristic of dust devils as they travel through that location. The method was conceived for use in a study of dust devils on the Martian surface, where bandwidth limitations encourage the transmission of only those blocks of data that are most likely to contain information about features of interest, such as dust devils. The method, which is a form of intelligent data compression, could readily be adapted to use for the same purpose in scientific investigation of dust devils on Earth. In this method, the readings of an atmospheric- pressure sensor are repeatedly digitized, recorded, and processed by an algorithm that looks for extreme deviations from a continually updated model of the current pressure environment. The question in formulating the algorithm is how to model current normal observations and what minimum magnitude deviation can be considered sufficiently anomalous as to indicate the presence of a dust devil. There is no single, simple answer to this question: any answer necessarily entails a compromise between false detections and misses. For the original Mars application, the answer was sought through analysis of sliding time windows of digitized pressure readings. Windows of 5-, 10-, and 15-minute durations were considered. The windows were advanced in increments of 30 seconds. Increments of other sizes can also be used, but computational cost increases as the increment decreases and analysis is performed more frequently. Pressure models were defined using a polynomial fit to the data within the windows. For example, the figure depicts pressure readings from a 10-minute window wherein the model was defined by a third-degree polynomial fit to the readings and dust devils were identified as negative deviations larger than both 3 standard deviations (from the mean) and 0.05 mbar in magnitude. An algorithm embodying the detection scheme of this example was found to yield a miss rate of just 8 percent and a false-detection rate of 57 percent when evaluated on historical pressure-sensor data collected by the Mars Pathfinder lander. Since dust devils occur infrequently over the course of a mission, prioritizing observations that contain successful detections could greatly conserve bandwidth allocated to a given mission. This technique can be used on future Mars landers and rovers, such as Mars Phoenix and the Mars Science Laboratory.
Recently, a metric-based mesh adaptation capability has been developed for the advanced compressible flow solver US3D. Metric-based mesh adaptation is a solution informed mesh adaptation strategy that typically improves the resolution of the mesh along anisotropic flow features, like strong shock waves or shear layers. An anisotropic error indicator is reconstructed based on a provided Computational Fluid Dynamics (CFD) solution which prescribes the locally desired element size and orientation. The benefits of this mesh adaptation strategy is twofold: first, it simplifies the manual meshing labor that typically needs to be carried out by the CFD engineer because the mesh adaptation is informed by the provided solution. Second, the computational cost is kept to a minimum while improving the resolution of the simulation. The aim here is to demonstrate how anisotropic mesh adaptation can be employed to improve the predictions of surface pressure for atmospheric entry vehicles. In this work, we compare CFD simulations that use this newly developed anisotropic mesh adaptation capability for US3D with pressure data that was collected by Mars Entry, Descent, and Landing Instrumentation 2 (MEDLI2) during the atmospheric entry phase of Mars2020.
A metric-based mesh adaptation capability has been developed for the advanced compressible flow solver US3D. Metric-based mesh adaptation is a solution informed mesh adaptation strategy that improves the resolution of the mesh along anisotropic flow features, like strong shock waves or shear layers. An anisotropic error indicator is reconstructed based on a provided Computational Fluid Dynamics (CFD) solution which prescribes the locally desired element size and orientation. The benefits of this mesh adaptation strategy is twofold: first, it simplifies the manual meshing labor that typically needs to be carried out by the CFD engineer because the mesh adaptation is informed by the provided solution. Second, the computational cost is kept to a minimum while improving the resolution of the simulation. The aim here is to demonstrate how anisotropic mesh adaptation can be employed to improve the predictions of surface pressure for atmospheric entry vehicles. In this work, we compare CFD simulations that use this newly developed anisotropic mesh adaptation capability for US3D with pressure data that was collected by Mars Entry, Descent, and Landing Instrumentation (MEDLI2) suite.
The Science Data Management and Science Payload Operations subpanel reports from the NASA Conference on Scientific Data Compression (Snowbird, Utah in 1988) indicate the need for both lossless and lossy image data compression systems. The ranges developed by the subpanel suggest ratios of 2:1 to 4:1 for lossless coding and 2:1 to 6:1 for lossy predictive coding. For the NASA Freedom Science Video Processing Facility it would be highly desirable to implement one baseline compression system which would meet both of these criteria. Presented here is such a system, utilizing an LZW hybrid coding scheme which is adaptable to either type of compression. Simulation results are presented with the hybrid LZW algorithm operating in each of its modes.
The feasibility of reducing data volume and data rate is evaluated for the Earth Observing System (EOS) Synthetic Aperture Radar (SAR). All elements of data stream from the sensor downlink data stream to electronic delivery of browse data products are explored. The factors influencing design of a data compression system are analyzed, including the signal data characteristics, the image quality requirements, and the throughput requirements. The conclusion is that little or no reduction can be achieved in the raw signal data using traditional data compression techniques (e.g., vector quantization, adaptive discrete cosine transform) due to the induced phase errors in the output image. However, after image formation, a number of techniques are effective for data compression.
Efficient on-board lossless hyperspectral data compression reduces data volume in order to meet NASA and DoD limited downlink capabilities. The technique also improves signature extraction, object recognition and feature classification capabilities by providing exact reconstructed data on constrained downlink resources. At JPL a novel, adaptive and predictive technique for lossless compression of hyperspectral data was recently developed. This technique uses an adaptive filtering method and achieves a combination of low complexity and compression effectiveness that far exceeds state-of-the-art techniques currently in use. The JPL-developed 'Fast Lossless' algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. It is of low computational complexity and thus well-suited for implementation in hardware.
This paper presents an adaptive algorithm for motion compensated color image coding. The algorithm can be used for video teleconferencing or broadcast signals. Activity segmentation is used to reduce the bit rate and a variable stage search is conducted to save computations. The adaptive algorithm is compared with the nonadaptive algorithm and it is shown that with approximately 60 percent savings in computing the motion vector and 33 percent additional compression, the performance of the adaptive algorithm is similar to the nonadaptive algorithm. The adaptive algorithm results also show improvement of up to 1 bit/pel over interframe DPCM coding with nonuniform quantization. The test pictures used for this study were recorded directly from broadcast video in color.
Accurate capturing of discontinuities within compressible flow computations is achieved by coupling a suitable solver with an automatic adaptive mesh algorithm for unstructured triangular meshes. The mesh adaptation procedures developed rely on non-hierarchical dynamical local refinement/derefinement techniques, which hence enable structural optimization as well as geometrical optimization. The methods described are applied for a number of the ICASE test cases are particularly interesting for unsteady flow simulations.
The requirements, design, implementation, and flight performance of an on-board image compression system for the lunar orbiting Radio Astronomy Explorer-2 (RAE-2) spacecraft are described. The image to be compressed is a panoramic camera view of the long radio astronomy antenna booms used for gravity-gradient stabilization of the spacecraft. A compression ratio of 32 to 1 is obtained by a combination of scan line skipping and adaptive run-length coding. The compressed imagery data are convolutionally encoded for error protection. This image compression system occupies about 1000 cu cm and consumes 0.4 W.
Previous calculations of jet-in-crossflow problems have been sensitive to the turbulence and artificial viscosity models and to the grid. Consequently, the eddy viscosity model in the PARC3D code was modified to consider the turbulent jet by switching from the Baldwin-Lomax (1978) model to an axisymmetric jet model. A modified artificial viscosity model has been utilized and evaluated in this study as well. The new model includes cell size scaling and a directional dependence in the coefficients. Computational results from PARC3D demonstrate the effects of the viscosity models on the pressure distribution fore and aft of the jet and the ability of the adaptive grid scheme to adjust to the three-dimensional gradients around the jet.
The Dugdale analysis for metals loaded in tension was adapted to model the failure of notched composite laminates loaded in compression. Compression testing details, MTS alignment verification, and equipment needs were resolved. Thus far, only 2 ductile material systems, HST7 and F155, were selected for study. A Wild M8 Zoom Stereomicroscope and necessary attachments for video taping and 35 mm pictures were purchased. Currently, this compression test system is fully operational. A specimen is loaded in compression, and load vs shear-crippling zone size is monitored and recorded. Data from initial compression tests indicate that the Dugdale model does not accurately predict the load vs damage zone size relationship of notched composite specimens loaded in compression.
An advanced imaging communication system (AICS) for planetary exploration is presented. The system offers 'end-to-end' information rate improvements of 3 to 5 times over existing systems in addition to extensive user flexibility to adapt his rate/fidelity priorities to fit a particular mission. AICS contains two major system elements. The first is a concatenated Reed-Solomon/Viterbi coded channel. This provides a powerful, yet practical, solution to the usual 'error vulnerability' problem associated with compressed data. The second major element is an extremely adaptive image data compression algorithm called RM2. The details of this algorithm as presently simulated are discussed in considerable detail. Used in conjunction with the virtually error free performance of the Reed-Solomon/Viterbi channel the stated AICS advantages are obtained.
A method of efficiently computing turbulent compressible flow over complex two dimensional configurations is presented. The method makes use of fully unstructured meshes throughout the entire flow field, thus enabling the treatment of arbitrarily complex geometries and the use of adaptive meshing techniques throughout both viscous and inviscid regions of the flow field. Mesh generation is based on a locally mapped Delaunay technique in order to generate unstructured meshes with highly-stretched elements in the viscous regions. The flow equations are discretized using a finite element Navier-Stokes solver, and rapid convergence to steady-state is achieved using an unstructured multigrid algorithm. Turbulence modeling is performed using an inexpensive algebraic model, implemented for use on unstructured and adaptaive meshes. Compressible turbulent flow solutions about multiple-element airfoil geometries are computed and compared with expeirmental data.