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All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Communications and information research: Improved space link performance via concatenated forward error correction coding

With the development of new advanced instruments for remote sensing applications, sensor data will be generated at a rate that not only requires increased onboard processing and storage capability, but imposes demands on the space to ground communication link and ground data management-communication system. Data compression and error control codes provide viable means to alleviate these demands. Two types of data compression have been studied by many researchers in the area of information theory: a lossless technique that guarantees full reconstruction of the data, and a lossy technique which generally gives higher data compaction ratio but incurs some distortion in the reconstructed data. To satisfy the many science disciplines which NASA supports, lossless data compression becomes a primary focus for the technology development. While transmitting the data obtained by any lossless data compression, it is very important to use some error-control code. For a long time, convolutional codes have been widely used in satellite telecommunications. To more efficiently transform the data obtained by the Rice algorithm, it is required to meet the a posteriori probability (APP) for each decoded bit. A relevant algorithm for this purpose has been proposed which minimizes the bit error probability in the decoding linear block and convolutional codes and meets the APP for each decoded bit. However, recent results on iterative decoding of 'Turbo codes', turn conventional wisdom on its head and suggest fundamentally new techniques. During the past several months of this research, the following approaches have been developed: (1) a new lossless data compression algorithm, which is much better than the extended Rice algorithm for various types of sensor data, (2) a new approach to determine the generalized Hamming weights of the algebraic-geometric codes defined by a large class of curves in high-dimensional spaces, (3) some efficient improved geometric Goppa codes for disk memory systems and high-speed mass memory systems, and (4) a tree based approach for data compression using dynamic programming.

Rao, T. R. N.↗
NASA NTRS1989

Fractal image compression

Fractals are geometric or data structures which do not simplify under magnification. Fractal Image Compression is a technique which associates a fractal to an image. On the one hand, the fractal can be described in terms of a few succinct rules, while on the other, the fractal contains much or all of the image information. Since the rules are described with less bits of data than the image, compression results. Data compression with fractals is an approach to reach high compression ratios for large data streams related to images. The high compression ratios are attained at a cost of large amounts of computation. Both lossless and lossy modes are supported by the technique. The technique is stable in that small errors in codes lead to small errors in image data. Applications to the NASA mission are discussed.

Barnsley, Michael F.↗
NASA NTRS1994

New constitutive equation for the volume viscosity in fluids

The traditional volume viscosity, Stokes' hypothesis, and acoustical relaxation are reviewed. The lossy Navier-Stokes Equation is applied to periodic (acoustic) flow, and it is shown that the traditional volume viscosity leads to a result which contradicts that describing acoustical relaxation. It is demonstrated that the addition of a second volume viscosity term to the constitutive equation, to account for pressure relaxation, resolves the conflict, and leads to a direct correspondence between the volume viscosity parameters and the acoustical relaxation parameters. The representation of volume viscosity is formulated for the case of multiple relaxations, as occur in air. Finally, an application of the new constitutive equation to a simple convective compressible flow, namely a linearly accelerating flow, demonstrates the impact of volume viscosity upon the flow and the physical conditions for which it is important.

Zuckerwar, Allan J.↗
NASA NTRS2000

Unsteady Analysis of Inlet-Compressor Acoustic Interactions Using Coupled 3-D and 1-D CFD Codes

It is well known that the dynamic response of a mixed compression supersonic inlet is very sensitive to the boundary condition imposed at the subsonic exit (engine face) of the inlet. In previous work, a 3-D computational fluid dynamics (CFD) inlet code (NPARC) was coupled at the engine face to a 3-D turbomachinery code (ADPAC) simulating an isolated rotor and the coupled simulation used to study the unsteady response of the inlet. The main problem with this approach is that the high fidelity turbomachinery simulation becomes prohibitively expensive as more stages are included in the simulation. In this paper, an alternative approach is explored, wherein the inlet code is coupled to a lesser fidelity 1-D transient compressor code (DYNTECC) which simulates the whole compressor. The specific application chosen for this evaluation is the collapsing bump experiment performed at the University of Cincinnati, wherein reflections of a large-amplitude acoustic pulse from a compressor were measured. The metrics for comparison are the pulse strength (time integral of the pulse amplitude) and wave form (shape). When the compressor is modeled by stage characteristics the computed strength is about ten percent greater than that for the experiment, but the wave shapes are in poor agreement. An alternate approach that uses a fixed rise in duct total pressure and temperature (so-called 'lossy' duct) to simulate a compressor gives good pulse shapes but the strength is about 30 percent low.

Suresh, A.↗