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Results for “lossy compression”

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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113 records · Page 7
All sourcesNASA NTRSDOE OSTI
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.↗
DOE OSTI2024

guppy i : a code for reducing the storage requirements of cosmological simulations

ABSTRACT As cosmological simulations have grown in size, the permanent storage requirements of their particle data have also grown. Even modest simulations present a major logistical challenge for the groups which run these boxes and researchers without access to high performance computing facilities often need to restrict their analysis to lower quality data. In this paper, we present guppy, a compression algorithm and code base tailored to reduce the sizes of dark matter-only cosmological simulations by approximately an order of magnitude. guppy is a ‘lossy’ algorithm, meaning that it injects a small amount of controlled and uncorrelated noise into particle properties. We perform extensive tests on the impact that this noise has on the internal structure of dark matter haloes, and identify conservative accuracy limits which ensure that compression has no practical impact on single-snapshot halo properties, profiles, and abundances. We also release functional prototype libraries in C, Python, and Go for reading and creating guppy data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

QProR: An Efficient Framework for Quantity-of-Interest Based Progressive Retrieval with Guaranteed Error Control

Scientific applications generate an unprecedented volume of data, overwhelming the network and file systems’ bandwidth and posing challenges for efficient and scalable data retrieval and analysis. Progressive data compression offers a promising solution by enabling on-demand retrieval at reduced size. However, existing progressive methods either fail to bound the errors in essential quantities of interest (QoIs) derived from raw data or suffer from suboptimal retrieval efficiency. In this work, we propose QProR, an efficient QoI-based progressive framework that optimizes progressive retrieval for target QoIs. Our key contributions include: (1) a systematic framework that integrates error-controlled lossy compressors with bitplane encoding while decoupling the two processes for high flexibility and adaptability; (2) a novel weighted bitplane encoding method which incorperates QoI knowledge into data refactoring to enhance retrieval efficiency; (3) an optimized retrieval strategy that accounts for the varying impacts of different variables on multivariate QoIs; (4) comprehensive evaluations using six real-world datasets from multiple scientific applications and thorough comparisons against state of the arts. Experimental results demonstrate that QProR achieves up to 80.38% reduction in the retrieval size under the same requested QoI error tolerance, when compared with the best-performing existing methods. When transferring 384 GB of scientific data to remote sites, QProR delivers up to 1.68 × speedup in the end-to-end data transfer performance.

Li, Wenbo [University of Kentucky]↗
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.↗