Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “COMPRESSION RATIO”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

The effect of lossy image compression on image classification

We have classified four different images, under various levels of JPEG compression, using the following classification algorithms: minimum-distance, maximum-likelihood, and neural network. The training site accuracy and percent difference from the original classification were tabulated for each image compression level, with maximum-likelihood showing the poorest results. In general, as compression ratio increased, the classification retained its overall appearance, but much of the pixel-to-pixel detail was eliminated. We also examined the effect of compression on spatial pattern detection using a neural network.

Paola, Justin D.↗

Quasi-static magnetic compression of field-reversed configuration plasma: amended scalings and limits from two-dimensional MHD equilibrium

In this work, several key scaling laws of the quasi-static magnetic compression of field reversed configuration (FRC) plasma (Spencer et al 1983 Phys. Fluids 26 1564) are amended from a series of two-dimensional FRC MHD equilibriums numerically obtained using the Grad–Shafranov equation solver NIMEQ. Based on the new scaling for the elongation and the magnetic fields at the separatrix and the wall, the empirically stable limits for the compression ratio, the fusion gain, and the neutron yield are evaluated, which may serve as a more accurate estimate for the upper ceiling of performance from the magnetic compression of FRC plasma as a potential fusion energy as well as neutron source devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Performance considerations for the application of the lossless browse and residual model

A hybrid lossless compression model employing both the (lossy) JPEG DCT algorithm and one of a selection of lossless image compression methods has been tested. The hybrid model decomposes the original image into a low-loss quick-look browse and a residual image. The lossless compression methods tested in the model are Huffman, arithmetic, LZW, lossless JPEG, and diagonal coding. For both the direct and the hybrid application of these lossless methods, the compression ratios (CR's) are calculated and compared on three test images. For each lossless method tested, the hybrid model had no more than a nominal loss in compression efficiency relative to the direct approach. In many cases, the hybrid model provided a significant compression gain. When used in the hybrid model, lossless JPEG outperformed the other lossless methods over a broad range of browse image qualities.

Abbott, Walter D., III↗

Stable compression of a spherical tokamak plasma

In this study, an analysis of toroidal plasma compression by a collapsing flux conserver reveals linearly stable scenarios of operation to high compression ratios. The resistive and ideal MHD stability is calculated in full toroidal geometry using the asymptotic matching method in realistic conditions. A time dependent MHD simulation of the compression is conducted to confirm the conservation principles used to calculate the equilibrium states for the analysis. The near edge current profile, controlled by toroidal field ramping during compression, is shown to be critical to stability due to coupling between poloidal components of the least stable mode. Two cases with slight differences in edge current are examined, one with a stable corridor to high compression and one without.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Modeling turbulent energy behavior and sudden viscous dissipation in compressing plasma turbulence

Here, we present a simple model for the turbulent kinetic energy behavior of subsonic plasma turbulence undergoing isotropic three-dimensional compression, which may exist in various inertial confinement fusion experiments or astrophysical settings. The plasma viscosity depends on both the temperature and the ionization state, for which many possible scalings with compression are possible. For example, in an adiabatic compression the temperature scales as 1/L 2 , with L the linear compression ratio, but if thermal energy loss mechanisms are accounted for, the temperature scaling may be weaker. As such, the viscosity has a wide range of net dependencies on the compression. The model presented here, with no parameter changes, agrees well with numerical simulations for a range of these dependencies. This model permits the prediction of the partition of injected energy between thermal and turbulent energy in a compressing plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Cyclobutanedicarboxylate Metal–Organic Frameworks as a Platform for Dramatic Amplification of Pore Partition Effect

Ultrafine tuning of MOF structures at sub-angstrom or picometer levels can help improve separation selectivity for gases with subtle differences. However, for MOFs with large-enough pore size, the effect from ultrafine tuning on sorption can be muted. Here we show an integrative strategy that couples together extreme pore compression with ultrafine pore tuning. Furthermore, this strategy is made possible by unique combination of two features of the pacs platform (pacs = partitioned acs): multi-modular framework and exceptional tolerance towards isoreticular replacement. Specifically, we use one module (Ligand 1, L1) to shrink pore size to an extreme minimum on pacs. A compression ratio of about 30% was achieved (based on unit-cell c/a ratio) from prototypical 1,4-benzenedicarboxylate-pacs to trans-1,3-cyclobutanedicarboxylate-pacs. This is followed by using another module (Ligand 2, L2) for ultrafine pore tuning (< 3% compression). This L1-L2 strategy increases C 2 H 2 /CO 2 selectivity from 2.6 to 20.8 and gives rise to excellent experi-mental breakthrough performance. Being the shortest cyclic dicarboxylate that mimics para-benzene-based moieties us-ing bioisosteric (BIS) strategy on pacs, trans-1,3-cyclobutanedicarboxylate-based MOF chemistry offers new opportuni-ties in MOF chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Invariant regimes of Spencer scaling law for magnetic compression of rotating FRC plasma

Abstract The scaling laws for the magnetic compression of a toroidally rotating field reversed configuration (FRC) have been investigated in this work. The magnetohydrodynamics (MHD) simulations of the magnetic compression on rotating FRCs employing the NIMROD code (Sovinec et al 2004 J. Comput. Phys. 195 355), are compared with the Spencer’s one-dimensional (1D) theory (Spencer et al 1983 Phys. Fluids 26 1564) for a wide range of initial flow speeds and profiles. The toroidal flow can influence the scalings directly through the alteration of the compressional work as also evidenced in the 1D adiabatic model, and indirectly by reshaping the initial equilibrium. However, in comparison to the static initial FRC equilibrium cases, the pressure and the radius scalings remain invariant for the magnetic compression ratio B w 2 / B w 1 up to 6 in presence of the initial equilibrium flow, suggesting a broader applicable regime of the Spencer scaling law for FRC magnetic compression. The invariant scaling has been proven a natural consequence of the conservation of angular momentum of both fluid and magnetic field during the dynamic compression process.

Ma, Yiming↗

A High-Quality Workflow for Multi-Resolution Scientific Data Reduction and Visualization

Multi-resolution methods such as Adaptive Mesh Refinement (AMR) can enhance storage efficiency for HPC applications generating vast volumes of data. However, their applicability is limited and cannot be universally deployed across all applications. Furthermore, integrating lossy compression with multi-resolution techniques to further boost storage efficiency encounters significant barriers. To this end, we introduce an innovative workflow that facilitates high-quality multi-resolution data compression for both uniform and AMR simulations. Initially, to extend the usability of multi-resolution techniques, our workflow employs a compression-oriented Region of Interest (ROI) extraction method, transforming uniform data into a multi-resolution format. Subsequently, to bridge the gap between multi-resolution techniques and lossy compressors, we optimize three distinct compressors, ensuring their optimal performance on multi-resolution data. These optimizations can improve the compression ratio of SOTA approaches by up to 3.3× under the same data quality loss. Lastly, we incorporate an advanced uncertainty visualization method into our workflow to understand the potential impacts of lossy compression. Experimental evaluation demonstrates that our workflow achieves significant compression quality improvements.

Wang, Daoce↗

Achieving Diesel-Like Efficiency in a High Stroke-to-Bore Ratio DISI Engine under Stoichiometric Operation

This work explores pathways to achieve diesel-like, high-efficiency combustion with stoichiometric 3-way catalyst compatible spark ignition (SI). A high stroke-to-bore engine design (1.5:1) with cooled exhaust gas recirculation (EGR) and high compression ratio (r c ) was used to improve engine efficiency by up to 30% compared with a production turbocharged gasoline direct injection spark ignition engine. To achieve efficiency improvements, engine experiments were coupled with computational fluid dynamics simulations to guide and explain experimental trends between the original engine and the high stroke-to-bore ratio design (1.5:1). The effects of EGR and late intake valve closing (IVC) and fuel characteristics are investigated through their effects on knock mitigation. Direct injection of 91 RON E10 gasoline, 99 RON E0 gasoline, and liquified petroleum gas (i.e., propane/autogas) were evaluated with geometric rc ranging from 13.3:1 to 16.8:1. Finally, engine experiments demonstrated 47% gross thermal efficiency, and 45% net thermal efficiency at stoichiometric engine operation, at up to 17 bar IMEP and 2000 r/min with 16.8:1 rc.

42 ENGINEERING↗

SAR image data compression for an on-line archive system

This paper summarizes the investigation of SAR image data compression for an on-line archive data distribution system. This system is planned for the ground processing system of Alaska SAR Facility (ASF) and Shuttle Imaging Radar (SIR-C). The objective of the SAR image data compression is to enable the data archive system to provide the remote users a large data base with good image quality, short response time, low transfer cost, and minimal decoding complexity. The requirements and limitations of the on-line archive data distribution system are presented. The effects of SAR image data characteristics on data compression are addressed. The users' survey results suggest that compression ratios between 10:1 and 20:1 appear suitable. Based on the algorithm evaluation results, the two-level tree-searched vector quantization technique has been recommended as the SAR image data compression algorithm for the on-line archive data distribution system.

Chang, C. Y.↗

Multidimensional Numerical Simulations of Knocking Combustion in a Cooperative Fuel Research Engine

A numerical approach was developed based on multidimensional computational fluid dynamics (CFD) to predict knocking combustion in a cooperative fuel research (CFR) engine. G-equation model was employed to track the turbulent flame front and a multizone model was used to capture auto-ignition in the end-gas. Furthermore, a novel methodology was developed wherein a lookup table generated from a chemical kinetic mechanism could be employed to provide laminar flame speed as an input to the Gequation model, instead of using empirical correlations. To account for fuel chemistry effects accurately and lower the computational cost, a compact 121-species primary reference fuel (PRF) skeletal mechanism was developed from a detailed gasoline surrogate mechanism using the directed relation graph (DRG) assisted sensitivity analysis (DRGASA) reduction technique. Extensive validation of the skeletal mechanism was performed against experimental data available from the literature on both homogeneous ignition delay and laminar flame speed. The skeletal mechanism was used to generate lookup tables for laminar flame speed as a function of pressure, temperature, and equivalence ratio. The numerical model incorporating the skeletal mechanism was employed to perform simulations under research octane number (RON) and motor octane number (MON) conditions for two different PRFs. Parametric tests were conducted at different compression ratios (CR) and the predicted values of critical CR, delineating the boundary between “no knock” and “knock,” were found to be in good agreement with available experimental data. The virtual CFR engine model was, therefore, demonstrated to be capable of adequately capturing the sensitivity of knock propensity to fuel chemistry.

CFD↗

zPerf: A Statistical Gray-Box Approach to Performance Modeling and Extrapolation for Scientific Lossy Compression

With the scaling up of simulation-based scientific discovery on high-performance computing systems, the disparity between compute and I/O has increased, forcing domain scientists to save only a small amount of simulation data to persistent storage. This can result in the loss of essential physics fields that are needed for data analysis. While error-bounded lossy compression has made tremendous progress in bridging the gap between compute and I/O, the lack of understanding of compression performance remains a key hurdle to its wide adoption. Here, in this work, we present zPerf, a statistical gray-box performance modeling approach for scientific lossy compression. Our contributions are threefold: 1) We develop zPerf to estimate the performance of lossy compression techniques, based on in-depth understanding and statistical modeling for data features and core compression metrics; 2) We demonstrate the in-detailed implementation of zPerf using two case studies, where we derive the performance modeling for SZ and ZFP, two leading lossy compressors; 3) We evaluate the effectiveness of zPerf on real-world datasets across various domains. Based on the evaluation, we demonstrate the efficacy of the zPerf performance model; 4) We further discuss three case studies where zPerf is applied to extrapolate the compression ratio of SZ and ZFP with alternative encoding schemes as well as ZFP with an alternative transform scheme. Through the case studies, we demonstrate the potential of zPerf for exploring the design space of lossy compression, which has hardly been studied in the literature.

97 MATHEMATICS AND COMPUTING↗

Fast 2D Bicephalous Convolutional Autoencoder for Compressing 3D Time Projection Chamber Data

High-energy large-scale particle colliders produce data at high speed in the order of 1 terabytes per second in nuclear physics and petabytes per second in high energy physics. Developing real-time data compression algorithms to reduce such data at high throughput to fit permanent storage has drawn increasing attention. Specifically, at the newly constructed sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC), a time projection chamber is used as the main tracking detector, which records particle trajectories in a volume of three-dimensional (3D) cylinder. The resulting data are usually very sparse with occupancy around 10.8%. Such sparsity presents a challenge to conventional learning-free lossy compression algorithms, such as SZ, ZFP, and MGARD. The 3D convolutional neural network (CNN)-based approach, Bicephalous Convolutional Autoencoder (BCAE), outperforms traditional methods both in compression rate and reconstruction accuracy. BCAE can also utilize the computation power of graphical processing units suitable for deployment in a modern heterogeneous highperformance computing environment. This work introduces two BCAE variants: BCAE++ and BCAE-2D. BCAE++ achieves a 15% better compression ratio and a 77% better reconstruction accuracy measured in mean absolute error compared with BCAE. BCAE-2D treats the radial direction as the channel dimension of an image, resulting in a 3× speedup in compression throughput. In addition, we demonstrate an unbalanced autoencoder with a larger decoder can improve reconstruction accuracy without significantly sacrificing throughput. Lastly, we observe both the BCAE++ and BCAE-2D can benefit more from using half-precision mode in throughput (76 - 79% increase) without loss in reconstruction accuracy. The source code and links to data and pretrained models can be found at https://github.com/BNL-DAQ-LDRD/NeuralCompression_v2

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Performance Optimization for Relative-Error-Bounded Lossy Compression on Scientific Data

Scientific simulations in high-performance computing (HPC) environments generate vast volume of data, which may cause a severe I/O bottleneck at runtime and a huge burden on storage space for postanalysis. Unlike traditional data reduction schemes such as deduplication or lossless compression, not only can error-controlled lossy compression significantly reduce the data size but it also holds the promise to satisfy user demand on error control. Pointwise relative error bounds (i.e., compression errors depends on the data values) are widely used by many scientific applications with lossy compression since error control can adapt to the error bound in the dataset automatically. Pointwise relative-error-bounded compression is complicated and time consuming. In this article, we develop efficient precomputation-based mechanisms based on the SZ lossy compression framework. Our mechanisms can avoid costly logarithmic transformation and identify quantization factor values via a fast table lookup, greatly accelerating the relative-error-bounded compression with excellent compression ratios. In addition, we reduce traversing operations for Huffman decoding, significantly accelerating the decompression process in SZ. Experiments with eight well-known real-world scientific simulation datasets show that our solution can improve the compression and decompression rates (i.e., the speed) by about 40 and 80 p, respectively, in most of cases, making our designed lossy compression strategy the best-in-class solution in most cases.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

A stable corridor for toroidal plasma compression

In this study, a toroidal plasma compressed by a collapsing flux conserver is analyzed to reveal stable scenarios of operation to high compression ratios. The resistive and ideal MHD stability is calculated in full toroidal geometry, using the asymptotic matching method in realistic conditions, and comparing with nonlinear simulations. The near edge current profile, controlled by toroidal field ramping during compression, is shown to be critical to stability due to coupling between poloidal components of the least stable mode. The extension of a length of shaft on axis is also found to be critical at high compression, as the resulting good curvature region in magnetic field stabilizes pressure driven modes that would otherwise be unstable. This work extends from previous studies, which initially showed the existence of a stable scenario, to include findings of more extensive stable zones, detailed effects of geometry, and nonlinear simulations of the instabilities. The nonlinear simulations of the compression are consistent with the linear analyses, confirming both the conservation and stability properties.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Preliminary Study of Fuel Injection and Compression Ignition as Applied to an Aircraft Engine Cylinder

This report summarizes some results obtained with a single cylinder test engine at the Langley Field Laboratory during a preliminary investigation of the problem of applying fuel injection and compression ignition to aircraft engines. For this work a standard Liberty Engine cylinder was fitted with a high compression, 11.4 : 1 compression ratio, piston, and equipped with an airless injection system, including a primary fuel pump, an injection pump, and an automatic injection valve. The results obtained during this investigation have indicated the possibility of applying airless injection and compression ignition to a cylinder of this size, 8-inch bore by 7-inch stroke, when operating at engine speeds as high as 1,850 R. P. M. A minimum specific fuel consumption with diesel engine fuel oil of 0.30 pound per I. HP. Hour was obtained when developing about 16 B. HP. At 1,730 R. P. M.

Gardiner, Arthur W↗

Numerical studies of the formation and destruction of vortices in a motored four-stroke piston-cylinder configuration

A finite-difference procedure which solves the conservation equations of mass, momentum, and energy is used to investigate the effects of the compression ratio, engine speed, bore-to-stroke ratio, and air intake flow angle on the turbulent flow field within an axisymmetric piston-cylinder configuration. It is shown that in a four-stroke piston-cylinder configuration, the intake stroke is characterized by the formation of a piston vortex. The piston vortex is stretched during the intake stroke, and the head vortex has an almost constant diameter. For a 0-deg air intake flow angle, both vortices disappear by the end of the compression stroke; for an air intake flow angle of 45 deg, the flow field within the cylinder shows three elongated vortices which persist into the compression stroke and then break up and merge. It is also shown that larger bore-to-stroke ratios give rise to lower turbulent levels than smaller bore-to-stroke ratios and that the turbulent intensity is almost independent of the rpm.

Schock, H. J.↗

Maintaining Trust in Reduction: Preserving the Accuracy of Quantities of Interest for Lossy Compression

As the growth of data sizes continues to outpace computational resources, there is a pressing need for data reduction techniques that can significantly reduce the amount of data and quantify the error incurred in compression. Compressing scientific data presents many challenges for reduction techniques since it is often on non-uniform or unstructured meshes, is from a high-dimensional space, and has many Quantities of Interests (QoIs) that need to be preserved. To illustrate these challenges, we focus on data from a large scale fusion code, XGC. XGC uses a Particle-In-Cell (PIC) technique which generates hundreds of PetaBytes (PBs) of data a day, from thousands of timesteps. XGC uses an unstructured mesh, and needs to compute many QoIs from the raw data, f.One critical aspect of the reduction is that we need to ensure that QoIs derived from the data (density, temperature, flux surface averaged momentums, etc.) maintain a relative high accuracy. We show that by compressing XGC data on the high-dimensional, nonuniform grid on which the data is defined, and adaptively quantizing the decomposed coefficients based on the characteristics of the QoIs, the compression ratios at various error tolerances obtained using a multilevel compressor (MGARD) increases more than ten times. We then present how to mathematically guarantee that the accuracy of the QoIs computed from the reduced f is preserved during the compression. We show that the error in the XGC density can be kept under a user-specified tolerance over 1000 timesteps of simulation using the mathematical QoI error control theory of MGARD, whereas traditional error control on the data to be reduced does not guarantee the accuracy of the QoIs.

Gong, Qian↗