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Results for “high 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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1946

Knock-Limited Performance of Triptane and Xylidines Blended with 28-R Aviation Fuel at High Compression Ratios and Maximum-Economy Spark Setting

An investigation was conducted to evaluate the possibilities of utilizing the high-performance characteristics of triptane and xylidines blended with 28-R fuel in order to increase fuel economy by the use of high compression ratios and maximum-economy spark setting. Full-scale single-cylinder knock tests were run with 20 deg B.T.C. and maximum-economy spark settings at compression ratios of 6.9, 8.0, and 10.0, and with two inlet-air temperatures. The fuels tested consisted of triptane, four triptane and one xylidines blend with 28-R, and 28-R fuel alone. Indicated specific fuel consumption at lean mixtures was decreased approximately 17 percent at a compression ratio of 10.0 and maximum-economy spark setting, as compared to that obtained with a compression ratio of 6.9 and normal spark setting. When compression ratio was increased from 6.9 to 10.0 at an inlet-air temperature of 150 F, normal spark setting, and a fuel-air ratio of 0.065, 55-percent triptane was required with 28-R fuel to maintain the knock-limited brake power level obtained with 28-R fuel at a compression ratio of 6.9. Brake specific fuel consumption was decreased 17.5 percent at a compression ratio of 10.0 relative to that obtained at a compression ratio of 6.9. Approximately similar results were noted at an inlet-air temperature of 250 F. For concentrations up through at least 20 percent, triptane can be more efficiently used at normal than at maximum-economy spark setting to maintain a constant knock-limited power output over the range of compression ratios tested.

Held, Louis F.↗
NASA NTRS1981

Ignition and combustion: Low compression ratio, high output diesel

The feasibility of converting a spark ignition aircraft engine GTSI0-520 to compression ignition without increasing the peak combustion pressure of 1100 lbs/sq.in. was determined. The final contemplated utilized intake air heating at idle and light load and a compression ratio of about 10:1 with a small amount of fumigation (the addition of about 15% fuel into the combustion air before the cylinder). The engine used was a modification of a Continental-Teledyne gasoline engine cylinder from the GTSI0-520 supercharged aircraft engine.

Source record↗
DOE OSTI2024

Next Gen High Efficiency Boosted Engine Development

This work represents an advanced engineering research project partially funded by the U.S. Department of Energy (DOE). Ford Motor Company, FEV North America, and Oak Ridge National Laboratory collaborated to develop a next generation boosted spark ignited engine concept. The project goals, specified by the DOE, were 23% improved fuel economy and 15% reduced weight relative to a 2015 or newer light-duty vehicle. The fuel economy goal was achieved by designing an engine incorporating high geometric compression ratio, high dilution tolerance, low pumping work, and low friction. The increased tendency for knock with high compression ratio was addressed using early intake valve closing (EIVC), cooled exhaust gas recirculation (EGR), an active pre-chamber ignition system, and careful management of the fresh charge temperature. Engine weight reduction measures were implemented throughout the engine system making use of composite materials, advanced manufacturing techniques, and architectural choices. This report outlines the analytical, design, fabrication, and test work conducted for the duration of the project. The combustion system stability, EGR tolerance, and knock resistance were validated on a single cylinder engine. An inline six-cylinder engine was then designed targeting application in the Ford F150. Multi-cylinder engines were produced and tested achieving the target vehicle fuel economy improvement of 23% assessed using measured engine fuel consumption combined with a vehicle drive cycle simulation. Actions were identified and designs were demonstrated to achieve the 15% weight reduction target. This project included items covering a range of technology readiness levels. Some of the technologies explored are production ready, while others were investigated to understand the limitations for what can be achieved in a stoichiometric, gasoline-fueled, spark-ignited internal combustion engine.

42 ENGINEERING↗
DOE OSTI2025

Evaluating Chemical Kinetics Predictions for Propane Using 3-D and 0-D Models in a Boosted Spark-Ignited Engine

Propane has been shown to be a promising alternative fuel to reduce emissions while simultaneously achieving high efficiencies in medium- and heavy-duty engines. These high-power density applications require boosted engines which, combined with high compression ratio, can lead to auto-ignition and knock. While three-dimensional (3-D) computational fluid dynamics (CFD) models are often used for resolving the complex fluid flow in engines, these models can become computationally expensive when simulating detailed chemical kinetics. Likewise, zero-dimensional (0-D) models are computationally concise enough for kinetics development, but lack any flow-field information which governs the flame propagation processes in spark ignition (SI) engines. This work presents a comprehensive comparison between 3-D and 0-D closed cycle simulations at knocking conditions in a high compression ratio high stroke-to-bore ratio propane engine. In order to initialize the flow-field for the 3-D closed cycle (intake valve closing, (IVC) to exhaust valve opening, (EVO)) simulation, a motored multi-cycle 3-D model was run using Converge to create a map at IVC, reducing the computational time. The map allowed a non-homogeneous 3-D closed cycle simulation to be satisfactorily validated against experiments, while a homogeneous case using only the turbulence field mapping was also simulated, mimicking 0-D modeling. The 3-D simulations were used to prescribe the initial conditions (e.g., IVC thermodynamics, speciation, burn-rate profile) for a 2-zone 0-D SI engine model in Chemkin Pro for both cases. It was found that 2-zone 0-D modeling underpredicted the knock onset timing, likely due to the lack of thermal stratification in the unburned gas region. Future work will carry multi-zone 0-D modeling to capture the fuel auto-ignition in the unburned region.

Douvry-Rabjeau, Julien [Oakland University, Roches↗
NASA NTRS1986

Aerodynamic instability performance of an advanced high-pressure-ratio compression component

The data acquisition and reduction, test procedures, and results of in-stall and in-surge testing of a NASA high-pressure-ratio compression component are discussed, in addition to the compressor-rig configuration and instrumentation used. Data analysis revealed information about rotating stall hysteresis, rotating stall development and cessation times, and rotating-stall-cell flow blockage. It is found that hysteresis exists in the work coefficient as well as in the pressure coefficient. Airflow rakes were designed to study the in-surge transient response of the compressor. The quasi-steady compressor characteristics underlying the transient-surge data were investigated using a parameter-identification technique.

Hosny, W. M.↗
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 NTRS1925

The effect of changes in compression ratio upon engine performance

This report is based upon engine tests made at the Bureau of Standards during 1920, 1921, 1922, and 1923. The majority of these tests were of aviation engines and were made in the Altitude Laboratory. For a small portion of the work a single cylinder experimental engine was used. This, however, was operated only at sea-level pressures. The report shows that an increase in break horsepower and a decrease in the pounds of fuel used per brake horsepower hour usually results from an increase in compression ratio. This holds true at least up to the highest ratio investigated, 14 to 1, provided there is no serious preignition or detonation at any ratio. To avoid preignition and detonation when employing high-compression ratios, it is often necessary to use some fuel other than gasoline. It has been found that the consumption of some of these fuels in pounds per brake horsepower hour is so much greater than the consumption of gasoline that it offsets the decrease derived from the use of the high-compression ratio. The changes in indicated thermal efficiency with changes in compression ratio are in close agreement with what would be anticipated from a consideration of the air cycle efficiencies at the various ratios. In so far as these tests are concerned there is no evidence that a change in compression ratio produces an appreciable, consistent change in friction horsepower, volumetric efficiency, or in the range of fuel-air ratios over which the engine can operate. The ratio between the heat loss to the jacket water and the heat converted into brake horsepower or indicated horsepower decreases with increase in compression ratio. (author)

Sparrow, Stanwood W↗
NASA NTRS2002

Impact of lossy compression on diagnostic accuracy of radiographs for periapical lesions

OBJECTIVES: The purpose of this study was to evaluate the lossy Joint Photographic Experts Group compression for endodontic pretreatment digital radiographs. STUDY DESIGN: Fifty clinical charge-coupled device-based, digital radiographs depicting periapical areas were selected. Each image was compressed at 2, 4, 8, 16, 32, 48, and 64 compression ratios. One root per image was marked for examination. Images were randomized and viewed by four clinical observers under standardized viewing conditions. Each observer read the image set three times, with at least two weeks between each reading. Three pre-selected sites per image (mesial, distal, apical) were scored on a five-scale score confidence scale. A panel of three examiners scored the uncompressed images, with a consensus score for each site. The consensus score was used as the baseline for assessing the impact of lossy compression on the diagnostic values of images. The mean absolute error between consensus and observer scores was computed for each observer, site, and reading session. RESULTS: Balanced one-way analysis of variance for all observers indicated that for compression ratios 48 and 64, there was significant difference between mean absolute error of uncompressed and compressed images (P <.05). After converting the five-scale score to two-level diagnostic values, the diagnostic accuracy was strongly correlated (R (2) = 0.91) with the compression ratio. CONCLUSION: The results of this study suggest that high compression ratios can have a severe impact on the diagnostic quality of the digital radiographs for detection of periapical lesions.

NASA Discipline Space Human Factors↗
NASA NTRS2015

Performance of a Discrete Wavelet Transform for Compressing Plasma Count Data and its Application to the Fast Plasma Investigation on NASA's Magnetospheric Multiscale Mission

Plasma measurements in space are becoming increasingly faster, higher resolution, and distributed over multiple instruments. As raw data generation rates can exceed available data transfer bandwidth, data compression is becoming a critical design component. Data compression has been a staple of imaging instruments for years, but only recently have plasma measurement designers become interested in high performance data compression. Missions will often use a simple lossless compression technique yielding compression ratios of approximately 2:1, however future missions may require compression ratios upwards of 10:1. This study aims to explore how a Discrete Wavelet Transform combined with a Bit Plane Encoder (DWT/BPE), implemented via a CCSDS standard, can be used effectively to compress count information common to plasma measurements to high compression ratios while maintaining little or no compression error. The compression ASIC used for the Fast Plasma Investigation (FPI) on board the Magnetospheric Multiscale mission (MMS) is used for this study. Plasma count data from multiple sources is examined: resampled data from previous missions, randomly generated data from distribution functions, and simulations of expected regimes. These are run through the compression routines with various parameters to yield the greatest possible compression ratio while maintaining little or no error, the latter indicates that fully lossless compression is obtained. Finally, recommendations are made for future missions as to what can be achieved when compressing plasma count data and how best to do so.

Particles↗
NASA NTRS1989

A comparison of select image-compression algorithms for an electronic still camera

This effort is a study of image-compression algorithms for an electronic still camera. An electronic still camera can record and transmit high-quality images without the use of film, because images are stored digitally in computer memory. However, high-resolution images contain an enormous amount of information, and will strain the camera's data-storage system. Image compression will allow more images to be stored in the camera's memory. For the electronic still camera, a compression algorithm that produces a reconstructed image of high fidelity is most important. Efficiency of the algorithm is the second priority. High fidelity and efficiency are more important than a high compression ratio. Several algorithms were chosen for this study and judged on fidelity, efficiency and compression ratio. The transform method appears to be the best choice. At present, the method is compressing images to a ratio of 5.3:1 and producing high-fidelity reconstructed images.

Nerheim, Rosalee↗
NASA NTRS1937

Effect of Nozzle Design on Fuel Spray and Flame Formation in a High-Speed Compression-Ignition Engine

Fuel was injected from different type of injection nozzles into the combustion chamber of the NACA combustion apparatus, operated as a compression-ignition engine. High speed motion pictures were taken of the fuel sprays and combustion. Single-orifice nozzles of 0.008, 0.020, and 0.040 inch diameter, and multiorifice nozzles having 2, 6, and 16 orifices were tested. Nozzles having impinging jets and slit orifices were also included. The photographs indicate that the rate of vapor diffusion from the spray is comparatively slow and that this slow rate of diffusion for combustion chambers with little or no air flow prevents the compression-ignition engine from giving the high performance inherent in the high compression ratios. The sprays from the multiorifice nozzles destroyed the air movement to a greater extent than did those from single orifice nozzles. It is concluded that high performance cannot be realized until the methods of distributing the fuel are improved by means of the injection-nozzle design, air flow, or both.

Rothrock, A M↗
NASA NTRS1995

A seismic data compression system using subband coding

This article presents a study of seismic data compression techniques and a compression algorithm based on subband coding. The algorithm includes three stages: a decorrelation stage, a quantization stage that introduces a controlled amount of distortion to allow for high compression ratios, and a lossless entropy coding stage based on a simple but efficient arithmetic coding method. Subband coding methods are particularly suited to the decorrelation of nonstationary processes such as seismic events. Adaptivity to the nonstationary behavior of the waveform is achieved by dividing the data into separate blocks that are encoded separately with an adaptive arithmetic encoder. This is done with high efficiency due to the low overhead introduced by the arithmetic encoder in specifying its parameters. The technique could be used as a progressive transmission system, where successive refinements of the data can be requested by the user. This allows seismologists to first examine a coarse version of waveforms with minimal usage of the channel and then decide where refinements are required. Rate-distortion performance results are presented and comparisons are made with two block transform methods.

Kiely, A. B.↗
DOE OSTI2024

Next Generation High Efficiency Boosted Engine Concept

This report summarizes a collaborative research project between Ford Motor Company, FEV North America, and Oak Ridge National Laboratory to develop a next-generation, high-efficiency, boosted spark-ignited engine. The goal was to achieve a 23% improvement in fuel economy and a 15% reduction in engine weight compared to a 2016 Ford F150. The team utilized advanced technologies including a high compression ratio, cooled exhaust gas recirculation (EGR), early intake valve closing, and a novel active pre-chamber ignition system. The final engine prototype met the fuel economy goal and demonstrated a 4.3% weight reduction, with further opportunities identified to reach the full 15% target.

Fuel economy↗
NASA NTRS1936

Friction of Compression-ignition Engines

The cost in mean effective pressure of generating air flow in the combustion chambers of single-cylinder compression-ignition engines was determined for the prechamber and the displaced-piston types of combustion chamber. For each type a wide range of air-flow quantities, speeds, and boost pressures was investigated. Supplementary tests were made to determine the effect of lubricating-oil temperature, cooling-water temperature, and compression ratio on the friction mean effective pressure of the single-cylinder test engine. Friction curves are included for two 9-cylinder, radial, compression-ignition aircraft engines. The results indicate that generating the optimum forced air flow increased the motoring losses approximately 5 pounds per square inch mean effective pressure regardless of chamber type or engine speed. With a given type of chamber, the rate of increase in friction mean effective pressure with engine speed is independent of the air-flow speed. The effect of boost pressure on the friction cannot be predicted because the friction was decreased, unchanged, or increased depending on the combustion-chamber type and design details. High compression ratio accounts for approximately 5 pounds per square inch mean effective pressure of the friction of these single-cylinder compression-ignition engines. The single-cylinder test engines used in this investigation had a much higher friction mean effective pressure than conventional aircraft engines or than the 9-cylinder, radial, compression-ignition engines tested so that performance should be compared on an indicated basis.

Moore, Charles S↗
DOE OSTI2025

Machine Learning Techniques for Data Reduction of Climate Applications

Scientists conduct large-scale simulations to compute derived quantities-of-interest (QoI) from primary data. Often, QoI are linked to specific features, regions, or time intervals, such that data can be adaptively reduced without compromising the integrity of QoI. For many spatiotemporal applications, these QoI are binary in nature and represent presence or absence of a physical phenomenon. We present a pipelined compression approach that first uses neural-network-based techniques to derive regions where QoI are highly likely to be present. Then, we employ a Guaranteed Autoencoder (GAE) to compress data with differential error bounds. GAE uses QoI information to apply low-error compression to only these regions. This results in overall high compression ratios while still achieving downstream goals of simulation or data collections. Experimental results are presented for climate data generated from the E3SM Simulation model for downstream quantities such as tropical cyclone and atmospheric river detection and tracking. These results show that our approach is superior to comparable methods in the literature.

Li, Xiao [University of Florida]↗
DOE OSTI2025

Real Time implementation of Artificial Intelligence compression algorithm for High-Speed Streaming Readout signals

The new generation of high-energy physics experiments plans to acquire data in streaming mode. With this approach, it is possible to access the information of the whole detector (organized in time slices) for optimal and lossless triggering of data acquisitions. With this approach, data rates, especially in large detectors, are often very high, and the network is likely to be the bottleneck for the entire Streaming Read Out system. The aim of this work is to study the implementation of a lossy compression algorithm based on Artificial Intelligence: an Autoencoder. With Machine Learning it is possible to achieve a high compression ratio and fast inference time with only a small degradation of the signals, almost negligible for the specific application. This work explores different configurations of the Autoencoder and the implementation on different hardware. Different Autoencoder configurations are explored to find the best trade-off between compression ratio and reconstruction loss, both for signals and energy spectrum. Different hardware implementations are also explored to find the best platform to achieve real-time performance for the specific application.

Rossi, Fabio (ORCID:0009000385713885)↗
DOE OSTI2024

Identifying Outliers in AI-based Image Compression

Image compression using artificial intelligence (AI) is becoming increasingly prevalent across various fields, including scientific research. Scientific instruments can generate hundreds of images per second, and effectively compressing these images with high compression ratios is crucial for facilitating scientific discoveries. However, automatically detecting outlier cases, where compression may not have succeeded or where interesting scientific phenomena are present, poses a significant challenge. To address this, we have developed a methodology based on unsupervised machine learning techniques for detecting outlier compressed images. This methodology utilizes metrics such as peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), structural texture similarity index measure (STSIM), and deep image and structural texture similarity index (DISTS). We have evaluated our methodology on several unlabeled datasets, including microscopy and x-ray images, and have successfully identified multiple outlier images using our proposed approach. Furthermore, our approach has enabled us to identify image semantics that are valuable for post-experiment analysis by scientists.

Data Analysis↗