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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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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Scheduled Sequential Compressed Spectrum Sensing for Wideband Cognitive Radios

The support for high data rate applications with the cognitive radio technology necessitates wideband spectrum sensing. However, it is costly to apply long-term wideband sensing and is especially difficult in the presence of uncertainty, such as high noise, interference, outliers, and channel fading. In this paper, we propose scheduling of sequential compressed spectrum sensing which jointly exploits compressed sensing (CS) and sequential periodic detection techniques to achieve more accurate and timely wideband sensing. Instead of invoking CS to reconstruct the signal in each period, our proposed scheme performs backward grouped-compressed-data sequential probability ratio test (backward GCD-SPRT) using compressed data samples in sequential detection, while CS recovery is only pursued when needed. This method on one hand significantly reduces the CS recovery overhead, and on the other takes advantage of sequential detection to improve the sensing quality. Furthermore, we propose (a) an in-depth sensing scheme to accelerate sensing decision-making when a change in channel status is suspected, (b) a block-sparse CS reconstruction algorithm to exploit the block sparsity properties of wide spectrum, and (c) a set of schemes to fuse results from the recovered spectrum signals to further improve the overall sensing accuracy. Finally, extensive performance evaluation results show that our proposed schemes can significantly outperform peer schemes under sufficiently low SNR settings.

42 ENGINEERING↗
DOE OSTI2019

TTHRESH: Tensor Compression for Multidimensional Visual Data

Memory and network bandwidth are decisive bottlenecks when handling high-resolution multidimensional data sets in visualization applications, and they increasingly demand suitable data compression strategies. In this paper, we introduce a novel lossy compression algorithm for multidimensional data over regular grids. It leverages the higher-order singular value decomposition (HOSVD), a generalization of the SVD to three dimensions and higher, together with bit-plane, run-length and arithmetic coding to compress the HOSVD transform coefficients. Our scheme degrades the data particularly smoothly and achieves lower mean squared error than other state-of-the-art algorithms at low-to-medium bit rates, as it is required in data archiving and management for visualization purposes. Further advantages of the proposed algorithm include very fine bit rate selection granularity and the ability to manipulate data at very small cost in the compression domain, for example to reconstruct filtered and/or subsampled versions of all (or selected parts) of the data set.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Dynamic Compression of Spinor Exciton-Polariton Systems in Semiconductor Microcavities

The dynamically compressed coherent exciton-polariton condensate state was implemented at the low polariton (LP) band bottom in GaAs microcavity resonantly excited in a wide range of wavevectors by the convergent 2.5-ps long Gaussian linearly polarized beam when the active region of the cavity was ahead of the waist. Formation of the dynamically compressed condensate state at the LP band bottom and its further dynamics are shown to be well described by the Gross-Pitaevskii equation. The state persists for several picosecond until LP-LP repulsion causes its expansion in both spatial and momentum spaces. Dynamic compression of an elliptically polarized LP system is found to occur without preserving its initial polarization: the dynamic compression of weakly interacting components with σ{sup +} and σ{sup −} polarization occurs almost independently.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Compressed Sensing with Sparse Corruptions: Fault-Tolerant Sparse Collocation Approximations

The recovery of approximately sparse or compressible coefficients in a polynomial chaos expansion is a common goal in many modern parametric uncertainty quantification (UQ) problems. However, relatively little effort in UQ has been directed toward theoretical and computational strategies for addressing the sparse corruptions problem, where a small number of measurements are highly corrupted. Such a situation has become pertinent today since modern computational frameworks are sufficiently complex with many interdependent components that may introduce hardware and software failures, some of which can be difficult to detect and result in a highly polluted simulation result. In this paper we present a novel compressive sampling--based theoretical analysis for a regularized $\ell^1$ minimization algorithm that aims to recover sparse expansion coefficients in the presence of measurement corruptions. Our recovery results are uniform (the theoretical guarantees hold for all compressible signals and compressible corruptions vectors) and prescribe algorithmic regularization parameters in terms of a user-defined a priori estimate on the ratio of measurements that are believed to be corrupted. We also propose an iteratively reweighted optimization algorithm that automatically refines the value of the regularization parameter and empirically produces superior results. Lastly, our numerical results test our framework on several medium to high dimensional examples of solutions to parameterized differential equations and demonstrate the effectiveness of our approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Multilevel Techniques for Compression and Reduction of Scientific Data-Quantitative Control of Accuracy in Derived Quantities

Although many compression algorithms are focused on preserving pointwise values of the data, application scientists are generally more concerned with derived quantities. Equally well, the user may even be willing to accept a high level of lossiness in the compression provided that the compressed data respect certain invariants, such as mass conservation. In the current work, we develop a mathematical framework and techniques that enable data to be adaptively compressed while maintaining a specified tolerance on a class of user-prescribed quantities. Here, the algorithm is used to augment the functionality of the data reduction package MGARD developed in previous work and the functionality is illustrated by a range of application including data from computational simulation of autocatalytic reaction simulation, turbulent combustion simulation, experimental data obtained from magnetic confinement fusion experiment, and simulation of turbulent flow along a rectangular channel. In each case, we consider one or more relevant quantities of interest and reduce the data so as to preserve these quantities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Effects of injection parameters, boost, and swirl ratio on gasoline compression ignition operation at idle and low-load conditions

In this study, we study the effects of injector nozzle inclusion angle, injection pressure, boost, and swirl ratio on gasoline compression ignition combustion. Closed-cycle computational fluid dynamics simulations using a 1/7th sector mesh representing a single cylinder of a four-cylinder 1.9 L diesel engine, operated in gasoline compression ignition mode with 87 anti-knock index (AKI) gasoline, were performed. Two different operating conditions were studied—the first is representative of idle operation (4 mg fuel/cylinder/cycle, 850 r/min), and the second is representative of a low-load condition (10 mg fuel/cylinder/cycle, 1500 r/min). The mixture preparation and reaction space from the simulations were analyzed to gain insights into the effects of injection pressure, nozzle inclusion angle, boost, and swirl ratio on achieving stable low-load to idle gasoline compression ignition operation. It was found that narrower nozzle inclusion angles allow for more reactivity or propensity to ignition (determined qualitatively by computing constant volume ignition delays) and are suitable over a wider range of injection timings. Under idle conditions, it was found that lower injection pressures helped to reduce overmixing of the fuel, resulting in greater reactivity and ignitability (ease with which ignition can be achieved) of the gasoline. However, under the low-load condition, lower injection pressures did not increase ignitability, and it is hypothesized that this is because of reduced chemical residence time resulting from longer injection durations. Reduced swirl was found to maintain higher in-cylinder temperatures through compression, resulting in better ignitability. It was found that boosting the charge also helped to increase reactivity and advanced ignition timing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Experimental investigation of the relationship between thermal barrier coating structured porosity and homogeneous charge compression ignition engine combustion

Heat transfer has a monumental influence on homogeneous charge compression ignition combustion. When a thermal barrier coating is applied to the combustion chamber, the insulating effect magnifies the wall temperature swing, decreasing heat transfer during combustion. This enables improvements in both thermal and combustion efficiency without the detrimental impacts of intake charge heating. Increasing the temperature swing requires coatings with lower thermal conductivity and heat capacity. An enticing avenue for simultaneously decreasing both thermal conductivity and capacity is to increase the porosity fraction. A proprietary solution precursor plasma spray process enables discrete organization of the porosity structure, called inter-pass boundaries, which in turn produces a step-reduction in thermal conductivity for a given porosity level. In this investigation, yttria-stabilized zirconia is used to create four different thermal barrier coatings to study the potential of structured porosity as means of improving the “temperature swing” behavior in a homogeneous charge compression ignition engine. The baseline coating is “dense YSZ,” applied using a standard air-plasma spray process. Furthermore, significant reductions of the thermal conductivity are achieved by utilizing the solution precursor plasma spray process to create inter-pass boundaries with a moderate overall porosity. Performance, efficiency, and emissions are compared against both a baseline configuration with a metal piston and an air-plasma spray “dense YSZ” coating. Experiments are carried out in a single-cylinder gasoline homogeneous charge compression ignition engine with exhaust re-induction. Experiments indicate that incorporating structured porosity into thermal barrier coatings produces tangible gains in combustion and thermal efficiencies. However, there is an upper limit to porosity levels acceptable for homogeneous charge compression ignition engine application because an elevated porosity fraction leads to excessive surface roughness and undesirable fuel interactions. Comparison of the coatings showed the best results with coating thickness of up to 150 µm. Thicker coatings led to slower surface temperature response and attenuated swing temperature magnitude.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Enhancing the efficiency benefit of thermal barrier coatings for homogeneous charge compression ignition engines through application of a low-k oxide

Prior experiments reported by the authors have proven the hypothesis that achieving a dynamic temperature swing on the combustion chamber surface will lead to improved thermal and combustion efficiencies of the homogeneous charge compression ignition engine. A thin layer of yttria-stabilized zirconia, roughly 150 μm, was plasma sprayed on the piston top. It led to markedly advanced ignition and heat release in the gasoline homogeneous charge compression ignition engine, accompanied with reduced unburnt hydrocarbon and carbon monoxide emissions, improved combustion efficiency, and a higher thermal efficiency. A related computational study highlighted the critical role of coating thermal conductivity in achieving a desired dynamic response; hence, the second phase of experimental investigations focused on introducing structured porosity in the yttria-stabilized zirconia coating, as a means of reducing effective conductivity. Indeed, additional incremental improvements were observed, as well as limitations related to adverse effects of the surface roughness and the fuel interactions with the surface roughness and open pores. Erosion can also be a problem in a direct injection engine. Therefore, the third round of investigations focused on a material with a natively low conductivity (low-k), sprayed on the top of an Al piston in a relatively dense form, and in a way that yields a smooth surface. The objective was to capitalize on the low conductivity, while avoiding the pitfalls accompanying high-porosity formulations. The heat-storage capacity was limited by keeping the thickness relatively low. The results verify the paramount importance of thermal conductivity in the context of high “temperature swing” behavior and indicate a potential to improve the homogeneous charge compression ignition engine’s combustion efficiency roughly 1.5%, with the overall indicated efficiency improvement on the order of 5%, on a relative basis. In addition, the low-k oxide thermal barrier applied to the piston extended significantly the low-load homogeneous charge compression ignition operability limit.

42 ENGINEERING↗
DOE OSTI2020

Computationally efficient evaluation of optimum homogeneous charge compression ignition operating range with accelerated multizone engine cycle simulation

The very intensive calculations necessary to define a performance map requiring evaluation of over a hundred individual operating points can be efficiently conducted with accelerated multizone for engine cycle simulation, leading to a definition of regions of acceptable and optimum homogeneous charge compression ignition operation. Accelerated multizone for engine cycle simulation has the virtue of enabling accurate evaluation of many operating conditions based on thermal stratification data from a single fluid mechanics run at motored conditions. This is possible because thermal stratification is more sensitive to engine geometry than to operating conditions. In this article, accuracy of accelerated multizone for engine cycle simulation is demonstrated by comparison with experimental data for iso-octane homogeneous charge compression ignition operation over a broad range of lean equivalence ratios (0.14–0.28). The validated accelerated multizone for engine cycle simulation model is then applied to generating a performance map for an engine controlled by appropriately adjusting equivalence ratio and internal exhaust gas recirculation. Regions of acceptable and optimum combustion are identified. It is finally demonstrated that while indicated mean effective pressure remains low for optimum homogeneous charge compression ignition operation (1–4 bar), this is sufficient for a large fraction of typical driving in light-duty vehicles. Much driving including idle can therefore be done in homogeneous charge compression ignition mode at high efficiency and low (essentially zero) NOx and particulate matter emissions.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2019

Ultra-High Pressure Dynamic Compression of Geological Materials

Dynamic-compression experiments on geological materials are important for understanding the composition and physical state of the deep interior of the Earth and other planets. These experiments also provide insights into impact processes relevant to planetary formation and evolution. Recently, new techniques for dynamic compression using high-powered lasers and pulsed-power systems have been developed. These methods allow for compression on timescales ranging from nanoseconds to microseconds and can often achieve substantially higher pressure than earlier gas-gun-based loading techniques. The capability to produce shockless (i.e., ramp) compression provides access to new regimes of pressure–temperature space and new diagnostics allow for a more detailed understanding of the structure and physical properties of materials under dynamic loading. This review summarizes these recent advances, focusing on results for geological materials at ultra-high pressures above 200 GPa. Implications for the structure and dynamics of planetary interiors are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

A Novel CAE Method for Compression Molding Simulation of Carbon Fiber-Reinforced Thermoplastic Composite Sheet Materials

Its high-specific strength and stiffness with lower cost make discontinuous fiber-reinforced thermoplastic (FRT) materials an ideal choice for lightweight applications in the automotive industry. Compression molding is one of the preferred manufacturing processes for such materials as it offers the opportunity to maintain a longer fiber length and higher volume production. In the past, we have demonstrated that compression molding of FRT in bulk form can be simulated by treating melt flow as a continuum using the conservation of mass and momentum equations. However, the compression molding of such materials in sheet form using a similar approach does not work well. The assumption of melt flow as a continuum does not hold for such deformation processes. To address this challenge, we have developed a novel simulation approach. First, the draping of the sheet was simulated as a structural deformation using the explicit finite element approach. Next, the draped shape was compressed using fluid mechanics equations. The proposed method was verified by building a physical part and comparing the predicted fiber orientation and warpage measurements performed on the physical parts. The developed method and tools are expected to help in expediting the development of FRT parts, which will help achieve lightweight targets in the automotive industry.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Energy Cascade Rate in Compressible Fast and Slow Solar Wind Turbulence

Estimation of the energy cascade rate in the inertial range of solar wind turbulence has been done so far mostly within incompressible magnetohydrodynamics (MHD) theory. Here, we go beyond that approximation to include plasma compressibility using a reduced form of a recently derived exact law for compressible, isothermal MHD turbulence. Using in situ data from the THEMIS / ARTEMIS spacecraft in the fast and slow solar wind, we investigate in detail the role of the compressible fluctuations in modifying the energy cascade rate with respect to the prediction of the incompressible MHD model. In particular, we found that the energy cascade rate (1) is amplified particularly in the slow solar wind; (2) exhibits weaker fluctuations in spatial scales, which leads to a broader inertial range than the previous reported ones; (3) has a power-law scaling with the turbulent Mach number; (4) has a lower level of spatial anisotropy. Other features of solar wind turbulence are discussed along with their comparison with previous studies that used incompressible or heuristic (nonexact) compressible MHD models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Total variation vs L1 regularization: a comparison of compressive sensing optimization methods for chemical detection

One of the fundamental assumptions of compressive sensing (CS) is that a signal can be reconstructed from a small number of samples by solving an optimization problem with the appropriate regularization term. Two standard regularization terms are the L1 norm and the total variation (TV) norm. We present a comparison of CS reconstruction results based on these two approaches in the context of chemical detection, and we demonstrate that optimization based on the L1 norm outperforms optimization based on the TV norm. Our comparison is driven by CS sampling, reconstruction, and chemical detection in two real-world datasets: the Physical Sciences Inc. Fabry-Perot interferometer sensor multispectral dataset and the Johns Hopkins Applied Physics Lab FTIR-based longwave infrared sensor hyperspectral dataset. Both datasets contain the release of a chemical simulant such as glacial acetic acid, triethyl phosphate, and sulfur hexafluoride. For chemical detection we use the adaptive coherence estimator (ACE) and bulk coherence, and we propose algorithmic ACE thresholds to define the presence or absence of a chemical of interest in both un-compressed data cubes and reconstructed data cubes. The un-compressed data cubes provide an approximate ground truth. We demonstrate that optimization based on either the L1 norm or TV norm results in successful chemical detection at a compression rate of 90%, but we show that L1 optimization is preferable. We present quantitative comparisons of chemical detection on reconstructions from the two methods, with an emphasis on the number of pixels with an ACE value above the threshold.

Hyperspectral imagery, L1-norm, total variation, A↗
DOE OSTI2019

Ignition, Flame Propagation, and End-Gas Autoignition Studies of Natural Gas/EGR Blends in a Rapid Compression Machine

The development of high efficiency, spark ignited natural gas engines is currently limited by engine knock at high power density (at high compression ratio and/or elevated boost pressures) and misfire (at lean conditions and/or high exhaust gas recirculation levels). The knock and misfire limits are further confounded by the wide variety in fuel reactivity observed in “pipeline quality” natural gas. In this study, a rapid compression machine (RCM) was used to characterize the effects of variation in natural gas fuel reactivity and exhaust gas recirculation (EGR) on homogeneous ignition delay, flame propagation rate and end-gas autoignition (EGAI) propensity for stoichiometric natural gas/oxidizer/EGR blends. Pipeline quality natural gas with variable reactivity (68 < Methane Number < 95) was simulated using mixtures of methane, ethane, and propane. EGR was simulated with mixtures of Ar, CO2, CO, and NO. EGR substitution rates were varied from 0 to 30 mass percent. Ignition delay period under homogeneous autoignition conditions was measured at compressed pressures of 24.0 to 33.1 bar and compressed temperatures of 667 to 980 K. Flame propagation rate and EGAI propensity was measured at spark-ignition pressures of 29.9 to 32.9 bar and temperatures of 721 to 782 K.

Ignition Delay, Flame Propagation Rate, Rapid Comp↗
DOE OSTI2024

Physical Properties of Hilti HIT-RE 500 V3 After Irradiation: Slant Shear, Tensile, Flexural, and Compressive

There are various applications in which epoxy adhesives may be used within hot-cell environments. These epoxies currently see limited use within hot cells since it is known that organics see degradation after small doses even as low as 50 kilogray (kGy). These losses in physical property strengths limit the use of these epoxies to non-structural applications. In modern construction, however, the use of epoxies to bond structural components such as rebar or threaded anchors is becoming increasingly prevalent. To employ these types of materials the Idaho National Laboratory (INL) has begun investigating the specific degradation properties of epoxies for use in structural applications in environments where radiation is present. Hilti HIT-RE 500 V3 is used extensively in new construction and renovation projects across the world. The INL has conducted various tests on this epoxy for low dose environments. These tests include tensile, flexural, compression, and slant shear tests following the American Society for Testing Material International (ASTM) standards D638, D790, D695, and C882/882M respectively. Two sample sets for each test were created where the baseline specimens were not irradiated, and another set was irradiated to an accumulated dose of approximately 50-60 kGy. All the samples were destructively tested and analyzed focusing on the change in physical properties, examples of these tests are shown in Figures 1-4. Tensile testing results indicate a 0.9% loss in maximum load capacity, a 0.5% loss in tensile stress at maximum load, a 1.4% loss in tensile strain at break, and a 15% decrease in modulus of elasticity. Flexural testing results display an increase in all the following: 12% in strain at maximum load, 10% in maximum load capacity, 5% in stress at maximum load, and 3% in young’s modulus. The compressive physical properties after irradiation display a 1% increase in maximum load, a 3% decrease in stress at yield, and a 5% decrease in modulus of elasticity. The maximum compressive stress saw no measurable change after irradiation. The slant shear specimens after irradiation displayed a 2% increase in maximum load capacity and maximum compressive stress. Though a structural analysis would have to be completed as is normal for building design the increases and decreases in the measured physical properties indicate that this material may be used for structural applications in low dose hot-cell environments without adhesive failure.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Multilevel techniques for compression and reduction of scientific data—the univariate case

We present a multilevel technique for the compression and reduction of univariate data and give an optimal complexity algorithm for its implementation. A hierarchical scheme offers the flexibility to produce multiple levels of partial decompression of the data so that each user can work with a reduced representation that requires minimal storage whilst achieving the required level of tolerance. The algorithm is applied to the case of turbulence modelling in which the datasets are traditionally not only extremely large but inherently non-smooth and, as such, rather resistant to compression. Here, we decompress the data for a range of relative errors, carry out the usual analysis procedures for turbulent data, and compare the results of the analysis on the reduced datasets to the results that would be obtained on the full dataset. The results obtained demonstrate the promise of multilevel compression techniques for the reduction of data arising from large scale simulations of complex phenomena such as turbulence modelling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Signal Recovery and System Calibration from Multiple Compressive Poisson Measurements

The measurement matrix employed in compressive sensing typically cannot be known precisely a priori and must be estimated via calibration. One may take multiple compressive measurements, from which the measurement matrix and underlying signals may be estimated jointly. This is of interest as well when the measurement matrix may change as a function of the details of what is measured. This problem has been considered recently for Gaussian measurement noise, and here we develop this idea with application to Poisson systems. A collaborative maximum likelihood algorithm and alternating proximal gradient algorithm are proposed, and associated theoretical performance guarantees are established based on newly derived concentration-of-measure results. A Bayesian model is then introduced, to improve flexibility and generality. Connections between the maximum likelihood methods and the Bayesian model are developed, and example results are presented for a real compressive X-ray imaging system.

Bayesian compressive sensing↗
DOE OSTI2018

Compressive Properties and Energy Absorption of Aluminum Foams with a Wide Range of Relative Densities

Quasi-static uniaxial compressive experiments were conducted on aluminum foams with a wide range of relative densities (0.134-0.472). The compressive properties and energy absorption capacity were systematically characterized and compared in a more suitable way. The compressive stress instead of compressive strain achieved during energy absorption process was taken into consideration. The results show that aluminum foam is not a kind of energy absorption materials with a stationary plateau region at the plastic deformation stage. There exists a strain hardening phenomenon which makes the stress–strain curve incline at this stage. For every aluminum foam with certain relative density, there exists an optimal stress. Under its optimal stress condition, the foam can absorb the maximum energy compared to foams with whatever different relative densities. The optimal stress and corresponding maximum energy absorption capacity increase with the increase in the foam’s relative density.

36 MATERIALS SCIENCE↗