Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data 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.

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

At least 487 records · Page 27

Effect of Carbon on the Volume of Solid Iron at High Pressure: Implications for Carbon Substitution in Iron Structures and Carbon Content in the Earth’s Inner Core

Understanding the effect of carbon on the density of hcp (hexagonal-close-packed) Fe-C alloys is essential for modeling the carbon content in the Earth’s inner core. Previous studies have focused on the equations of state of iron carbides that may not be applicable to the solid inner core that may incorporate carbon as dissolved carbon in metallic iron. Carbon substitution in hcp-Fe and its effect on the density have never been experimentally studied. We investigated the compression behavior of Fe-C alloys with 0.31 and 1.37 wt % carbon, along with pure iron as a reference, by in-situ X-ray diffraction measurements up to 135 GPa for pure Fe, and 87 GPa for Fe-0.31C and 109 GPa for Fe-1.37C. The results show that the incorporation of carbon in hcp-Fe leads to the expansion of the lattice, contrary to the known effect in body-centered cubic (bcc)-Fe, suggesting a change in the substitution mechanism or local environment. The data on axial compressibility suggest that increasing carbon content could enhance seismic anisotropy in the Earth’s inner core. The new thermoelastic parameters allow us to develop a thermoelastic model to estimate the carbon content in the inner core when carbon is incorporated as dissolved carbon hcp-Fe. The required carbon contents to explain the density deficit of Earth’s inner core are 1.30 and 0.43 wt % at inner core boundary temperatures of 5000 K and 7000 K, respectively.

58 GEOSCIENCES↗

X-Ray Reflectometry of DMPS Monolayers on a Water Substrate

The molecular structure of dimyristoyl phosphatidylserine (DMPS) monolayers on a water substrate in different phase states has been investigated by X-ray reflectometry with a photon energy of ~8 keV. According to the experimental data, the transition from a two-dimensional expanded liquid state to a solid gel state (liquid crystal) accompanied by the ordering of the hydrocarbon tails C{sub 14}H{sub 27} of the DMPS molecule occurs in the monolayer as the surface pressure rises. The monolayer thickness is 20 ± 3 and 28 ± 2 Å in the liquid and solid phases, respectively, with the deflection angle of the molecular tail axis from the normal to the surface in the gel phase being 26° ± 8°. At least a twofold decrease in the degree of hydration of the polar lipid groups also occurs under two-dimensional monolayer compression. The reflectometry data have been analyzed using two approaches: under the assumption about the presence of two layers with different electron densities in the monolayer and without any assumptions about the transverse surface structure. Both approaches demonstrate satisfactory agreement between themselves in describing the experimental results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optimizing Management of Persistent Data Structures in High-Performance Analytics

Large-scale data analytics workflows ingest massive input data into various data structures, including graphs and key-value datastores. These data structures undergo multiple transformations and computations and are typically reused in incremental and iterative analytics workflows. Persisting in-memory views of these data structures enables reusing them beyond the scope of a single program run while avoiding repetitive raw data ingestion overheads. Memory-mapped I/O enables persisting in-memory data structures without data serialization and deserialization overheads. However, memory-mapped I/O lacks the key feature of persisting consistent snapshots of these data structures for incremental ingestion and processing. The obstacles to efficient virtual memory snapshots using memory-mapped I/O include background writebacks outside the application’s control, and the significantly high storage footprint of such snapshots. To address these limitations, we present Privateer, a memory and storage management tool that enables storage-efficient virtual memory snapshotting while also optimizing snapshot I/O performance. Here, we integrated Privateer into Metall, a state-of-the-art persistent memory allocator for C++, and the Lightning Memory-Mapped Database (LMDB), a widely-used key-value datastore in data analytics and machine learning. Privateer optimized application performance by 1.22× when storing data structure snapshots to node-local storage, and up to 16.7× when storing snapshots to a parallel file system. Privateer also optimizes storage efficiency of incremental data structure snapshots by up to 11× using data deduplication and compression.

Computer science↗

A surprising proliferation of detwinning in β -tin at extreme loading rates

Integrating data from dynamic compression experiments of condensed matter across three national laboratories has led to insight and quantitative calibration of materials strength over decades of loading rate. For many materials, a single strength model (such as PTW) is sufficient to capture the flow-stress strain rate relationship which is monotonic. Here, we show here that β -tin, a tetragonal metal, exhibits dramatic deviations from this behavior. Naive fitting to a single PTW model is insufficient to capture the behavior; indeed, such resulting inferred flow stress versus strain exhibits a non-monotonic behavior. We suggest a resolution to this by proposing that in β -tin there are important Bauschinger effects arising from favorable conditions for twinning and detwinning. A simple yield surface model when paired with PTW hardening captures the experimental data.

36 MATERIALS SCIENCE↗

Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite

The analysis of connected data is an increasingly important application in high-performance computing. Such analyses can reveal fraudulent patterns in financial transactions, optimize telecommunications networks, predict information flow in social networks, etc. However, the landscape of graph analytics is highly diverse. Graph algorithms stress processor architectures differently, and no one graph can represent all topologies. Consequently, no single approach or framework is expected to be optimal for all graph analytics problems. To help make sense of this diverse landscape, we evaluated four approaches to graph analytics: GraphBLAS, Galois, BGL17, GraphIt; and compare them against hand-tuned implementations that take advantage of hardware features on our test platform. Graph- BLAS formulates graph analytics as sparse linear algebra. Galois provides syntactic constructs for data parallelism over irregular data structures. BGL17 is a generic C++ template library for implementing graph algorithms. GraphIt provides a domain- specific language to describe and optimize graph algorithms. We use the GAP Benchmark Suite to establish baseline performance and guide the side-by-side evaluation of each framework. GAP consists of 30 tests: six graph analytics algorithms (breadth- first search, single-source shortest path, PageRank, betweenness centrality, connected components, and triangle counting) run on five graphs, each with different topological characteristics (e.g., high diameter, skewed degree distribution, high average degree). High-performance reference implementations are included for each benchmark algorithm. Because a graph can be loaded into memory a number of ways (e.g., flat file on disk, compressed sparse format, data frames, retrieved from SQL or NoSQL databases), our evaluation focused on computational performance rather than I/O. Our results show the relative strengths of each framework.

Graph algorithms, Benchmarking, shared-memory prog↗

High-performance data format for scientific data storage and analysis

Here, in this article, we present the High-Performance Output (HiPO) data format developed at Jefferson Laboratory for storing and analyzing data from Nuclear Physics experiments. The format was designed to efficiently store large amounts of experimental data, utilizing modern fast compression algorithms. The purpose of this development was to provide organized data in the output, facilitating access to relevant information within the large data files. The HiPO data format has features that are suited for storing raw detector data, reconstruction data, and the final physics analysis data efficiently, eliminating the need to do data conversions through the lifecycle of experimental data. The HiPO data format is implemented in C++ and JAVA, and provides bindings to FORTRAN, Python, and Julia, providing users with the choice of data analysis frameworks to use. In this paper, we will present the general design and functionalities of the HiPO library and compare the performance of the library with more established data formats used in data analysis in High Energy and Nuclear Physics (such as ROOT and Parquete). In columnar data analysis, HiPO surpasses established data formats in performance and can be effectively applied to data analysis in other scientific fields.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Calibrating the SPECTACULAR constitutive model using legacy Sandia data for two filled epoxy systems: 828/CTBN/DEA/GMB and 828/DEA/GMB

The SPECTACULAR model is a development extension of the Simplified Potential Energy Clock (SPEC) model. Both models are nonlinear viscoelastic constitutive models used to predict a wide range of time-dependent behaviors in epoxies and other glass-forming materials. This report documents the procedures used to generate SPECTACULAR calibrations for two particulate-filled epoxy systems, 828/CTBN/DEA/GMB and 828/DEA/GMB. No previous SPECTACULAR or SPEC calibration exists for 828/CTBN/DEA/GMB, while a legacy SPEC calibration exists for 828/DEA/GMB. To generate the SPECTACULAR calibrations, a step-by-step procedure was executed to determine parameters in groups with minimal coupling between parameter groups. This procedure has often been deployed to calibrate SPEC, therefore the resulting SPECTACULAR calibration is backwards compatible with SPEC (i.e. none of the extensions specific to SPECTACULAR are used). The calibration procedure used legacy Sandia experimental data stored on the Polymer Properties Database website. The experiments used for calibration included shear master curves, isofrequency temperature sweeps under oscillatory shear, the bulk modulus at room temperature, the thermal strain during a temperature sweep, and compression through yield at multiple temperatures below the glass transition temperature. Overall, the calibrated models fit the experimental data remarkably well. However, the glassy shear modulus varies depending on the experiment used to calibrate it. For instance, the shear master curve, isofrequency temperature sweep under oscillatory shear, and the Young's modulus in glassy compression yield values for the glassy shear modulus at the reference temperature that vary by as much as 15 %. Also, for 828/CTBN/DEA/GMB, the temperature dependence of the glassy shear modulus when fit to the Young's modulus at different temperatures is approximately four times larger than when it is determined from the isofrequency temperature sweep under oscillatory shear. For 828/DEA/GMB, the temperature dependence of the shear modulus determined from the isofrequency temperature sweep under oscillatory shear accurately predicts the Young's modulus at different temperatures. When choosing values for the shear modulus, fitting the glassy compression data was prioritized. The new and legacy calibrations for 828/DEA/GMB are similar and appear to have been calibrated from the same data. However, the new calibration improves the fit to the thermal strain data. In addition to the standard calibrations, development calibrations were produced that take advantage of development features of SPECTACULAR , including an updated equilibrium Helmholtz free energy that eliminates undesirable behavior found in previous work. In addition to the previously mentioned experimental data, the development calibrations require data for the heat capacity during a stress-free temperature sweep to calibrate thermal terms.

36 MATERIALS SCIENCE↗

Characterization of Oxy-combustion Impacts in Existing Coal-fired Boilers

Reaction Engineering International (REI) managed a team of experts from University of Utah, Siemens Energy, Praxair, Vattenfall AB, Sandia National Laboratories, Brigham Young University (BYU) and Corrosion Management Ltd. to perform multi-scale experiments, coupled with mechanism development, process modeling and CFD modeling, for both applied and fundamental investigations. The primary objective of this program was to acquire data and develop tools to characterize and predict impacts of CO{sub 2} flue gas recycle and burner feed design on flame characteristics (burnout, NO{sub x}, SO{sub x}, mercury and fine particle emissions, heat transfer) and operational concerns (fouling, slagging and corrosion) inherent in the retrofit of existing coal-fired boilers for oxy-coal combustion. Experimental work was conducted at Sandia National Laboratories’ Entrained Flow Reactor, the University of Utah Industrial Combustion Research Facility, and Brigham Young University. Process modeling and computational fluid dynamics (CFD) modeling was performed at REI. Successful completion of the project objectives resulted in the following key deliverables: 1) Multi-scale test data from 0.1 kW bench-scale, 100 kW and 200 kW laboratory-scale, and 1 MW semi-industrial scale combustors that describe differences in flame characteristics, fouling, slagging and corrosion for coal combustion under air-firing and oxygen-firing conditions, including sensitivity to oxy-burner design and flue gas recycle composition. 2) Validated mechanisms developed from test data that describe fouling, slagging, waterwall corrosion, heat transfer, char burnout and sooting under coal oxy-combustion conditions. The mechanisms were presented in a form suitable for inclusion in CFD models or process models. 3) Principles to guide design of pilot-scale and full-scale coal oxy-firing systems and flue gas recycle configurations, such that boiler operational impacts from oxy-combustion retrofits are minimized. 4) Assessment of oxy-combustion impacts in two full-scale coal-fired utility boiler retrofits based on computational fluid dynamics (CFD) modeling of air-fired and oxygen-fired operation. This research determined that it is technically feasible to retrofit the combustion system in an air-fired boiler for oxy-fired operation. The impacts of CO{sub 2} flue gas recycle and burner design on flame characteristics (burnout, NO{sub x}, SO{sub x}, mercury and fine particle emissions, heat transfer) and operational concerns (fouling, slagging and corrosion) were minimal, with the exception of high sulfur levels resulting from untreated flue gas recycle with medium and high-sulfur coals. This work focused on combustion in the radiant and convective sections of the boiler and did not address boiler system integration issues, plant efficiencies, impacts on downstream air pollution control devices, or CO{sub 2} capture and compression. The experimental data, oxy-firing system principles and oxy-combustion process mechanisms provided by this work can be used by electric utilities, boiler OEMs, equipment suppliers, design firms, software vendors, consultants and government agencies to assess retrofit applications of oxy-combustion technologies to existing boilers and to guide development of new designs.

20 FOSSIL-FUELED POWER PLANTS↗

Phase transitions and photoinduced transformations at high pressure in the molecular donor-acceptor fullerene complex (Cd(dedtc){sub 2}){sub 2} · C{sub 60}

The Raman spectra of crystals of C{sub 60} fullerene-cadmium diethyldithiocarbamate molecular donor-acceptor complexes (Cd(dedtc){sub 2}){sub 2} · C{sub 60} were measured at pressures of up to 17 GPa, and the crystal lattice parameters of these complexes were determined at pressures of up to 6 GPa. An increase in pressure up to ∼2 GPa leads to changes in the Raman spectra, which are manifested by splitting of the intramolecular H{sub g}(1)-H{sub g}(8) phonon modes and by softening of the A{sub g}(2) mode of the C{sub 60} molecule. A further increase in pressure up to 17 GPa does not induce significant new changes to the Raman spectra, while a decrease is accompanied by the reverse transformation at a pressure of about 2 GPa. The pressure dependence of the lattice parameters also exhibits a reversible feature at 2 GPa related to a jumplike decrease in compressibility. All these data are indicative of a phase transition in the vicinity of 2 GPa related to the formation of covalent bonds between C{sub 60} molecules and, probably, the appearance of C{sub 120} dimers in fullerene layers. It was also found that, in the pressure interval from 2 to 6.3 GPa, the Raman spectra of complexes exhibit photoinduced transformations under prolonged exposure to laser radiation with a wavelength of λ = 532 nm and power density up to 5000 W/cm{sup 2}. These changes are manifested by splitting and softening of the A{sub g}(2) mode and resemble analogous changes accompanying the photopolymerization of C{sub 60} fullerene. The intensity of new bands exhibits exponential growth with increasing exposure time. The photopolymer yield depends on both the laser radiation power and external pressure. The A{sub g}(2) mode splitting under irradiation can be related to the formation of photo-oligomers with various numbers of intermolecular covalent bonds per C{sub 60} molecule.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

G-mode magnetic force microscopy: Separating magnetic and electrostatic interactions using big data analytics

In this work, we develop a full information capture approach for Magnetic Force Microscopy (MFM), referred to as generalized mode (G-Mode) MFM. G-Mode MFM acquires and stores the full data stream from the photodetector, captured at sampling rates approaching the intrinsic photodiode limit. The data can be subsequently compressed, denoised, and analyzed, without information loss. Here, G-Mode MFM is implemented and compared to the traditional heterodyne-based MFM on model systems, including domain structures in ferromagnetic Yttrium Iron Garnet and the electronically and magnetically inhomogeneous high entropy alloy, CoFeMnNiSn. We investigate the use of information theory to mine the G-Mode MFM data and demonstrate its usefulness for extracting information which may be hidden in traditional MFM modes, including signatures of nonlinearities and mode-coupling phenomena. Finally, we demonstrate detection and separation of magnetic and electrostatic tip-sample interactions from a single G-Mode image, by analyzing the entire frequency response of the cantilever. G-Mode MFM is immediately implementable on any atomic force microscopy platform and as such is expected to be a useful technique for probing spatiotemporal cantilever dynamics and mapping material properties, as well as their mutual interactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Genetic algorithm optimization of a chemical kinetic mechanism for propane at engine relevant conditions

Propane has demonstrated significant potential for reductions in greenhouse gas and pollutant emissions in medium- and heavy-duty engine applications, but further improvements require accurate, compact, and scalable chemical kinetic mechanisms to design the next generation of propane fueled engines, particularly at the boosted operating conditions necessary to meet the power density demand of medium- and heavy-duty applications. In this work, six key chemical reactions were identified in a reduced mechanism with 70 species and 352 reactions through a sensitivity analysis performed at conditions typical of thermodynamic trajectories observed in a high compression ratio, long stroke engine operated on propane from throttled to boosted operating conditions. While the original mechanism was validated against rapid compression machine (RCM) data, it was found to overpredict experimental autoignition tendencies in 2-zone, 0-D SI engine simulations performed in Chemkin Pro. Subsequently, a genetic algorithm approach was used to optimize the six reaction rate parameters within established uncertainty bounds by performing RCM simulations and comparing to two independent sets of literature ignition delay times for propane, thus generating two new kinetic mechanisms. The first optimization achieved a mean absolute percent error (MPE) reduction in 2nd stage ignition delay of 61.4% in seven generations, while the second optimization utilized a newer experimental RCM dataset, and achieved MPE reduction of 56.7% in seven generations, and further marginal improvement to 57.8% reduction in 34 generations. Finally, the two mechanisms were then evaluated again in the 2-zone 0-D SI engine model in Chemkin Pro comparing typical mean and knocking cycle trajectories, and it was found that the second optimized mechanism provided better prediction of knock onset at the representative conditions evaluated in this work, particularly for higher load operating conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advanced Polymer Characterization: Modular Operations for Spectral Alignment by Iterative Compression (MOSAIC)

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry encodes structural information across diverse homo- and copolymer ensembles, yet decrypting these spectra requires a systematic analytical approach. We introduce Modular Operations for Spectral Alignment by Iterative Compression (MOSAIC)─a general cipher algorithm that applies modular arithmetic to filter monomer-derived mass contributions and cluster MALDI peaks by nonconstitutional repeating units (non-CRUs). MOSAIC performs sequential modular operations using monomer mass differences as base units to compress complex spectral data, revealing end-group distributions and comonomer incorporation. As a demonstration, we applied MOSAIC to five copolymers formed by two different polymerization mechanisms. Furthermore, the resulting remainder–mass plots clearly resolve polymer homologs with distinct non-CRUs into visually apparent clusters, enabling intuitive assignment of mass spectral features.

Wang, Hanlin M. [University of Illinois at Urbana−↗

Investigation of oxygen self-diffusion in PuO 2 by combining molecular dynamics with thermodynamic calculations

In the present work, the defect properties of oxygen self-diffusion in PuO 2 are investigated over a wide temperature (300–1900 K) and pressure (0–10 GPa) range, by combining molecular dynamics simulations and thermodynamic calculations. Based on the well-established cBΩ thermodynamic model which connects the activation Gibbs free energy of diffusion with the bulk elastic and expansion properties, various point defect parameters such as activation enthalpy, activation entropy, and activation volume were calculated as a function of T and P. Molecular dynamics calculations provided the necessary bulk properties for the proper implementation of the thermodynamic model, in the lack of any relevant experimental data. The estimated compressibility and the thermal expansion coefficient of activation volume are found to be more than one order of magnitude greater than the corresponding values of the bulk plutonia. As a result, the diffusion mechanism is discussed in the context of the temperature and pressure dependence of the activation volume.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Simultaneous compression of NaCl, Au, and ruby: toward mutually consistent pressure scales

Here, we evaluate pressure consistency of equations of state (EOS) for NaCl and Au at 300 K. The simultaneous measurements of unit-cell volumes (V) with ruby R1 line shifts (Δλ) in a helium (He) loaded diamond cell effectively remove potential systematic errors. Compression and decompression data were automatically collected at 1 sec interval, yielding a dense dataset with >8,000 (V, Δλ) pairs each for NaCl and Au. Solidification of He has noticeable effects on both V and Delta lambda (hence P). Only data up to similar to 14 GPa, or 6000 (V, P) pairs, can be considered hydrostatic within the resolution. The P-V data are fitted to the Rydberg-Vinet and the 3 rd order Birch-Murnaghan EOS. Predicted pressures of these EOSs agree with those given by the Ruby2020 ruby scale to within +/- 0.05 GPa. Overall, pressures predicted by the Rydberg-Vinet EOS are in better agreement with the average of commonly used NaCl and Au pressure scales.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

CARMA MEASUREMENTS OF THE SUNYAEV-ZEL'DOVICH EFFECT IN RX J1347.5-1145

We demonstrate the Sunyaev-Zel'dovich (SZ) effect imaging capabilities of the Combined Array for Research in Millimeter-wave Astronomy (CARMA) by presenting an SZ map of the galaxy cluster RX J1347.5-1145. By combining data from multiple CARMA bands and configurations, we are able to capture the structure of this cluster over a wide range of angular scales, from its bulk properties to its core morphology. We find that roughly 9% of this cluster's thermal energy is associated with sub-arcminute-scale structure imparted by a merger, illustrating the value of high-resolution SZ measurements for pursuing cluster astrophysics and for understanding the scatter in SZ scaling relations. We also find that the cluster's SZ signal is lower in amplitude than suggested by a spherically symmetric model derived from X-ray data, consistent with compression along the line of sight relative to the plane of the sky. Finally, we discuss the impact of upgrades currently in progress that will further enhance CARMA's power as an SZ imaging instrument.

79 ASTRONOMY AND ASTROPHYSICS↗

In situ synchrotron diffraction of pressure-induced phase transition in DyPO 4 under variable hydrostaticity

In situ synchrotron x-ray diffraction was conducted on polycrystalline DyPO 4 to elucidate the details of the pressure-induced transition from the xenotime polymorph to the monazite polymorph. We used three different pressure-transmitting media (neon, a 16:3:1 methanol-ethanol-water mixture, and potassium chloride) to investigate the effect of hydrostaticity on the phase behavior. Specifically, our data clearly show a hydrostatic onset pressure of the xenotime-monazite transition of 9.1 GPa, considerably lower than the 15.3 GPa previously determined by Raman spectroscopy. Based on (quasi)hydrostatic data taken in a neon environment, third-order Birch-Murnaghan equation-of-state fits give a xenotime bulk modulus of 144 GPa and a monazite bulk modulus of 180 GPa (both with pressure derivatives of 4.0). Structural data and axial compressibilities show that DyPO 4 is sensitive to shear and has an anisotropic response to pressure. More highly deviatoric conditions cause the onset of the transition to shift to pressures at least as low as 7.0 GPa. We attribute early transition to shear-induced distortion of the PO4 tetrahedra. Finally, our characterization of the high-pressure behavior of DyPO 4 under variable hydrostaticity is critical for advancing rare earth orthophosphate fiber coating applications in ceramic matrix composites and may inform future tailoring of phase composition for controlled shear and pressure applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Model-independent versus model-dependent interpretation of the SDSS-III BOSS power spectrum: Bridging the divide

The traditional clustering analyses of galaxy redshift surveys compress the clustering data into a set of late-time physical variables in a model-independent way. This approach has recently been extended by an additional shape variable encoding early-time physics information. Here we apply this new technique, ShapeFit, to SDSS-III BOSS data and show that it matches the constraining power of alternative, model-dependent approaches, which directly constrain the model’s parameters adopting a cosmological model ab initio. ShapeFit is ~30 times faster, model independent, naturally splits early- and late-time variables, and enables a better control of observational systematics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗