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Results for “COMPRESSION RATIO”

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At least 271 records · Page 15

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DOE OSTI2023

Strong collisionless coupling between an unmagnetized driver plasma and a magnetized background plasma

Fast-exploding plasmas traveling though magnetized, collisionless plasmas can occur in a variety of physical systems, such as supernova remnants, coronal mass ejections, and laser-driven laboratory experiments. To study these systems, it is important to understand the coupling process between the plasmas. Here, in this work, we develop a semi-analytical model of the parameters that characterize the strong collisionless coupling between an unmagnetized driver plasma and a uniformly and perpendicularly magnetized background plasma. In particular, we derive analytical expressions that describe the characteristic diamagnetic cavity and magnetic compression of these systems, such as their corresponding velocities, the compression ratio, and the maximum size of the cavity. The semi-analytical model is compared with collisionless 1D particle-in-cell simulations and experimental results with laser-driven plasmas. The model allows us to provide bounds for parameters that are otherwise difficult to diagnose in experiments with similar setups.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Accuracy of Kohn–Sham density functional theory for warm- and hot-dense matter equation of state

We study the accuracy of Kohn–Sham density functional theory (DFT) for warm- and hot-dense matter (WDM and HDM). Specifically, considering a wide range of systems, we perform accurate ab initio molecular dynamics simulations with temperature-independent local/semilocal density functionals to determine the equations of state at compression ratios of 3x–7x and temperatures near 1 MK. We find very good agreement with path integral Monte Carlo benchmarks, while having significantly smaller error bars and smoother data, demonstrating the accuracy of DFT for the study of WDM and HDM at such conditions. In addition, using a Δ-machine learned force field scheme, we confirm that the DFT results are insensitive to the choice of exchange-correlation functional, whether local, semilocal, or nonlocal.

Suryanarayana, Phanish (ORCID:0000000151720049)↗

DOE OSTI2021

A robust plasma-based laser amplifier via stimulated Brillouin scattering

Brillouin amplification in plasma is more resilient to fluctuations in the laser and plasma parameters than Raman amplification, making it an attractive alternative to Raman amplification. In this work, we focus on high plasma densities, n 0 > n cr /4, where stimulated Raman scattering is not possible and laser beam filamentation is the dominant competing process. Through analytic theory and multi-dimensional particle-in-cell simulations, we identify a parameter regime for which Brillouin amplification can be efficient while maintaining filamentation of the probe at a controlled level. We demonstrate pump-to-probe compression ratios of up to 72 and peak amplified probe fluences over 1 kJ cm -2 with ≃50% efficiency. High pulse quality is maintained through control of parasitic filamentation, enabling operation at large beam diameters. Provided the pump and probe pulse diameters can be increased to 1 mm, our results suggest that Brillouin amplification can be used to produce sub-picosecond pulses of petawatt power.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

SnowPac : a multiscale cubic B-spline wavelet compressor for astronomical images

ABSTRACT As more advanced and complex survey telescopes are developed, the size and scale of data being captured grows at increasing rates. Across various domains, data compression through wavelets has enabled the reduction of data size and increase in computation efficiency. In this paper, we provide qualitative and quantitative tests of a new wavelet-based image compression method compared against the current standard for astronomical images. The analysis is improved by making use of state-of-the-art object detection systems to accurately measure the impact of the compression. We find that a combination of lossy wavelet-based methods, efficient quantization, and lossless dictionary compressors can preserve up to 98 per cent of astronomical objects at a 10:1 compression ratio. This significant reduction in file size also preserves astronomical object properties better than existing methods. These methods help further reduce future workloads for image-heavy processing pipelines.

Pulido, Jesus↗

DOE OSTI2020

Path integral Monte Carlo and density functional molecular dynamics simulations of warm dense MgSiO 3

In order to provide a comprehensive theoretical description of MgSiO 3 at extreme conditions, we combine results from path integral Monte Carlo and density functional molecular dynamics simulations and generate a consistent equation of state for this material. We consider a wide range of temperature and density conditions from 10 4 to 10 8 K and from 0.321 to 64.2 g/cm -3 (0.1- to 20-fold the ambient density). We study how the L and K shell electrons are ionized with increasing temperature and pressure. We derive the shock Hugoniot curve and compare with experimental results. Our Hugoniot curve is in good agreement with the experiments, and we predict a broad compression maximum that is dominated by the K shell ionization of all three nuclei while the peak compression ratio of 4.70 is obtained when the Si and Mg nuclei are ionized. To conclude, we analyze the heat capacity and structural properties of the liquid.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

Equation of state of boron nitride combining computation, modeling, and experiment

The equation of state (EOS) of materials at warm dense conditions poses significant challenges to both theory and experiment. We report a combined computational, modeling, and experimental investigation leveraging new theoretical and experimental capabilities to investigate warm-dense boron nitride (BN). The simulation methodologies include path integral Monte Carlo (PIMC), several density functional theory (DFT) molecular dynamics methods [plane-wave pseudopotential, Fermi operator expansion (FOE), and spectral quadrature (SQ)], activity expansion (actex), and all-electron Green's function Korringa-Kohn-Rostoker (mecca), and compute the pressure and internal energy of BN over a broad range of densities and temperatures. Our experiments were conducted at the Omega laser facility and the Hugoniot response of BN to unprecedented pressures (1200–2650 GPa). The EOSs computed using different methods cross validate one another in the warm-dense matter regime, and the experimental Hugoniot data are in good agreement with our theoretical predictions. By comparing the EOS results from different methods, we assess that the largest discrepancies between theoretical predictions are ≲ 4% in pressure and ≲ 3% in energy and occur at 10 6 K, slightly below the peak compression that corresponds to the K -shell ionization regime. At these conditions, we find remarkable consistency between the EOS from DFT calculations performed on different platforms and using different exchange-correlation functionals and those from PIMC using free-particle nodes. This provides strong evidence for the accuracy of both PIMC and DFT in the high-pressure, high-temperature regime. Moreover, the recently developed SQ and FOE methods produce EOS data that have significantly smaller statistical error bars than PIMC, and so represent significant advances for efficient computation at high temperatures. The shock Hugoniot predicted by PIMC, actex, and mecca shows a maximum compression ratio of 4.55 ± 0.05 for an initial density of 2.26 g/cm 3 , higher than the Thomas-Fermi predictions by about 5%. In addition, we construct tabular EOS models that are consistent with the first-principles simulations and the experimental data. Our findings clarify the ionic and electronic structure of BN over a broad range of temperatures and densities and quantify their roles in the EOS and properties of this material. The tabular models may be utilized for future simulations of laser-driven experiments that include BN as a candidate ablator material.

36 MATERIALS SCIENCE↗

DOE OSTI2022

First-principles equation of state of CHON resin for inertial confinement fusion applications

A wide-range (0 to 1044.0 g/ cm 3 and 0 to 10 9 K) equation-of-state (EOS) table for a CH 1.72 O 0.37 N 0.086 quaternary compound has been constructed based on density-functional theory (DFT) molecular-dynamics (MD) calculations using a combination of Kohn-Sham DFT MD, orbital-free DFT MD, and numerical extrapolation. The first-principles EOS data are compared with predictions of simple models, including the fully ionized ideal gas and the Fermi-degenerate electron gas models, to chart their temperature-density conditions of applicability. The shock Hugoniot, thermodynamic properties, and bulk sound velocities are predicted based on the EOS table and compared to those of C-H compounds. The Hugoniot results show the maximum compression ratio of the C-H-O-N resin is larger than that of CH polystyrene due to the existence of oxygen and nitrogen; while the other properties are similar between CHON and CH. Radiation hydrodynamic simulations have been performed using the table for inertial confinement fusion targets with a CHON ablator and compared with a similar design with CH. Here, the simulations show CHON outperforms CH as the ablator for laser-direct-drive target designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2018

High-Performance Indirect-Drive Cryogenic Implosions at High Adiabat on the National Ignition Facility

To reach the pressures and densities required for ignition, it may be necessary to develop an approach to design that makes it easier for simulations to guide experiments. Here, we report on a new short-pulse inertial confinement fusion platform that is specifically designed to be more predictable. Furthermore, the platform has demonstrated 99%+0.5% laser coupling into the hohlraum, high implosion velocity (411 km/s), high hotspot pressure (220+60 Gbar), and high cold fuel areal density compression ratio (>400), while maintaining controlled implosion symmetry, providing a promising new physics platform to study ignition physics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Dynamical Sketching for Enhanced Communication Efficiency in Federated Learning

Federated learning (FL) has revolutionized distributed machine learning by enabling collaborative model training without sharing local data. However, communication efficiency and privacy guarantees remain significant challenges. This paper introduces a dynamic sketching mechanism in FL, optimizing the trade-off between communication efficiency and model accuracy. By dynamically selecting the sketch matrix size, our approach adapts to the evolving characteristics of the data and the model, ensuring optimal performance across diverse scenarios. We leverage Bayesian optimization to systematically tune the sketch parameters, achieving an effective balance between resource efficiency and model performance. Experimental results on the MNIST dataset using a convolutional neural network (CNN) architecture validate the proposed method's efficiency and scalability. Our dynamic sketching approach significantly outperforms fixed-size sketching techniques, achieving higher compression ratios (up to 62x) and providing better privacy guarantees while maintaining high model accuracy. These findings highlight the robustness and versatility of our approach and make it a valuable solution for privacy-preserving, communication-efficient federated learning.

Afrose, Sharmin [ORNL]↗

DOE OSTI2021

Optimizing Error-Bounded Lossy Compression for Scientific Data by Dynamic Spline Interpolation

Today's scientific simulations are producing vast volumes of data that cannot be stored and transferred efficiently because of limited storage capacity, parallel I/O bandwidth, and network bandwidth. The situation is getting worse over time because of the ever-increasing gap between relatively slow data transfer speed and fast-growing computation power in modern supercomputers. Error-bounded lossy compression is becoming one of the most critical techniques for resolving the big scientific data issue, in that it can significantly reduce the scientific data volume while guaranteeing that the reconstructed data is valid for users because of its compression-error-bounding feature. In this paper, we present a novel error-bounded lossy compressor based on a state-of-the-art prediction-based compression framework. Our solution exhibits substantially better compression quality than all of the existing error-bounded lossy compressors, with comparable compression speed. Specifically, our contribution is threefold. (1) We provide an in-depth analysis of why the best-existing prediction-based lossy compressor can only minimally improve the compression quality. (2) We propose a dynamic spline interpolation approach with a series of optimization strategies that can significantly improve the data prediction accuracy, substantially improving the compression quality in turn. (3) We perform a thorough evaluation using six real-world scientific simulation datasets across different science domains to evaluate our solution vs. all other related works. Experiments show that the compression ratio of our solution is higher than that of the second-best lossy compressor by 20%similar to 460% with the same error bound in most of the cases.

Zhao, Kai↗

DOE OSTI2020

Efficient I/O for Neural Network Training with Compressed Data

FanStore is a shared object store that enables efficient and scalable neural network training on supercomputers. By providing a global cache layer on node-local burst buffers using a compressed representation, it significantly enhances the processing capability of deep learning (DL) applications on existing hardware. In addition, FanStore allows POSIX-compliant file access to the compressed data in user space. We investigate the tradeoff between runtime overhead and data compression ratio using real-world datasets and applications, and propose a compressor selection algorithm to maximize storage capacity given performance constraints. We consider both asynchronous (i.e., with prefetching) and synchronous I/O strategies, and propose mechanisms for selecting compressors for both approaches. Using FanStore, the same storage hardware can host 2-13x more data for example applications without significant runtime overhead. Empirically, our experiments show that FanStore scales to 512 compute nodes with near linear performance scalability.

Zhang, Zhao↗

DOE OSTI2021

Joint Matrix Completion and Compressed Sensing for State Estimation in Low-observable Distribution System

Limited measurement availability at the distribution grid presents challenges for state estimation and situational awareness. This paper combines the advantages of two sparsity-based state estimation approaches (matrix completion and compressive sensing) that have been proposed recently to address the challenge of unobservability. The proposed approach exploits both the low rank structure and a suitable transform domain representation to leverage the correlation structure of the spatio-temporal data matrix while incorporating the powerflow constraints of the distribution grid. Simulations are carried out on three phase unbalanced IEEE 37 test system to verify the effectiveness of the proposed approach. The performance results reveal - (1) the superiority over traditional matrix completion and (2) very low state estimation errors for high compression ratios representing very low observability.

Dahale, Shweta↗

DOE OSTI2022

NSTX-U Machine Core Vacuum Seals Upgrade Design

The vacuum in the National Spherical Torus Experiment Upgrade (NSTX-U) is in the range of 2.66x10⁻⁶ Pa (2x 10⁻⁸ torr). To enhance vacuum seals and lower gas permeation in the NSTX-U and therefore ensuring operation safety and quality, the machine core vacuum seal design has been upgraded using double elastomeric seals and pumped interspaces (guard channels). In NSTX-U machine core, there are six major vacuum seals, including upper and lower vacuum vessel main flanges, upper and lower bellows flanges, and two in the ceramic isolation ring assembly that are mounted to the upper vacuum vessel main flange. The elastomeric seals are commercially available and customized fluorocarbon (Viton) O-rings. To ensure appropriate O-ring compression ratios for the vacuum seal, the O-ring grooves are customized with appropriate tolerances considering specific situations for each seal. In this upgrade, the vacuum in each interspace is designed to reach 13.33 Pa (0.1 torr), thus the overall pressure difference crossing each double O-ring seal is expected to be reduced by at least three orders of magnitude, and accordingly the overall rates of leakage and permeation will be lowered by three orders of magnitude. The corresponding pump-down times for each seal, at room temperature, are estimated at about 60 s. Additionally, the vacuum pumped interspaces will be able to function as a real-time leak monitor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Initial Results on a New Light-Duty 2.7-L Opposed-Piston Gasoline Compression Ignition Multi-Cylinder Engine

Abstract Gasoline compression ignition (GCI) is a cost-effective approach to achieving diesel-like efficiencies with low emissions. The fundamental architecture of the two-stroke Achates Power Opposed-Piston (OP) Engine enables GCI by decoupling piston motion from cylinder scavenging, allowing for flexible and independent control of cylinder residual fraction and temperature leading to improved low-load combustion. In addition, the high peak cylinder pressure and noise challenges at high-load operation are mitigated by the lower brake mean effective pressure (BMEP) operation and faster heat release for the same pressure rise rate of the OP Engine. These advantages further solidify the performance benefits of the OP Engine and demonstrate the near-term feasibility of advanced combustion technologies, enabled by the opposed-piston architecture. This paper presents initial results from steady-state testing on a brand new 2.7-L OP GCI multi-cylinder engine (MCE) designed for light-duty truck applications. Successful GCI operation calls for a high compression ratio (CR), leading to higher combustion stability at low loads, higher efficiencies, and lower cycle HC + NOX emissions. Initial results show a cycle average brake thermal efficiency (BTE) of 31.7%, which is already greater than 11% conventional engines, after only ten weeks of testing. Emissions results suggest that Tier 3 Bin 160 levels can be achieved using a traditional diesel after-treatment system. Combustion noise was well controlled at or below the United States Council for Automotive Research limits. In addition, initial results on catalyst light-off mode with GCI are also presented.

Energy & Fuels↗

DOE OSTI2018

Prediction of Cyclic Variability and Knock-Limited Spark Advance (KLSA) in Spark-Ignition (SI) Engine

Engine knock remains one of the major barriers to further improve thermal efficiency of Spark Ignition (SI) engines. Knock can be suppressed by lowering the compression ratio, or retarding the spark ignition timing, however, at an expense of efficiency penalty. SI engine is usually operated at knock-limited spark advance (KLSA) to achieve possibly maximum efficiency with given engine hardware and fuel properties, such as Research Octane Number (RON), Motor Octane Number (MON), and heat of vaporization, etc. Co-optimization of engine design and fuel properties is promising to improve the engine efficiency and predictive CFD models can be used to facilitate this optimization process. However, difficulties exist in predicting KLSA in CFD simulations. First, cyclic variability of SI engine demands that multi-cycle results are required to capture the extreme conditions. Secondly, Mach Courant-Friedrichs-Lewy (CFL) number of 1 is desired to accurately predict the knock intensity (KI), resulting in unaffordable computational cost, especially for multi-cycle simulations. In this study, a new approach to numerically predict KLSA using large Mach CFL number of 50 is proposed. This approach is validated against experimental data for a boosted Direct Injection Spark Ignition (DISI) engine at multiple loads and spark timings. G-equation combustion model coupled with well-mixed chemical kinetic model are used to predict the turbulent flame propagation and end-gas auto-ignition, respectively. Simulations run for 10 consecutive engine cycles at each condition. The results show good agreement between model predictions and experiments in terms of cylinder pressure, combustion phasing and cyclic variation. Engine knock is predicted with early spark ignition timing, indicated by significant pressure wave oscillation and end-gas heat release. Maximum Amplitude of Pressure Oscillation (MAPO) analysis is performed to quantify the KI, and the slope change point in KI extrema is used to indicate the KLSA accurately. Using a smaller Mach CFL number of 5 also results in the same conclusions thus demonstrating that this approach is insensitive to the Mach CFL number. The use of large Mach CFL number allows us to achieve fast turn-around time for multi-cycle engine CFD simulations.

Yue, Zongyu↗

DOE OSTI2023

Thermodynamic analysis of heat transfer reduction in spark ignition using thermal barrier coatings

This work uses a 0D thermodynamic engine model coupled to a 1D surface temperature solver to study the potential of low thermal inertia thermal barrier coatings (TBCs) on combustion chamber surfaces to increase the efficiency of spark ignition engines. Under ideal conditions, coating the piston crown, head, and valve faces with a TBC with a thermal inertia of 640 J/m 2 K s 1/2 resulted in less than a 1% relative improvement in efficiency. Despite using a low thermal inertia coating to avoid open cycle charge heating, the reduction in closed cycle heat transfer, which is the pathway to increasing efficiency, increased knock propensity. Therefore, any efficiency gain through closed cycle heat transfer reduction in spark ignition is offset by the need to retard spark timing to counter knock. An exergy analysis of completely blocking heat transfer for a 10 crank-angle degree window showed that on a low compression engine, like those used for stoichiometric gasoline spark ignition, the maximum efficiency gain achievable was limited compared to a higher compression ratio engine. Furthermore, the high gas temperatures of stoichiometric operation mean that even state-of-the-art TBCs cannot elevate surface temperatures enough purely through temperature swing to achieve a significant reduction in heat transfer near top dead center, where work availability is highest. Overall, these results indicate that low thermal inertia TBCs are ill-suited for achieving an efficiency benefit in spark ignition through a heat transfer reduction pathway. Instead spark ignition TBC research should explore ways to use low thermal inertia TBCs to achieve open cycle charge cooling to reduce knock propensity.

Engineering↗

DOE OSTI2017

Piston geometry effects in a light-duty, swirl-supported diesel engine: Flow structure characterization

This work studied how in-cylinder flow structure is affected in a light-duty, swirl-supported diesel engine when equipped with three different piston geometries: the first two featuring a conventional re-entrant bowl, either with or without valve cut-outs on the piston surface and the third featuring a stepped-lip bowl. Particle image velocimetry experiments were conducted inside an optical engine to measure swirl vortex intensity and structure during the intake and compression strokes. A full computational model of the optical diesel engine was built using the FRESCO code, a recently developed object-oriented parallel computational fluid dynamics platform for engine simulations. The model was first validated against the measured swirl-plane velocity fields, and the simulation convergence for multiple cycles was assessed. Flow topology was studied by addressing bulk flow and turbulence quantities, including swirl structure, squish flux, plus geometric and operating parameters, such as the presence of valve cut-outs on the piston surface, compression ratio and engine speed. The results demonstrated that conventional re-entrant bowls have stronger flow separation at intake, hampering bowl swirl, but higher global swirl than for stepped-lip bowls thanks to a stronger and more axisymmetric squish mechanism and less tilted swirl. Stepped-lip bowls have larger inhomogeneities (tilt and axisymmetry) and higher turbulence levels, but also faster turbulence dissipation toward top dead center. They have weaker squish flux but larger squish inversion momentum as a result of the smaller inertia.

Perini, Federico↗

DOE OSTI2018

Advanced combustion free-piston engines: A comprehensive review

A reciprocating engine without a crank-slider mechanism is called a free-piston engine. If the piston is directly connected to a linear alternator, it is called a free-piston linear alternator. Free-piston engines and free-piston linear alternators have the potential to offer solutions for future hybrid electric vehicles and stationary power generation, by enabling direct conversion of mechanical energy to electricity. They benefit from reduced friction losses compared to conventional engines and can have variable compression ratio, which enables combustion control and optimization. Their widespread application has been limited by the necessity for high-speed control strategies. However, their operating characteristics can provide high efficiency, especially when used with low temperature combustion strategies. Low temperature combustion combines the high thermal efficiency of diesel engines, with the low soot emissions of spark-ignition engines, and low NO x emissions because of low burned gas temperatures. This article provides a comprehensive review of free-piston engine technology, with a focus on advanced combustion processes and their potential for use in future powertrain systems.

Zhou, Yingcong↗