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At least 415 records · Page 23

Quasi-isentropic compressibility of a strongly nonideal deuterium plasma at pressures of up to 5500 GPa: Nonideality and degeneracy effects

We report on the experimental results on the quasi-isentropic compressibility of a strongly nonideal deuterium plasma that have been obtained on setups of cylindrical and spherical geometries in the pressure range of up to P ≈ 5500 GPa. We describe the characteristics of experimental setups, as well as the methods for the diagnostics and interpretation of the experimental results. The trajectory of metal shells that compress the deuterium plasma was detected using powerful pulsed X-ray sources with a maximal electron energy of up to 60 MeV. The values of the plasma density, which varied from ρ ≈ 0.8 g/cm{sup 3} to ρ ≈ 6 g/cm{sup 3}, which corresponds to pressure P ≈ 5500 GPa (55 Mbar), were determined from the measured value of the shell radius at the instant that it was stopped. The pressure of the compressed plasma was determined using gasdynamic calculations taking into account the actual characteristics of the experimental setups. We have obtained a strongly compressed deuterium plasma in which electron degeneracy effects under the conditions of strong interparticle interaction are significant. The experimental results have been compared with the theoretical models of a strongly nonideal partly degenerate plasma. We have obtained experimental confirmation of the plasma phase transition in the pressure range near 150 GPa (1.5 Mbar), which is in keeping with the conclusion concerning anomaly in the compressibility of the deuterium plasma drawn in [1].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

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

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

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

What to Support When You’re Compressing

Over the last nearly 20 years, lossy compression has become an essential aspect of HPC applications’ data pipelines, allowing them to overcome limitations in storage capacity and bandwidth and, in some cases, increase computational throughput and capacity. However, with the adoption of lossy compression comes the requirement to assess and control the impact lossy compression has on scientific outcomes. In this work, we take a major step forward in describing the state of practice and by characterizing workloads. We examine applications’ needs and compressors’ capabilities across 9 different supercomputing application domains. We present 24 takeaways that provide best practices for applications, operational impacts for facilities achieving compressed data, and gaps in application needs not addressed by production compressors that point towards opportunities for future compression research.

Error-Bounded Lossy Compression↗

Use cases of lossy compression for floating-point data in scientific data sets

Architectural and technological trends of systems used for scientific computing call for a significant reduction of scientific data sets that are composed mainly of floating-point data. Here, this article surveys and presents experimental results of currently identified use cases of generic lossy compression to address the different limitations of scientific computing systems. The article shows from a collection of experiments run on parallel systems of a leadership facility that lossy data compression not only can reduce the footprint of scientific data sets on storage but also can reduce I/O and checkpoint/restart times, accelerate computation, and even allow significantly larger problems to be run than without lossy compression. In conclusion, these results suggest that lossy compression will become an important technology in many aspects of high performance scientific computing. Because the constraints for each use case are different and often conflicting, this collection of results also indicates the need for more specialization of the compression pipelines.

97 MATHEMATICS AND COMPUTING↗

Evolution and current understanding of physicochemical characterization of particulate matter from reactivity controlled compression ignition combustion on a multicylinder light-duty engine

Low-temperature compression ignition combustion can result in nearly smokeless combustion, as indicated by a smoke meter or other forms of soot measurement that rely on absorbance due to elemental carbon content. Highly premixed low-temperature combustion modes do not form particulate matter in the traditional pathways seen with conventional diesel combustion. Previous research into reactivity controlled compression ignition particulate matter has shown, despite a near zero smoke number, significant mass can be collected on filter media used for particulate matter certification measurement. In addition, particulate matter size distributions reveal that a fraction of the particles survive heated double-dilution conditions. This paper summarizes research completed at Oak Ridge National Laboratory to date on characterizing the nature, chemistry and aftertreatment considerations of reactivity controlled compression ignition particulate matter and presents new research highlighting the importance of injection strategy and fuel composition on reactivity controlled compression ignition particulate matter formation. Particle size measurements and the transmission electron microscopy results do show the presence of soot particles; however, the elemental carbon fraction was, in many cases, within the uncertainty of the thermal–optical measurement. Particulate matter emitted during reactivity controlled compression ignition operation was also collected with a novel sampling technique and analyzed by thermal desorption or pyrolysis gas chromatography mass spectroscopy. Particulate matter speciation results indicated that the high boiling range of diesel hydrocarbons was likely responsible for the particulate matter mass captured on the filter media. Finally, to investigate potential fuel chemistry effects, either ethanol or biodiesel were incorporated to assess whether oxygenated fuels may enhance particle emission reduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental measurements of soot formation in fuel-rich homogeneous mixtures using an optical rapid compression machine

Advanced combustion strategies are necessary for the use of more environmentally sustainable fuels than traditional diesel. Alcohol fuels and alcohol/gasoline blends are of particular interest as they are readily available in the marketplace. Heavy-duty engines typically use compression ignited, conventional diesel mixing controlled combustion. Mixing controlled combustion features a non-premixed diffusion flame with a wide range of local equivalence ratios, leading to potentially high rates of soot formation. This work studies the sooting behavior of iso-octane and ethanol as a function of equivalence ratio. Measurements are carried out in a rapid compression machine (RCM) and are reported for pre-ignition conditions of 10–30 bar and temperatures of 650–800 K. Theoretical equilibrium and bulk gas temperatures are calculated for both fuels. These data are used to identify the critical equivalence ratio, the lowest equivalence ratio where soot is detected with a single-pass laser extinction diagnostic. The critical equivalence ratio for iso-octane varies between 1.82 and 1.77 for compressed pressures of 10 and 20 bar, respectively. Ethanol, sometimes considered sootless, had a critical equivalence ratio between 2.37 and 2.12 for compressed pressures of 20 and 30 bar, respectively. When characterizing soot formation by oxygenated equivalence ratio, the critical equivalence ratios for ethanol approach those of iso-octane. This suggests the oxygenated nature of alcohol fuels reduces sooting tendency, but other factors such as fuel molecular structure and morphology may play a role. It was observed that ethanol will form soot at equivalence ratios only slightly higher than iso-octane, which could have implications in mixing controlled combustion. It was seen for both fuels that soot formation is pressure sensitive, with the critical equivalence ratio being inversely proportional to compressed pressure and the rate of soot formation. Future work will investigate the sooting behavior of gasoline/ethanol blends.

02 PETROLEUM↗

High-energy sub-phonon lifetime pulse compression by stimulated Brillouin scattering in liquids

Multi-Joule level stimulated Brillouin scattering (SBS) pulse compression below the acoustic phonon lifetime is demonstrated with a energy-scalable generator-amplifier setup. Single-pass compression of pulses longer than 20τ B (τ B as phonon lifetime) to as short as 0.5τ B with ~100 mJ pulse energy is realized from the generator, by choosing the focusing length to match approximately with the full length at half maximum of the input Gaussian pulses. The interaction length is identified, both experimentally and numerically, as the key parameter in achieving sub-phonon lifetime pulse compression, with its main mechanism being the steepening of the Stokes pulse trailing edge via energy exchange process. After combining the generator with an amplifier that involves only collimated beams and serves as energy booster, the compression of 9 ns, 2 J pulses at 532 nm into 170 ps, 1.3 J per pulse is achieved in water, with very good stability in both pulse energy and duration. Furthermore, this work demonstrates for the first time the efficient high-energy SBS sub-phonon lifetime pulse compression, and paves a way to the reliable generation of sub-200 ps laser pulses with Joule-level energy.

74 ATOMIC AND MOLECULAR PHYSICS↗

A Comparison of Compressed Sensing and Sparse Recovery Algorithms Applied to Simulation Data

The move toward exascale computing for scientific simulations is placing new demands on compression techniques. It is expected that the I/O system will not be able to support the volume of data that is expected to be written out. To enable quantitative analysis and scientific discovery, we are interested in techniques that compress high-dimensional simulation data and can provide perfect or near-perfect reconstruction. In this paper, we explore the use of compressed sensing (CS) techniques to reduce the size of the data before they are written out. Using large-scale simulation data, we investigate how the sufficient sparsity condition and the contrast in the data affect the quality of reconstruction and the degree of compression. Also, we provide suggestions for the practical implementation of CS techniques and compare them with other sparse recovery methods. Finally, our results show that despite longer times for reconstruction, compressed sensing techniques can provide near perfect reconstruction over a range of data with varying sparsity.

97 MATHEMATICS AND COMPUTING↗

Illinois Compressed Air Energy Storage

Compressed Air Storage Energy (CAES) is one of the few mid- technology readiness level (TRL) energy storage technologies that can address the long-duration infrastructure needed for dealing with variable electric output from renewable energy sources and be reliable backup source for replacing natural gas during supply interruptions. In CAES the goal is to capture and store compressed air in subsurface sedimentary strata when off-peak power is available, or there is a need for grid balancing. The stored high-pressure air is returned to the surface and used to power turbines during reductions in either renewable energy or supply issues with fossil fuels. The Illinois CAES project evaluates the feasibility of capturing surplus electrical energy from renewable sources and off-peak energy at a fossil fuel power plant at the University of Illinois Urbana - Champaign (UIUC) campus. The UIUC Abbott Power Plant uses natural gas and coal to generate electricity (capacity: 35 MWe by coal and 49 MWe by NG). UIUC receives additional electricity from on campus solar farm, and off-campus wind farm. Also, UIUC offsets electricity usage by integrating geothermal energy systems into building heating Also, UIUC offsets steam, hot and chilled water usage by integrating geothermal energy systems into building heating and cooling systems. Furthermore, the two UIUC solar farms (Solar Farm 1 is 21 acres and Solar Farm 2 is 54 acres) to generate 4.68 megawatts (MW) and 12.1 MW, respectively. Campus receives 8.6% of the wind-generated electricity from the Rail Splitter Wind Farm. The project objectives were to design an integrated system to 1) capture surplus electrical energy from renewable sources and the Abbott Power Plant using a CAES system, 2) store both the compressed air and the thermal heat generated by compression in the subsurface as part of an adiabatic system, 3) simulate the movement of the air and heat in the subsurface, 4) recover the compressed air and stored thermal heat to rotate turbine generators during sustained interruption due to weather events or fossil fuel disruptions.

03 NATURAL GAS↗

X-ray Free Electron Laser Accelerator Lattice Design Using Laser-Assisted Bunch Compression

We report the start-to-end modeling of our accelerator lattice design employing a laser-assisted bunch compression (LABC) scheme in an X-ray free electron laser (XFEL), using the proposed Matter-Radiation Interactions in Extremes (MaRIE) XFEL parameters. The accelerator lattice utilized a two-stage bunch compression scheme, with the first bunch compressor performing a conventional bulk compression enhancing the beam current from 20 A to 500 A, at 750 MeV. The second bunch compression was achieved by modulating the beam immediately downstream of the first bunch compressor by a laser with 1-μm wavelength in a laser modulator, accelerating the beam to the final energy of 12 GeV, and compressing the individual 1-μm periods of the modulated beam into a sequence of microbunches with 3-kA current spikes by the second bunch compressor. The LABC architecture presented had been developed based on the scheme of enhanced self-amplified spontaneous emission (ESASE), but operated in a disparate regime of parameters. Enabled by the novel technology of the cryogenic normal conducting radiofrequency photoinjector, we investigated an electron beam with ultra-low emittance at the starting point of the lattice design. Our work aimed at mitigating the well-known beam instabilities to preserve the beam emittance and suppress the energy spread growth.

43 PARTICLE ACCELERATORS↗

Lossy checkpoint compression in full waveform inversion: a case study with ZFPv0.5.5 and the overthrust model

This paper proposes a new method that combines checkpointing methods with error-controlled lossy compression for large-scale high-performance full-waveform inversion (FWI), an inverse problem commonly used in geophysical exploration. This combination can significantly reduce data movement, allowing a reduction in run time as well as peak memory. In the exascale computing era, frequent data transfer (e.g., memory bandwidth, PCIe bandwidth for GPUs, or network) is the performance bottleneck rather than the peak FLOPS of the processing unit. Like many other adjoint-based optimization problems, FWI is costly in terms of the number of floating-point operations, large memory footprint during backpropagation, and data transfer overheads. Past work for adjoint methods has developed checkpointing methods that reduce the peak memory requirements during backpropagation at the cost of additional floating-point computations. Combining this traditional checkpointing with error-controlled lossy compression, we explore the three-way tradeoff between memory, precision, and time to solution. We investigate how approximation errors introduced by lossy compression of the forward solution impact the objective function gradient and final inverted solution. Empirical results from these numerical experiments indicate that high lossy-compression rates (compression factors ranging up to 100) have a relatively minor impact on convergence rates and the quality of the final solution.

58 GEOSCIENCES↗

Developing A Fully Implicit Compressible Flow Valve Model in RELAP-7 and Its Application in Short Term BWR Station Black-Out Analyses

This paper presents a set of dynamical models for SRV simulation and their implementation in the RELAP-7 code, which is a new reactor system analysis code being developed at INL. RELAP-7 is based on the MOOSE (the Multi-Physics Object-Oriented Simulation Environment) framework. The compressible flow SRV model covers three different sets of models: fully closed case, subsonic case, and choking case. The RELAP-7 is a fully implicit code and the preconditioned Jacobian-free Newton-Krylov (JFNK) method is used to solve the discretized nonlinear problem. The JFNK method generally needs a good preconditioning scheme to be effective and efficient. There are different ways to precondition the JFNK method. In RELAP-7, two main options are used to obtain the preconditioning matrix: (1) FDP (Finite Difference Preconditioning) option which uses the default finite differencing method provided in the PETSc package. PETSc is the numerical solver software developed by Argonne National Laboratory and used by MOOSE as the numerical solution engine; (2) SMP (Single Matrix Preconditioning) option which requires code developers to provide approximate analytical Jacobian inputs for the important diagonal and off-diagonal terms. Due to the strong discontinuity in the residual vector space when the compressible flow valve model switches from one set of model to another, FDP option cannot guarantee convergence. Instead, accurate analytical Jacobain terms are provided for the compressible flow valve model. With the SMP option selected, the compressible flow valve model can be solved efficiently under different cases. The developed compressible flow valve model has been used for SRV component simulation in several simplified BWR SBO (Station Black-Out) simulations with RELAP-7. This paper only presents cases for short-term SBO in which all the safety systems fail to start and function properly when SBO occurs. Consequently, only the SRVs automatically open and close periodically to control the primary system pressure and discharge the high temperature and high pressure steam into the suppression pool. Although simplified, this case is quite similar to what happened in Fukushima Daiichi Unit 1. Unit 1 had no RCIC system, while the isolation condenser system was believed to be non-functioning, or only available for a very short period of time during the accident. Therefore, the Unit 1 reactor core reached a fuel failure temperature only a few hours into the accident. Two short-term SBO cases will be compared: one with single SRV discharge line which represents all the SRV lines and another case with multi-group SRVs which represent each group of SRV line with different setting points.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

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

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

Gong, Qian↗

Unlocking large compressive strains in thin active elastocaloric layers

Elastocaloric cooling attracts broad interest and rapidly growing attention due to its potential for high efficiency and low environmental impact. While it is common knowledge that triggering reversible entropy and temperature changes with stress applied in compression prevents rapid failures of materials, realizing this regime in elastocaloric systems is highly challenging because nearly all geometries suited for efficient heat transfer are prone to buckling even under modest loads. This work describes a concept of a novel composite, where an active NiTi layer is embedded into a polymer support structure such that the elastocaloric material is entirely in compression when the assembly is subjected to bending. The active layer achieves 8.1 K temperature change at 2.5% compressive strain without buckling. After 10,000 cycles at 2% compressive strain, the composite maintains mechanical integrity without degradation of the elastocaloric effect. The results demonstrate that NiTi and, potentially, other elastocalorically active materials in geometries previously thought impossible can be successfully implemented in regenerative cooling systems operating in compression.

42 ENGINEERING↗

A laboratory-scale compression feed screw for characterizing continuous feeding of dense granular materials

Compression feed screws are commonly used in biorefineries for the continuous feeding of biomass feedstock into reactors. Developing methods to assess the feasibility of feeding granular materials in a compression feed screw is critical for reducing solids handling issues during operation. A laboratory-scale compression feed screw has been built to measure critical process parameters of the feeding operation, namely the driving torque and the mass flow rate. The process parameters of two granular materials, microcrystalline cellulose Avicel PH-200 and milled corn stover are measured using the laboratory-scale feeder. The results show that a larger torque is required to feed corn stover than Avicel PH-200, even though the former consists of more compressible particles. Further, the device can capture real-time fluctuations in the process parameters during operation. Here, the laboratory-scale feeder can be used to compare the feeding of different granular materials and the measured parameters can be used to validate predictive models for a compression screw feeding process.

09 BIOMASS FUELS↗

Compressive strength improvements from noncircular carbon fibers: A numerical study

The benefits of high-performance unidirectional carbon fiber composites are limited in many cost-driven industries due to the high cost relative to alternative reinforcement fibers. Low-cost carbon fibers have been previously proposed, but the longitudinal compressive strength continues to be a limiting factor or studies are based on simplifications that warrant further analysis. A micromechanical model is used to (1) determine if the longitudinal compressive strength of composites can be improved with noncircular carbon fiber shapes and (2) characterize why some shapes are stronger than others in compression. In comparison to circular fibers, the results suggest that the strength can be increased by 10%–13% by using a specific six-lobe fiber shape and by 6%–9% for a three-lobe fiber shape. A slight increase is predicted in the compressive strength of the study two-lobe fiber but has the highest uncertainty and sensitivity to fiber orientation and misalignment direction. The underlying mechanism governing the compressive failure of the composites was linked to the unique stress fields created by the lobes, particularly the pressure stress in the matrix. Importantly, this work provides mechanics-based evidence of strength improvements from noncircular fiber shapes and insight on how matrix yielding is altered with alternative fiber shapes.

36 MATERIALS SCIENCE↗

Probing water distribution in compressed fuel-cell gas-diffusion layers using X-ray computed tomography

X-ray computed tomography was used to investigate geometrical land and channel effects on spatial liquid-water distribution in gas-diffusion layers (GDLs) of polymer-electrolyte fuel cells under different levels of compression. At low compression, a uniform liquid-water front was observed due to water redistribution and uniform porosity; however, at high compression, the water predominantly advanced at locations under the channel for higher liquid pressures. Lastly, at low compression, no apparent correlation between the spatial liquid water and porosity distributions was observed, whereas at high compression, a strong correlation was shown, indicating a potential for smart GDL architecture design with modulated porosity.

25 ENERGY STORAGE↗

Thermodynamic analysis of a compressed carbon dioxide energy storage system using two saline aquifers at different depths as storage reservoirs

Compressed air energy storage (CAES) is one of the leading large-scale energy storage technologies. However, low thermal efficiency and low energy storage density restrict its application. To improve the energy storage density, we propose a two-reservoir compressed CO 2 energy storage system. We present here thermodynamic and parametric analyses of the performance of an idealized two-reservoir CO 2 energy storage system under supercritical and transcritical conditions using a steady-state mathematical model. Results show that the transcritical compressed CO 2 energy storage system has higher round-trip efficiency and exergy efficiency, and larger energy storage density than the supercritical compressed CO 2 energy storage. However, the configuration of supercritical compressed CO 2 energy storage is simpler, and the energy storage densities of the two systems are both higher than that of CAES, which is advantageous in terms of storage volume for a given power rating.

25 ENERGY STORAGE↗