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At least 685 records · Page 38

Ensemble Sampling vs. Time Sampling in Molecular Dynamics Simulations of Thermal Conductivity

In this report we compare time sampling and ensemble averaging as two different methods available for phase space sampling. For the comparison, we calculate thermal conductivities of solid argon and silicon structures, using equilibrium molecular dynamics. We introduce two different schemes for the ensemble averaging approach, and show that both can reduce the total simulation time as compared to time averaging. It is also found that velocity rescaling is an efficient mechanism for phase space exploration. Although our methodology is tested using classical molecular dynamics, the ensemble generation approaches may find their greatest utility in computationally expensive simulations such as first principles molecular dynamics. For such simulations, where each time step is costly, time sampling can require long simulation times because each time step must be evaluated sequentially and therefore phase space averaging is achieved through sequential operations. On the other hand, with ensemble averaging, phase space sampling can be achieved through parallel operations, since each ensemble is independent. For this reason, particularly when using massively parallel architectures, ensemble sampling can result in much shorter simulation times and exhibits similar overall computational effort.

74 ATOMIC AND MOLECULAR PHYSICS↗

On the theory of nonhomogeneous nonequilibrium superconductivity in 2D systems with massless fermions

Here we analyze static and nonequilibrium superconducting properties of a 2D relativistic-like model system with local electron-electron interaction, Rashba spin-orbit interaction αR in presence of time-dependent in-plane magnetic field H(t). It is shown that similar to the 2D case with ordinary massive quasiparticle dispersion ε(k)~|k| 2 at large fields, such a system demonstrates a nonhomogeneous superconducting stripe phase with the order parameter Δ(r)=Δ(0)cos(2[μ B B×r]n/$\hbarυ_F$) (B is the magnetic induction, υF is the Fermi velocity, n is the normal to the plane, μ B is the Bohr magneton, and αR$\ll$υF) where the stripes are oriented along the B direction. In the considered system, the inter-stripe period L and the magnitude of the magnetic field B are related by a universal relation BL=$\hbarυ_F$/μ B ≃0.714∙10 -4 Tm. Contrary to the case of massive quasiparticles, where the condition α R ~υ F can be, in principle, satisfied by increasing α R or by charge doping (Fermi velocity decreasing), in a relativistic-like system, where υF is doping-independent and one-two orders of magnitude larger than typical Fermi velocity in the “standard” 2D systems, the stripe phase can be the ground state at a rather low doping level. We also analyzed the nonequilibrium properties of the system with a focus on the melting of the stripe order (when the magnetic field is quenched to a lower value) and stripe dynamics (when the field is rotated by 90° degrees) and found several notable results. In particular, it was shown that the stripe domains melt according to law R~1$\sqrt{t}$ at initial times, while at longer times they shrink exponentially. In the case of the flipped magnetic field, the stripe orientation gradually turns from x- to y-direction, and the intermediate “crossed-stripe” phase takes place during times of order of picoseconds. Such a crossed phase is built of periodic superconducting bubbles that potentially may have applications in modern ultrafast superconducting technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Thermodynamic Cloud Phase Classifications Using Machine Learning at NSA and ANX

Vertically resolved thermodynamic cloud phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) THERMOCLDPHASE Value-Added Product (VAP) uses a multi-sensor approach to classify thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave radiometer-derived liquid water path, and radiosonde temperature measurements. The measured voxels are classified as ice, snow, mixed-phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multilayer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with one year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1-score, and mean Intersection over Union (IOU). Analysis of ML confidence scores shows ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential datastreams for ML thermodynamic cloud phase predictions. The ML models’ generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. Finally, we evaluate the ML models’ response to simulated instrument outages and signal degradation.

54 ENVIRONMENTAL SCIENCES↗

Classifying thermodynamic cloud phase using machine learning models

Vertically resolved thermodynamic cloud-phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Thermodynamic Cloud Phase (THERMOCLDPHASE) value-added product (VAP) uses a multi-sensor approach to classify the thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave-radiometer-derived liquid water path, and radiosonde temperature measurements. The measured pixels are classified as ice, snow, mixed phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multi-layer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with 1 year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1 score, and mean intersection over union (IOU). Analysis of ML confidence scores shows that ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential data streams for ML thermodynamic cloud-phase predictions. Lidar measurements exhibit lower feature importance due to rapid signal attenuation caused by the frequent presence of persistent low-level clouds at the NSA site. The ML models' generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. The models demonstrated similar performance to that observed at the NSA site. Finally, we evaluate the ML models' response to simulated instrument outages and signal degradation and show that a CNN U-Net model trained with input channel dropouts performs better when input fields are missing.

ARM Aerial Facility↗

DYNAMICS AND ENERGY LOSS IN SUPERBUBBLES

Interstellar bubbles appear to be smaller in observations than expected from calculations. Instabilities at the shell boundaries create three-dimensional (3D) effects and are probably responsible for part of this discrepancy. We investigate instabilities and dynamics in superbubbles using 3D hydrodynamics simulations with time-resolved energy input from massive stars, including supernova explosions. We find that the superbubble shells are accelerated by supernova explosions, coincident with substantial brightening in soft X-ray emission. In between the explosions, the superbubbles lose energy efficiently, approaching the momentum-conserving snowplow limit. This and enhanced radiative losses due to instabilities reduce the expansion compared to the corresponding radiative bubbles in pressure-driven snowplow models with constant energy input. We note generally good agreement with observations of superbubbles and some open issues. In particular, there are hints that the shell velocities in the X-ray-bright phases are underpredicted.

79 ASTRONOMY AND ASTROPHYSICS↗

QUASI-PERIODIC SLIPPING MAGNETIC RECONNECTION DURING AN X-CLASS SOLAR FLARE OBSERVED BY THE SOLAR DYNAMICS OBSERVATORY AND INTERFACE REGION IMAGING SPECTROGRAPH

We first report the quasi-periodic slipping motion of flare loops during an eruptive X-class flare on 2014 September 10. The slipping motion was investigated at a specific location along one of the two ribbons and can be observed throughout the impulsive phase of the flare. The apparent slipping velocity was 20–110 km s{sup −1}, and the associated period was 3–6 minutes. The footpoints of flare loops appeared as small-scale bright knots observed in 1400 Å, corresponding to fine structures of the flare ribbon. These bright knots were observed to move along the southern part of the longer ribbon and also exhibited a quasi-periodic pattern. The Si iv 1402.77 Å line was redshifted by 30–50 km s{sup −1} at the locations of moving knots with a ∼40–60 km s{sup −1} line width, larger than other sites of the flare ribbon. We suggest that the quasi-periodic slipping reconnection is involved in this process and the redshift at the bright knots is probably indicative of reconnection downflow. The emission line of Si iv at the northern part of the longer ribbon also exhibited obvious redshifts of about 10–70 km s{sup −1} in the impulsive phase of the flare, with the redshifts at the outer edges of the ribbon larger than those in the middle. The redshift velocities at post-flare loops reached about 80–100 km s{sup −1} in the transition region.

79 ASTRONOMY AND ASTROPHYSICS↗

2-dimensional ion velocity distributions measured by laser-induced fluorescence above a radio-frequency biased silicon wafer

The dynamics of ions traversing sheaths in low temperature plasmas are important to the formation of the ion energy distribution incident onto surfaces during microelectronics fabrication. Ion dynamics have been measured using laser-induced fluorescence (LIF) in the sheath above a 30 cm diameter, 2.2 MHz-biased silicon wafer in a commercial inductively coupled plasma processing reactor. The velocity distribution of argon ions was measured at thousands of positions above and radially along the surface of the wafer by utilizing a planar laser sheet from a pulsed, tunable dye laser. Velocities were measured both parallel and perpendicular to the wafer over an energy range of 0.4–600 eV. The resulting fluorescence was recorded using a fast CCD camera, which provided resolution of 0.4 mm in space and 30 ns in time. Data were taken at eight different phases during the 2.2 MHz cycle. The ion velocity distributions (IVDs) in the sheath were found to be spatially non-uniform near the edge of the wafer and phase-dependent as a function of height. Several cm above the wafer the IVD is Maxwellian and independent of phase. Experimental results were compared with simulations. The experimental time-averaged ion energy distribution function as a function of height compare favorably with results from the computer model.

36 MATERIALS SCIENCE↗

Thermodynamics, dynamics, and structure of supercritical water at extreme conditions

Molecular dynamics (MD) simulations to understand the thermodynamic, dynamic, and structural changes in supercritical water across the Frenkel line and the melting line have been performed. The two-phase thermodynamic model [J. Phys. Chem. B(2010), 114(24), 8191-8198] and the velocity autocorrelation functions are used to locate the Frenkel line and to calculate the thermodynamic and dynamic properties. The Frenkel lines obtained from the two-phase thermodynamic model and the velocity autocorrelation criterion do not agree with each other. Structural characteristics and the translational diffusion dynamics of water suggest that this inconsistency could arise from the two oscillatory modes in water, which are associated with the bending of hydrogen bonds and intermolecular collisions inside the first coordination shell. Finally, the overall results lead us to conclude that the universality of the Frenkel line as a dynamic crossover line from rigid to nonrigid fluids is preserved in water.

74 ATOMIC AND MOLECULAR PHYSICS↗

Phase transition and strength of vanadium under shock compression up to 88 GPa

A series of reverse-impact experiments were performed on vanadium at shock pressure ranging from 32 GPa to 88 GPa. Particle velocity profiles measured at sample/LiF window interface were used to estimate the sound velocities, shear modulus, and yield stress in shocked vanadium. A phase transition at ∼60.5 GPa that may be the body-centered cubic (BCC) to rhombohedral structure was identified by the discontinuity of the sound velocity against shock pressure. This transition pressure is consistent with the results from diamond anvil cell (DAC) experiments and first-principle calculations. However, present results show that the rhombohedral phase has higher strength and shear modulus than the BCC phase, which is contrast to the findings from DAC experiments and theoretical work.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Wavelength calibration of x-ray imaging crystal spectrometer on Joint Texas Experimental Tokamak

The wavelength calibration of x-ray imaging crystal spectrometer is a key issue for the measurements of plasma rotation. For the lack of available standard radiation source near 3.95 Å and there is no other diagnostics to measure the core rotation for inter-calibration, an indirect method by using tokamak plasma itself has been applied on joint Texas experimental tokamak. It is found that the core toroidal rotation velocity is not zero during locked mode phase. This is consistent with the observation of small oscillations on soft x-ray signals and electron cyclotron emission during locked-mode phase.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Transport of radial heat flux and second sound in fusion plasmas

Simple flux-gradient relations that involve time delay and radial coupling are discussed. Such a formulation leads to a rather simple description of avalanches and may explain breaking of gyroBohm transport scaling. The generalization of the flux-gradient relation (i.e., constitutive relation), which involve both time delay and spatial coupling, is derived from drift-kinetic equation, leading to kinetic definitions of constitutive elements such as the flux of radial heat flux. This allows numerical simulations to compute these cubic quantities directly. The formulation introduced here can be viewed as an extension of turbulence spreading to include the effect of spreading of cross-phase as well as turbulence intensity, combined in such a way to give the flux. The link between turbulence spreading and entropy production is highlighted. An extension of this formulation to general quasi-linear theory for the distribution function in the phase space of radial position and parallel velocity is also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Velocity-space signatures of shock-drift acceleration at quasi-perpendicular collisionless shocks

The shock-drift acceleration of ions at quasi-perpendicular shocks is a well-known kinetic mechanism for the acceleration of a small fraction of incoming ions to high energy. Here, we use a suite of sixteen hybrid simulations of quasi-perpendicular collisionless shocks over the range of Alfvén Mach number 4.3 ≤ M A ≤ 15.8 (corresponding to a range of fast magnetosonic Mach numbers 2.6 ≤ M f ≤ 9.4) and shock-normal angle 45°≤ θ Bn ≤ 90° to identify the velocity-space signature of shock-drift acceleration using the field-particle correlation technique. We show that the features of the ion velocity distribution in the shock foot and ramp regions can be clearly interpreted by analysis of the single-particle trajectory of a reflected ion through the full 3D-3V phase space. The characteristic features of the velocity-space signature of shock-drift acceleration remain qualitatively robust over the full parameter range of our simulations, providing a potential means for its identification using single-point spacecraft measurements. At higher Alfvén Mach numbers M A ≳8 (M f ≳5), kinetic instabilities generate fluctuations of the electromagnetic fields within the shock transition region, leading to fluctuations in and smearing out of the resulting velocity-space signatures, but the signature remains generally robust and identifiable. The results on the shock-drift acceleration of ions presented here represent a novel means to determine more completely the partitioning of upstream bulk flow kinetic energy into plasma heating, particle acceleration, and electromagnetic fields in collisionless shocks.

Howes, Gregory G. [Univ. of Iowa, Iowa City, IA (U↗

The radial variation of H i velocity dispersions in dwarfs and spirals

Gas velocity dispersions provide important diagnostics of the forces counteracting gravity to prevent collapse of the gas. We use the 21 cm line of neutral atomic hydrogen (H i) to study H i velocity dispersion (σ{sub H I}) and H i phases as a function of galaxy morphology in 22 galaxies from The H i Nearby Galaxy Survey. We stack individual H i velocity profiles and decompose them into broad and narrow Gaussian components. We study the H i velocity dispersion and the H i surface density, Σ{sub H I}, as a function of radius. For spirals, the velocity dispersions of the narrow and broad components decline with radius and their radial profiles are well described by an exponential function. For dwarfs, however, the profiles are much flatter. The single Gaussian dispersion profiles are, in general, flatter than those of the narrow and broad components. In most cases, the dispersion profiles in the outer disks do not drop as fast as the star formation profiles derived in the literature. This indicates the importance of other energy sources in driving σ{sub H I} in the outer disks. The radial surface density profiles of spirals and dwarfs are similar. The surface density profiles of the narrow component decline more steeply than those of the broad component, but not as steep as what was found previously for the molecular component. As a consequence, the surface density ratio between the narrow and broad components, an estimate of the mass ratio between cold H i and warm H i, tends to decrease with radius. On average, this ratio is lower in dwarfs than in spirals. This lack of a narrow, cold H i component in dwarfs may explain their low star formation activity.

79 ASTRONOMY AND ASTROPHYSICS↗

A Radial-velocity Search for Binary RR Lyrae Variables

We report 272 radial velocities for 19 RR Lyrae variables. For most of the stars we have radial velocities for the complete pulsation cycle. These data are used to determine robust center-of-mass radial velocities that have been compared to values from the literature in a search for evidence of binary systems. Center-of-mass velocities were determined for each star using Fourier Series and template fits to the radial velocities. Our center-of-mass velocities have uncertainties from ±0.16 km s{sup −1} to ±2.5 km s{sup −1}, with a mean uncertainty of ±0.92 km s{sup −1}. We combined our center-of-mass velocities with values from the literature to look for deviations from the mean center-of-mass velocity of each star. Fifteen RR Lyrae show no evidence of binary motion (BK And, CI And, Z CVn, DM Cyg, BK Dra, RR Gem, XX Hya, SZ Leo, BX Leo, TT Lyn, CN Lyr, TU Per, U Tri, RV UMa, and AV Vir). In most cases this conclusion is reached due to the sporadic sampling of the center-of-mass velocities over time. Three RR Lyrae show suspicious variation in the center-of-mass velocities that may indicate binary motion but do not prove it (SS Leo, ST Leo, and AO Peg). TU UMa was observed by us near a predicted periastron passage (at 0.14 in orbital phase) but the absence of additional center-of-mass velocities near periastron makes the binary detection, based on radial velocities alone, uncertain. Two stars in our sample show Hγ emission in phases 0.9–1.0: SS Leo and TU UMa.

47 OTHER INSTRUMENTATION↗

Hybrid (Vlasov-Fluid) simulation of ion-acoustic solitons chain formation including trapped electrons

Disintegration of a Gaussian profile into ion-acoustic solitons in the presence of trapped electrons [H. Hakimi Pajouh and H. Abbasi, Phys. Plasmas 15, 082105 (2008)] is revisited. Through a hybrid (Vlasov-Fluid) model, the restrictions associated with the simple modified Korteweg de-Vries (mKdV) model are studied. For instance, the lack of vital information in the phase space associated with the evolution of electron velocity distribution, the perturbative nature of mKdV model which limits it to the weak nonlinear cases, and the special spatio-temporal scaling based on which the mKdV is derived. Remarkable differences between the results of the two models lead us to conclude that the mKdV model can only monitor the general aspects of the dynamics, and the precise picture including the correct spatio-temporal scales and the properties of solitons should be studied within the framework of hybrid model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Microstructure development during rapid alloy solidification

Abstract Solidification processing of structural alloys can take place over an extremely wide range of solid–liquid interface velocities spanning six orders of magnitude, from the low-velocity constitutional supercooling limit of microns/s to the high-velocity absolute stability limit of m/s. In between these two limits, the solid–liquid interface is morphologically unstable and typically forms cellular-dendritic microstructures, but also other microstructures that remain elusive. Rapid developments in additive manufacturing have renewed the interest in modeling the high-velocity range, where approximate analytical theories provide limited predictions. In this article, we discuss recent advances in phase-field modeling of rapid solidification of metallic alloys, including a brief description of state-of-the-art experiments used for model validation. We describe how phase-field models can cope with the dual challenge of carrying out simulations on experimentally relevant length- and time scales and incorporating nonequilibrium effects at the solid–liquid interface that become dominant at rapid rates. We present selected results, illustrating how phase-field simulations have yielded unprecedented insights into high-velocity interface dynamics, shedding new light on both the absolute stability limit and the formation of banded microstructures that are a hallmark of rapid alloy solidification near this limit. We also discuss state-of-the-art experiments used to validate those insights. Graphical abstract

36 MATERIALS SCIENCE↗

Emergence of vorticity and viscous stress in finite-scale quantum hydrodynamics

The Madelung equations offer a hydrodynamic description of quantum systems, from single particles to quantum fluids. In this formulation, the probability density is mapped onto the fluid density and the phase is treated as a scalar potential generating the velocity field. As examples of potential flows, quantum fluids described in this way are inherently irrotational, but quantum vortices may arise at discrete points where the phase is undefined. In this paper, starting from this irrotational description of a quantum fluid, a coarse-graining procedure is applied to arrive at a macroscopic description of the quantum fluid in terms of a hierarchy of moments in which the role of velocity is played by a Favre average of the microscopic velocity field. This hierarchy is truncated using an explicit closure derived from an expansion in a finite length scale. The resulting coarse-grained fields are shown to allow for finite vorticity at any point in the fluid. Additionally, it is shown that this vorticity obeys a similar equation to the vorticity equation in classical hydrodynamics and includes a vortex-stretching term. The particular closure employed here also gives rise to a novel stress term in the fluid equations, which in the appropriate limit appears analogous to an artificial viscous stress from computational fluid dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Properties of Moving Discrete Breathers in Beryllium

Discrete breathers (DBs) have been described among pure metals with face-centered cubic (FCC) and body-centered cubic (BCC) lattice, but for hexagonal close-packed (HCP) metals, their properties are little studied. In this paper, the properties of standing and moving DBs in beryllium HCP metal are analyzed by the molecular dynamics method using the many-body interatomic potential. It is shown that the DB is localized in a close-packed atomic row in the basal plane, while oscillations with a large amplitude along the close-packed row are made by two or three atoms, moving in antiphase with the nearest neighbors. Dependences of the DB frequency on the amplitude, as well as the velocity of the DB on its amplitude and on parameter δ, which determines the phase difference of the oscillations of neighboring atoms, are obtained. The maximum velocity of the DB movement in beryllium reaches 4.35 km/s, which is 33.7% of the velocity of longitudinal sound waves. The obtained results supplement our concepts about the mechanisms of localization and energy transport in HCP metals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗