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At least 811 records · Page 45

Dynamical correlation effects on structure factor of spin-polarized two-dimensional electron gas

We report a theoretical study on static density structure factor S(q) of a spin-polarized two-dimensional electron gas over a wide range of electron number density r{sub s}. The electron correlations are treated within the dynamical version of the self-consistent mean-field theory of Singwi, Tosi, Land, and Sjolander, the so-called qSTLS approach. The calculated S(q) exhibits almost perfect agreement with the quantum Monte Carlo simulation data at r{sub s}=1. However, the extent of agreement somewhat diminishes with increasing r{sub s}, particularly for q around 2k{sub F}. Seen in conjunction with the success of qSTLS theory in dealing with correlations in the unpolarized phase, our study suggests that the otherwise celebrated qSTLS theory is not that good in treating the like-spin correlations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

An efficient reconstruction algorithm for differential phase-contrast tomographic images from a limited number of views

The main focus of this paper is reconstruction of tomographic phase-contrast image from a set of projections. We propose an efficient reconstruction algorithm for differential phase-contrast computed tomography that can considerably reduce the number of projections required for reconstruction. The key result underlying this research is a projection theorem that states that the second derivative of the projection set is linearly related to the Laplacian of the tomographic image. The proposed algorithm first reconstructs the Laplacian image of the phase-shift distribution from the second-derivative of the projections using total variation regularization. The second step is to obtain the phase-shift distribution by solving a Poisson equation whose source is the Laplacian image previously reconstructed under the Dirichlet condition. We demonstrate the efficacy of this algorithm using both synthetically generated simulation data and projection data acquired experimentally at a synchrotron. The experimental phase data were acquired from a human coronary artery specimen using dark-field-imaging optics pioneered by our group. Our results demonstrate that the proposed algorithm can reduce the number of projections to approximately 33% as compared with the conventional filtered backprojection method, without any detrimental effect on the image quality.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Dodging the cosmic curvature to probe the constancy of the speed of light

We develop a new model-independent method to probe the constancy of the speed of light c . In our method, the degeneracy between the cosmic curvature and the speed of light can be eliminated, which makes the test more natural and general. Combining the independent observations of Hubble parameter H ( z ) and luminosity distance d {sub L} ( z ), we use the model-independent smoothing technique, Gaussian processes, to reconstruct them and then detect variation of the speed of light. We find no signal of deviation from the present value of the speed of light c {sub 0}. Moreover, to demonstrate the improvement in probing the constancy of the speed of light from future experiments, we produce a series of simulated data. The Dark Energy Survey will be able to detect Δ c / c {sub 0} ∼ 1% at ∼ 1.5σ confidence level and Δ c / c {sub 0} ∼ 2% at ∼ 3σ confidence level. If the errors are reduced to one-tenth of the expected DES ones, it can detect a Δ c / c {sub 0} ∼ 0.1% variation at ∼ 2σ confidence level.

79 ASTRONOMY AND ASTROPHYSICS↗

Remote Sensing Low Signal-to-Noise-Ratio Target Detection Enhancement

In real-time remote sensing application, frames of data are continuously flowing into the processing system. The capability of detecting objects of interest and tracking them as they move is crucial to many critical surveillance and monitoring missions. Detecting small objects using remote sensors is an ongoing, challenging problem. Since object(s) are located far away from the sensor, the target’s Signal-to-Noise-Ratio (SNR) is low. The Limit of Detection (LOD) for remote sensors is bounded by what is observable on each image frame. In this paper, we present a new method, a “Multi-frame Moving Object Detection System (MMODS)”, to detect small, low SNR objects that are beyond what a human can observe in a single video frame. This is demonstrated by using simulated data where our technology-detected objects are as small as one pixel with a targeted SNR, close to 1:1. We also demonstrate a similar improvement using live data collected with a remote camera. The MMODS technology fills a major technology gap in remote sensing surveillance applications for small target detection. Our method does not require prior knowledge about the environment, pre-labeled targets, or training data to effectively detect and track slow- and fast-moving targets, regardless of the size or the distance.

47 OTHER INSTRUMENTATION↗

Validation of NSFsim as a Grad-Shafranov equilibrium solver at DIII-D

Plasma shape is a significant factor that must be considered for any Fusion Pilot Plant (FPP) as it has significant consequences for plasma stability and core confinement. A new simulator, NSFsim, has been developed based on a historically successful code, DINA [1], offering tools to simulate both transport and plasma shape. Specifically, NSFsim is a free boundary equilibrium and transport solver and has been configured to match the properties of the DIII-D tokamak. This paper is focused on validating the Grad-Shafranov (GS) solver of NSFsim by analyzing its ability to recreate the plasma shape, the poloidal flux distribution, and the measurements of the simulated diagnostic signals originating from flux loops and magnetic probes in DIII-D. Five different plasma shapes are simulated to show the robustness of NSFsim to different plasma conditions; these shapes are Lower Single Null (LSN), Upper Single Null (USN), Double Null (DN), Inner Wall Limited (IWL), and Negative Triangularity (NT). The NSFsim results are compared against real measured signals, magnetic profile fits from EFIT [2], and another plasma equilibrium simulator, GSevolve [3]. EFIT reconstructions of shots are readily available at DIII-D, but GSevolve was manually ran by us to provide simulation data to compare against.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Temperature Rise on Liner Surfaces of Fuel Cell Electric Vehicle Tanks during Fueling Process

Herein, the temperature of the inner tank walls, or plastic liners, of composite pressure tanks in fuel cell electric vehicles during fueling using three‐dimensional computational fluid dynamics (CFD) models is evaluated. The liner materials are limited to 85.0 °C to prevent thermal stress causing material failure that would result in a hydrogen leak. Therefore, the temperature of hydrogen gas must be limited to below 85.0 °C during the fueling process as dictated by the current fueling protocol. However, there are limited experimental or simulation data confirming that the temperature changes do not exceed the threshold. Herein, the liner temperatures with CFD tank models for two sizes of type IV tanks representative of the upper and lower system bounds that are close to the SAE J2601 fueling protocol (36.0 and 244.0 L) are evaluated. First, each model's reliability is validated with experimental data and then analyzed, and the data are used to evaluate the maximum hydrogen and liner temperatures under real‐world fueling conditions. The evaluation shows that the maximum liner surface temperature of each tank model is at least 7 °C lower than that of the hydrogen. Additionally, there is at least 12 °C difference found between the upper limit and actual liner temperatures.

33 ADVANCED PROPULSION SYSTEMS↗

Perpendicular diffusion of a dilute beam of charged dust particles in a strongly coupled dusty plasma

The diffusion of projectiles drifting through a target of strongly coupled dusty plasma is investigated in a simulation. A projectile's drift is driven by a constant force F. We characterize the random walk of the projectiles in the direction perpendicular to their drift. The perpendicular diffusion coefficient D{sub p⊥} is obtained from the simulation data. The force dependence of D{sub p⊥} is found to be a power law in a high force regime, but a constant at low forces. A mean kinetic energy W{sub p} for perpendicular motion is also obtained. The diffusion coefficient is found to increase with W{sub p} with a linear trend at higher energies, but an exponential trend at lower energies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Comparisons of characteristic timescales and approximate models for Brownian magnetic nanoparticle rotations

Magnetic nanoparticles are promising tools for a host of therapeutic and diagnostic medical applications. The dynamics of rotating magnetic nanoparticles in applied magnetic fields depend strongly on the type and strength of the field applied. There are two possible rotation mechanisms and the decision for the dominant mechanism is often made by comparing the equilibrium relaxation times. This is a problem when particles are driven with high-amplitude fields because they are not necessarily at equilibrium at all. Instead, it is more appropriate to consider the “characteristic timescales” that arise in various applied fields. Approximate forms for the characteristic time of Brownian particle rotations do exist and we show agreement between several analytical and phenomenological-fit models to simulated data from a stochastic Langevin equation approach. We also compare several approximate models with solutions of the Fokker-Planck equation to determine their range of validity for general fields and relaxation times. The effective field model is an excellent approximation, while the linear response solution is only useful for very low fields and frequencies for realistic Brownian particle rotations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

REPEATABILITY AND ACCURACY OF EXOPLANET ECLIPSE DEPTHS MEASURED WITH POST-CRYOGENIC SPITZER

We examine the repeatability, reliability, and accuracy of differential exoplanet eclipse depth measurements made using the InfraRed Array Camera (IRAC) on the Spitzer Space Telescope during the post-cryogenic mission. We have re-analyzed an existing 4.5 μ m data set, consisting of 10 observations of the XO-3b system during secondary eclipse, using seven different techniques for removing correlated noise. We find that, on average, for a given technique, the eclipse depth estimate is repeatable from epoch to epoch to within 156 parts per million (ppm). Most techniques derive eclipse depths that do not vary by more than a factor 3 of the photon noise limit. All methods but one accurately assess their own errors: for these methods, the individual measurement uncertainties are comparable to the scatter in eclipse depths over the 10 epoch sample. To assess the accuracy of the techniques as well as to clarify the difference between instrumental and other sources of measurement error, we have also analyzed a simulated data set of 10 visits to XO-3b, for which the eclipse depth is known. We find that three of the methods (BLISS mapping, Pixel Level Decorrelation, and Independent Component Analysis) obtain results that are within three times the photon limit of the true eclipse depth. When averaged over the 10 epoch ensemble, 5 out of 7 techniques come within 60 ppm of the true value. Spitzer exoplanet data, if obtained following current best practices and reduced using methods such as those described here, can measure repeatable and accurate single eclipse depths, with close to photon-limited results.

79 ASTRONOMY AND ASTROPHYSICS↗

Fluctuations in the Dynamics of Glasses

This research program addressed the question of the presence of dynamical heterogeneities – strong spatial fluctuations in the dynamics – in glass forming liquids and jamming systems near dynamical arrest, with particular emphasis on aging systems, i.e. systems that are in the (non-equilibrium) glass regime. The main goals proposed for this research were: to perform numerical simulations of atomistic structural glass models to characterize dynamical heterogeneities in out of equilibrium (aging) glassy systems; to test the hypothesis that a certain symmetry (“time reparametrization symmetry”) is present in microscopic models of glassy systems and that this symmetry can explain the main features of dynamical heterogeneities; and to test to what extent these phenomena are universal across different glassy/jamming systems. It was found that: most of the important features of dynamical heterogeneities in the aging regime could be described in terms of simple scaling behaviors; that some of the most basic theoretical models of glassy systems indeed have time reparametrization symmetry; that all tests performed in numerical simulation data were consistent with the predictions from time reparametrization symmetry; and that to a large degree, the main features of dynamical heterogeneities were universal across different glassy systems. Most of the findings that came out of this research have been reported in detail in eight papers in high quality journals, two unpublished but publicly accessible manuscripts, and 27 invited and contributed talks.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Comparison of the Accuracy and Speed of Transient Mobile A/C System Simulation Models: Preprint

The operation of air conditioning (A/C) systems is a significant contributor to the total amount of fuel used by light- and heavy-duty vehicles. Therefore, continued improvement of the efficiency of these mobile A/C systems is important. Numerical simulation has been used to reduce the system development time and to improve the electronic controls, but numerical models that include highly detailed physics run slower than desired for carrying out vehicle-focused drive cycle-based system optimization. Therefore, faster models are needed even if some accuracy is sacrificed. In this study, a validated model with highly detailed physics, the 'Fully-Detailed' model, and two models with different levels of simplification, the 'Quasi-Transient' and the 'Mapped- Component' models, are compared. The Quasi-Transient model applies some simplifications compared to the Fully-Detailed model to allow faster model execution speeds. The Mapped-Component model is similar to the Quasi-Transient model except instead of detailed flow and heat transfer calculations in the heat exchangers, it uses lookup tables created with the Quasi-Transient model. All three models are set up to represent the same physical A/C system and the same electronic controls. Speed and results of the three model versions are compared for steady state and transient operation. Steady state simulated data are also compared to measured data. The results show that the Quasi-Transient and Mapped-Component models ran much faster than the Fully-Detailed model, on the order of 10- and 100-fold, respectively. They also adequately approach the results of the Fully-Detailed model for steady-state operation, and for drive cycle-based efficiency predictions

02 PETROLEUM↗

A robust deep learning workflow to predict multiphase flow behavior during geological C O 2 sequestration injection and Post-Injection periods

Simulation of multiphase flow in porous media is essential to manage the geologic CO 2 sequestration (GCS) process, and physics-based simulation approaches usually take prohibitively high computational cost due to the nonlinearity of the coupled physics. This paper contributes to the development and evaluation of a deep learning workflow that accurately and efficiently predicts the temporal-spatial evolution of pressure and CO 2 plumes during injection and post-injection periods of GCS operations. Based on a Fourier Neural Operator, the deep learning workflow takes input variables or features including rock properties, well operational controls and time steps, and predicts the state variables of pressure and CO 2 saturation. To further improve the predictive fidelity, separate deep learning models are trained for CO 2 injection and post-injection periods due to the difference in primary driving force of fluid flow and transport during these two phases. We also explore different combinations of features to predict the state variables. We use a realistic example of CO 2 injection and storage in a 3D heterogeneous saline aquifer, and apply the deep learning workflow that is trained from physics-based simulation data and emulate the physics process. Through this numerical experiment, we demonstrate that using two separate deep learning models to distinguish post-injection from injection period generates the most accurate prediction of pressure, and a single deep learning model of the whole GCS process including the cumulative injection volume of CO 2 as a deep learning feature, leads to the most accurate prediction of CO 2 saturation. For the post-injection period, it is key to use cumulative CO 2 injection volume to inform the deep learning models about the total carbon storage when predicting either pressure or saturation. The deep learning workflow not only provides high predictive fidelity across temporal and spatial scales, but also offers a speedup of 250 times compared to full physics reservoir simulation, and thus will be a significant predictive tool for engineers to manage the long-term process of GCS.

58 GEOSCIENCES↗

Theoretical Approach for the Fast Estimation of the Turbulent Kinematic Viscosity for Internal Flows

An analytical expression for turbulent kinematic viscosity (νt), based solely on the hydraulic Reynolds number (Re), was derived and evaluated. The analytical expression is valid for the fast estimation of νt for internal, isotropic, fully developed flows. The expression was compared with experimental and simulation data for air, water, and liquid sodium, and was shown to provide reasonable values for 2100 ≤ Re ≤ 3.6 × 106 and Prandtl number (Pr) range of 0.0107 ≤ Pr ≤ 5.65. In addition, new expressions suitable for the central portion of internal flows, away from the wall, were derived for the turbulent Reynolds number (ReT), showing its relationship to Re, as well as to the ratio of νt and the molecular kinematic viscosity (ν).

42 ENGINEERING↗

A hybrid 3D/2D field response calculation for liquid argon detectors with PCB based anode plane

Liquid Argon Time Projection Chamber (LArTPC) technology is commonly utilized in neutrino detector designs. It enables detailed reconstruction of neutrino events with high spatial precision and low energy threshold. Its field response (FR) model describes the time-dependent electric currents induced in the anode-plane electrodes when ionization electrons drift nearby. An accurate and precise FR is a crucial input to LArTPC detector simulations and charge reconstruction. Established LArTPC designs have been based on parallel wire planes. It allows accurate and computationally economic two-dimensional (2D) FR models utilizing the translational symmetry along the direction of the wires. Recently, novel LArTPC designs utilize electrodes formed on printed circuit board (PCB) in the shape of strips with through holes. The translational symmetry is no longer a good approximation near the electrodes and a new FR calculation that employs regions with three dimensions (3D) has been developed. Extending the 2D models to 3D would be computationally expensive. Fortuitously, the nature of strips with through holes allows for a computationally economic approach based on the finite-difference method (FDM). In this paper, we present a new software package pochoir that calculates LArTPC field response for these new strip-based anode designs. This package combines 3D calculations in the volume near the electrodes with 2D far-field solutions to achieve fast and precise field response computation. We apply the resulting FR to simulate and reconstruct samples of cosmic-ray muons and 39 Ar decays from a Vertical Drift (VD) detector prototype operated at CERN. We find the difference between real and simulated data within 5%. Current state-of-the-art LArTPC software requires a 2D FR which we provide by averaging over one dimension and estimate that variations lost in this average are smaller than 7%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Reconstruction of neuronal input through modeling single-neuron dynamics and computations

Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-space method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A constitutive model for sheared dense suspensions of rough particles

In a concentrated suspension, particles come into contact due to the presence of asperities on their surfaces. As a result, the contact forces and interparticle friction become one of the important factors governing the rheology of rigid particle suspensions at high concentrations. We show that a load-dependent friction model can be used to reproduce the experimentally observed shear thickening [ST—continuous and discontinuous (DST)] behavior with an increase in the asperity size. Increasing the particle surface roughness size leads to a decrease in the critical shear rate above which shear-thickening takes place, a reduction in the critical volume fraction for DST and an increase in the viscosity jump across non-shear-thickened to shear-thickened regime. In this paper, we propose a constitutive model to quantify the effect of increasing the roughness size on the rheology of dense ST suspensions as well as on the critical shear rate for ST and the critical volume fraction for DST. We fit this model to our simulation data for stress controlled shear flow of dense rough particle suspensions. Once the fitting is complete, these equations are used to predict exact volume fractions and shear stress values for transitions between three regimes on the shear stress-shear rate flow state diagram for different roughness values. Furthermore, the results of this study can be used to tune the particle surface roughness for manipulating the dense suspension rheology according to different applications.

42 ENGINEERING↗

Information content of and the ability to reconstruct dichroic X-ray tomography and laminography

Dichroic tomography is a 3D imaging technique in which the polarization of the incident beam is used to induce contrast due to the magnetization or orientation of a sample. The aim is to reconstruct not only the optical density but the dichroism of the sample. The theory of dichroic tomographic and laminographic imaging in the parallel-beam case is discussed as well as the problem of reconstruction of the sample’s optical properties. The set of projections resulting from a single tomographic/laminographic measurement is not sufficient to reconstruct the magnetic moment for magnetic circular dichroism unless additional constraints are applied or data are taken at two or more tilt angles. For linear dichroism, three polarizations at a common tilt angle are insufficient for unconstrained reconstruction. However, if one of the measurements is done at a different tilt angle than the other, or the measurements are done at a common polarization but at three distinct tilt angles, then there is enough information to reconstruct without constraints. Possible means of applying constraints are discussed. Furthermore, it is shown that for linear dichroism, the basic assumption that the absorption through a ray path is the integral of the absorption coefficient, defined on the volume of the sample, along the ray path, is not correct when dichroism or birefringence is strong. This assumption is fundamental to tomographic methods. An iterative algorithm for reconstruction of linear dichroism is demonstrated on simulated data.

Marcus, Matthew A. (ORCID:0000000325277586)↗

A molecular dynamics study on slow ion interactions with the polycyclic aromatic hydrocarbon molecule anthracene

Atomic collisions with polycyclic aromatic hydrocarbon (PAH) molecules are astrophysically particularly relevant for collision energies of less than 1 keV. In this regime, the interaction dynamics are dominated by elastic interactions. We have employed a molecular dynamics simulation based on analytical interaction potentials to model the interaction of low energy hydrogen and helium projectiles with isolated anthracene (C{sub 14}H{sub 10}) molecules. This approach allows for a very detailed investigation of the elastic interaction dynamics on an event by event basis. From the simulation data the threshold projectile kinetic energies above which direct C atom knock out sets in were determined. Anthracene differential energy transfer cross sections and total (dissociation) cross sections were computed for a wide range of projectile kinetic energies. The obtained results are interpreted in the context of PAH destruction in astrophysical environments.

74 ATOMIC AND MOLECULAR PHYSICS↗