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At least 1,225 records · Page 68

Entanglement signatures of emergent Dirac fermions: Kagome spin liquid and quantum criticality

Quantum spin liquids (QSLs) are exotic phases of matter that host fractionalized excitations. It is difficult for local probes to characterize QSL, whereas quantum entanglement can serve as a powerful diagnostic tool due to its nonlocality. The kagome antiferromagnetic Heisenberg model is one of the most studied and experimentally relevant models for QSL, but its solution remains under debate. In this work, we perform a numerical Aharonov-Bohm experiment on this model and uncover universal features of the entanglement entropy. By means of the density matrix renormalization group, we reveal the entanglement signatures of emergent Dirac spinons, which are the fractionalized excitations of the QSL. This scheme provides qualitative insights into the nature of kagome QSL and can be used to study other quantum states of matter. As a concrete example, we also benchmark our methods on an interacting quantum critical point between a Dirac semimetal and a charge-ordered phase.

36 MATERIALS SCIENCE↗

Development and Benchmarking of a Hybrid PIC Code For Dense Plasmas and Fast Ignition (Final Report)

Radiation processes play an important role in the study of both fast ignition and other inertial confinement schemes, such as plasma jet driven magneto-inertial fusion, both in their effect on energy balance, and in generating diagnostic signals. In the latter case, warm and hot dense matter may be produced by the convergence of a plasma shell formed by the merging of an assembly of high Mach number plasma jets. This innovative approach has the potential advantage of creating matter of high energy densities in voluminous amount compared with high power lasers or particle beams. An important application of this technology is as a plasma liner for the flux compression of magnetized plasma to create ultra-high magnetic fields and burning plasmas. HyperV Technologies Corp. has been developing plasma jet accelerator technology in both coaxial and linear railgun geometries to produce plasma jets of sufficient mass, density, and velocity to create such imploding plasma liners. An enabling tool for the development of this technology is the ability to model the plasma dynamics, not only in the accelerators themselves, but also in the resulting magnetized target plasma and within the merging/interacting plasma jets during transport to the target. Welch pioneered numerical modeling of such plasmas (including for fast ignition) using the LSP simulation code. Lsp is an electromagnetic, parallelized, plasma simulation code under development since 1995. It has a number of innovative features making it uniquely suitable for modeling high energy density plasmas including a hybrid fluid model for electrons that allows electrons in dense plasmas to be modeled with a kinetic or fluid treatment as appropriate. In addition to in-house use at Voss Scientific, several groups carrying out research in Fast Ignition (LLNL, SNL, UCSD, AWE (UK), and Imperial College (UK)) also use LSP. A collaborative team consisting of HyperV Technologies Corp., Voss Scientific LLC, FAR-TECH, Inc., Prism Computational Sciences, Inc. and Advanced Energy Systems Inc. joined efforts to develop new physics and numerical models for LSP in several key areas to enhance the ability of LSP to model high energy density plasmas (HEDP). This final report details those efforts. Areas addressed in this research effort include: adding radiation transport to LSP, first in 2D and then fully 3D, extending the EMHD model to 3D, implementing more advanced radiation and electrode plasma boundary conditions, and installing more efficient implicit numerical algorithms to speed complex 2-D and 3-D computations. The new capabilities allow modeling of the dominant processes in high energy density plasmas, and further assist the development and optimization of plasma jet accelerators, with particular attention to MHD instabilities and plasma/wall interaction (based on physical models for ion drag friction and ablation/erosion of the electrodes). In the first funding cycle we implemented a solver for the radiation diffusion equation. To solve this equation in 2-D, we used finite-differencing and applied the parallelized sparse-matrix solvers in the PETSc library (Argonne National Laboratory) to the resulting system of equations. A database of the necessary coefficients for materials of interest was assembled using the PROPACEOS and ATBASE codes from Prism. The model was benchmarked against Prism's 1-D radiation hydrodynamics code HELIOS, and against experimental data obtained from HyperV's separately funded plasma jet accelerator development program. Work in the second funding cycle focused on extending the radiation diffusion model to full 3-D, continued development of the EMHD model, optimizing the direct-implicit model to speed up calculations, add in multiply ionized atoms, and improved the way boundary conditions are handled in LSP. These new LSP capabilities were then used, along with analytic calculations and Mach2 runs, to investigate plasma jet merging, plasma detachment and transport, restrike and advanced jet accelerator design. In addition, a strong linkage to diagnostic measurements was made by modeling plasma jet experiments on PLX to support benchmarking of the code. A large number of upgrades and improvements advancing hybrid PIC algorithms were implemented in LSP during the second funding cycle. These include development of fully 3D radiation transport algorithms, new boundary conditions for plasma-electrode interactions, and a charge conserving equation of state that permits multiply ionized high-Z ions. The final funding cycle focused on 1) mitigating the effects of a slow-growing grid instability which is most pronounced in plasma jet frame expansion problems using the two-fluid Eulerian remap algorithm, 2) extension of the Eulerian Smoothing Algorithm to allow EOS/Radiation modeling, 3) simulations of collisionless shocks formed by jet merging, 4) simulations of merging jets using high-Z gases, 5) generation of PROPACEOS EOS/Opacity databases, 6) simulations of plasma jet transport experiments, 7) simulations of plasma jet penetration through transverse magnetic fields, and 8) GPU PIC code development. The tools developed during this project are applicable not only to the study of plasma jets, but also to a wide variety of HEDP plasmas of interest to DOE, including plasmas created in short-pulse laser experiments performed to study fast ignition concepts for inertial confinement fusion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A local crack-tracking strategy to model three-dimensional crack propagation with embedded methods

We develop a local, implicit crack tracking approach to propagate embedded failure surfaces in three-dimensions. We build on the global crack-tracking strategy of Oliver et al. (Int J. Numer. Anal. Meth. Geomech., 2004; 28:609–632) that tracks all potential failure surfaces in a problem at once by solving a Laplace equation with anisotropic conductivity. We discuss important modifications to this algorithm with a particular emphasis on the effect of the Dirichlet boundary conditions for the Laplace equation on the resultant crack path. Algorithmic and implementational details of the proposed method are provided. Finally, several three-dimensional benchmark problems are studied and results are compared with available literature. Lastly, the results indicate that the proposed method addresses pathological cases, exhibits better behavior in the presence of closely interacting fractures, and provides a viable strategy to robustly evolve embedded failure surfaces in 3D.

3D fracture↗

Machine Learning-Based Anomaly Detection for Load Forecasting Under Cyberattacks

Accurate load forecasting can create both economic and reliability benefits for power system operators. However, the cyberattack on load forecasting may mislead operators to make unsuitable operational decisions for the electricity delivery. To effectively and accurately detect these cyberattacks, this paper develops a machine learning-based anomaly detection (MLAD) methodology. First, load forecasts provided by neural networks are used to reconstruct the benchmark and scaling data by using the k-means clustering. Second, the cyberattack template is estimated by the naive Bayes classification based on the cumulative distribution function and statistical features of the scaling data. Finally, the dynamic programming is utilized to calculate both the occurrence and parameter of one cyberattack on load forecasting data. Here, a widely used symbolic aggregation approximation method is compared with the developed MLAD method. Numerical simulations on the publicly load data show that the MLAD method can effectively detect cyberattacks for load forecasting data with relatively high accuracy. Also, the robustness of MLAD is verified by thousands of attack scenarios based on Monte Carlo simulation.

97 MATHEMATICS AND COMPUTING↗

New Simulations for Ion-Production and Back-Bombardment in GaAs Photo-guns

GaAs-based DC high voltage photo-guns used at accelerators with extensive user programs must exhibit long photocathode operating lifetime. Achieving this goal represents a significant challenge for proposed high average current facilities that must operate at tens of milliamperes or more. Specifically, the operating lifetime is dominated by ion back-bombardment of the photocathode from ionized residual gas. While numerous experiments have been performed to characterize the operating lifetime under various conditions, detailed simulations of the ion back-bombardment mechanism that explains these experiments are lacking. Recently, a new user routine was implemented using the code General Particle Tracer (GPT) to simulate electron impact ionization of residual beam line gas and simultaneously track the incident electron, the ejected electron, and the newly formed ion. This new routine was benchmarked against analytical calculations and then applied to experiments performed at the CEBAF injector at the Thomas Jefferson National Accelerator Facility to study the effectiveness of limiting ions from entering the cathode-anode gap using a positively biased anode. These simulations were performed using detailed 3D field maps produced with CST Microwave Studio describing the photo-gun electrostatics. Discussion of the experiment and the application of this new GPT routine to model the experiments will be presented at the workshop.

Yoskowitz, Joshua↗

Modeling the Benchmark Active Control Technology Wind-Tunnel Model for Active Control Design Applications

This report describes the formulation of a model of the dynamic behavior of the Benchmark Active Controls Technology (BACT) wind tunnel model for active control design and analysis applications. The model is formed by combining the equations of motion for the BACT wind tunnel model with actuator models and a model of wind tunnel turbulence. The primary focus of this report is the development of the equations of motion from first principles by using Lagrange's equations and the principle of virtual work. A numerical form of the model is generated by making use of parameters obtained from both experiment and analysis. Comparisons between experimental and analytical data obtained from the numerical model show excellent agreement and suggest that simple coefficient-based aerodynamics are sufficient to accurately characterize the aeroelastic response of the BACT wind tunnel model. The equations of motion developed herein have been used to aid in the design and analysis of a number of flutter suppression controllers that have been successfully implemented.

Waszak, Martin R.↗

Transfer-AE: A novel autoencoder-based impact detection model for structural digital twin

Accurately detecting the location and intensity of impacts is crucial for ensuring structural safety. Currently, AI-based structural impact detection methods are widely used for their excellent detection accuracy. However, their generalization capability is limited by the scenarios present in the training data. Many complex and dangerous impact scenarios are difficult to conduct real-world experiments on to collect sufficient samples. To capture all impact scenarios and fully leverage the advantages of AI-based detection technologies, advanced methods involve combining real-world structural monitoring data with corresponding numerical models to construct digital twins. These methods continuously refine the created numerical models with limited real-world data and provide diverse impact scenarios through numerical model simulations. However, there are inevitable differences between digital models and physical models that are challenging to correct through mechanical means. This discrepancy in data distribution between the two models significantly hinders the application of digital twin technology in impact/event identification tasks. To address this challenge, this study proposes a novel model based on autoencoders, named Transfer-AE. Transfer-AE encodes the common features of digital twins in the latent space to bridge the uncertainty gap at a macro scale between numerical models and physical models and synchronously fits the magnitude and location of the impact load in the decoder. This enables consistent detection results for the same impact event, whether the sample comes from the numerical model or the physical model. Transfer-AE includes two operating modes: Mode 1 has a fixed computational complexity with stable inference speed, but the training cost and difficulty increase with data distribution. Mode 2's computational complexity increases with data distribution, but it has a fixed training cost and speed. In both cases involving the geodesic dome structure simulating a deep space habitat and the IASC-ASCE benchmark structure, Transfer-AE demonstrated the best performance in impact localization and quantification tasks compared to mainstream domain-adaptive transfer models.

Chengjia Han↗

The 2016 Edition of the ICSBEP Handbook

Over the past several decades, numerous experiments have been performed worldwide to support criticality safety. These experiments represent a significant investment in infrastructure, expertise, and cost, and are valuable resources of data for present and future research. These valuable assets provide the basis for recording, development, and validation of methods and nuclear data. If the experimental data are lost, the high cost to repeat many of these measurements may be prohibitive. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) was established to: 1. Identify a comprehensive set of critical benchmark data and, to the extent possible, verify the data; 2. Evaluate the data and quantify overall uncertainties through various types of sensitivity analyses; 3. Compile the data into a standardized format; 4. Perform calculations of each experiment with standard criticality safety codes; and 5. Formally document the work into a single source of verified benchmark critical data. Annually, contributors from around the world continue to collaborate in the evaluation and review of select benchmark experiments for inclusion in the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP Handbook). Further information regarding the ICSBEP, including highlighted criticality safety benchmark evaluations, can be found in the September and October 2003 editions of Nuclear Science and Engineering. Several new evaluations have been prepared for inclusion in the September 2016 edition of the ICSBEP Handbook. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

GPU acceleration of all-electron electronic structure theory using localized numeric atom-centered basis functions

We present an implementation of all-electron density-functional theory for massively parallel GPU-based platforms, using localized atom-centered basis functions and real-space integration grids. Special attention is paid to domain decomposition of the problem on non-uniform grids, which enables compute- and memory-parallel execution across thousands of nodes for real-space operations, e.g. the update of the electron density, the integration of the real-space Hamiltonian matrix, and calculation of Pulay forces. To assess the performance of our GPU implementation, we performed benchmarks on three different architectures using a 103-material test set. We find that operations which rely on dense serial linear algebra show dramatic speedups from GPU acceleration: in particular, SCF iterations including force and stress calculations exhibit speedups ranging from 4.5 to 6.6. For the architectures and problem types investigated here, this translates to an expected overall speedup between 3–4 for the entire calculation (including non-GPU accelerated parts), for problems featuring several tens to hundreds of atoms. Additional calculations for a 375-atom Bi2Se3 bilayer show that the present GPU strategy scales for large-scale distributed-parallel simulations.

42 ENGINEERING↗

Numerically exploring the 1D-2D dimensional crossover on spin dynamics in the doped Hubbard model

Using determinant quantum Monte Carlo (DQMC) simulations, we systematically study the doping dependence of the crossover from one to two dimensions and its impact on the magnetic properties of the Hubbard model. A square lattice of chains is used, in which the dimensionality can be tuned by varying the interchain coupling t ⊥ . The dynamical spin structure factor and static quantities, such as the static spin susceptibility and nearest-neighbor spin correlation function, are characterized in the one- and two-dimensional limits as a benchmark. When the dimensionality is tuned between these limits, the magnetic properties, while evolving smoothly from one to two dimensions, drastically change regardless of the doping level. This suggests that the spin excitations in the two-dimensional Hubbard model, even in the heavily doped case, cannot be explained using the spinon picture known from one dimension. In conclusion, the DQMC calculations are complemented by cluster perturbation theory studies to form a more complete picture of how the crossover occurs as a function of doping and how doped holes impact magnetic order.

36 MATERIALS SCIENCE↗

Evaluation of a nonlinear variational multiscale method for fluid transport problems

Diverse transport problems, especially those based on fluid flow models, are intrinsically multiscale and nonlinear, characteristics that often lead to intricate dynamics such as the development of instabilities and turbulence. Computational simulations that resolve all scales in these problems are often unfeasible, prompting to coarse-grained simulation strategies in which small-scale features are modeled instead of resolved. Variational Multiscale (VMS) methods, and particularly residual-based Large-Eddy Simulation (LES) approaches, have proven effective and robust for the coarse-grained simulation of complex transport problems. VMS methods avoid the assumption of separable nonlinearity and the reliance on empirical small-scale models by using a variational decomposition of scales together with a residual-based approximation of the small-scales. Evaluation of a nonlinear VMS approach, denoted as VMS n , is presented for the coarse-grained simulation of transient-advective-diffusive-reactive (TADR) transport problems arising from fluid flow models. In contrast to classical VMS approaches that neglect the effect of the small scales on the transport operator, VMS n treats the inter-dependence between large- and small-scales upfront. The treatment of inter-scale coupling involves the solution of a local algebraic nonlinear system describing the evolution of the small-scales. The VMS n approach is complemented with two algebraic approximations of the small-scales: one based on the main diagonal of the transport matrices and another that preserves transport fluxes and is suitable for generic TADR systems. The suitability of the VMS n approach for handling general TADR problems and regimes is evaluated with benchmark incompressible, compressible, and magnetohydrodynamic laminar flow problems, the incompressible Taylor-Green vortex flow, the turbulent free jet, and the two-temperature arc in crossflow. Furthermore, simulation results show that VMS n leads to minor improvements in accuracy with respect to the classical VMS for the laminar flow problems, but to significantly greater accuracy for the turbulent flows and the unsteady plasma flow problems, while using the same cohesive numerical formulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Simulating Sea-Ice Deformation in Viscous-Plastic Sea-Ice Models With CD-Grids

Linear kinematic features (LKFs) are found everywhere in the Arctic sea-ice cover. They are strongly localized deformations often associated with the formation of leads and pressure ridges. In viscous-plastic (VP) sea-ice models, the simulation of LKFs depends on several factors such as the grid resolution, the numerical solver convergence, and the placement of the variables on the mesh. In this study, we compare two recently proposed discretization with a CD-grid placement with respect to their ability to reproduce LKFs. The first (CD1) is based on a nonconforming finite element discretization, whereas the second (CD2) uses a conforming subgrid discretization. To analyze their resolution properties, we evaluate runs from different models (e.g., FESOM, MPAS) on a benchmark problem using quadrilateral, hexagonal and triangular meshes. Our findings show that the CD1 setup simulates more deformation structure than the CD2 setup. This highlights the importance of the type of spatial discretization for the simulation of LKFs. Due to the higher number of degrees of freedom, both CD-grids resolve more LKFs than traditional A, B, and C-grids at fixed mesh level. This is an advantage of the CD-grid approach, as high spatial mesh resolution is needed in VP sea-ice models to simulate LKFs.

54 ENVIRONMENTAL SCIENCES↗

RECONSTRUCTION OF THE CORONAL MAGNETIC FIELD USING THE CESE-MHD METHOD

We present a new implementation of the MHD relaxation method for reconstruction of the nearly force-free coronal magnetic field from a photospheric vector magnetogram. A new numerical MHD scheme is proposed to solve the full MHD equations by using the spacetime conservation-element and solution-element method. The bottom boundary condition is prescribed in a similar way as in the stress-and-relax method, by changing the transverse field incrementally to match the magnetogram, and other boundaries of the computational box are set by the nonreflecting boundary conditions. Applications to the well-known benchmarks for nonlinear force-free-field reconstruction, the Low and Lou force-free equilibria, validate the method and confirm its capability for future practical application, with observed magnetograms as inputs.

79 ASTRONOMY AND ASTROPHYSICS↗

Catalyst: Fast and flexible modeling of reaction networks

We introduce Catalyst.jl, a flexible and feature-filled Julia library for modeling and high-performance simulation of chemical reaction networks (CRNs). Catalyst supports simulating stochastic chemical kinetics (jump process), chemical Langevin equation (stochastic differential equation), and reaction rate equation (ordinary differential equation) representations for CRNs. Through comprehensive benchmarks, we demonstrate that Catalyst simulation runtimes are often one to two orders of magnitude faster than other popular tools. More broadly, Catalyst acts as both a domain-specific language and an intermediate representation for symbolically encoding CRN models as Julia-native objects. This enables a pipeline of symbolically specifying, analyzing, and modifying CRNs; converting Catalyst models to symbolic representations of concrete mathematical models; and generating compiled code for numerical solvers. Leveraging ModelingToolkit.jl and Symbolics.jl, Catalyst models can be analyzed, simplified, and compiled into optimized representations for use in numerical solvers. Finally, we demonstrate Catalyst’s broad extensibility and composability by highlighting how it can compose with a variety of Julia libraries, and how existing open-source biological modeling projects have extended its intermediate representation.

59 BASIC BIOLOGICAL SCIENCES↗

Computation of Turbulent Recirculating Flow in Channels, and for Impingement Cooling

Fully elliptic forms of the transport equations have been solved numerically for two flow configurations. The first is turbulent flow in a channel with transverse rectangular ribs, and the second is impingement cooling of a plane surface. Both flows are relevant to proposed designs for active cooling of hypersonic vehicles using supercritical hydrogen as the coolant. Flow downstream of an abrupt pipe expansion and of a backward-facing step were also solved with various near-wall turbulence models as benchmark problems. A simple form of periodicity boundary condition was used for the channel flow with transverse rectangular ribs. The effects of various parameters on heat transfer in channel flow with transverse ribs and in impingement cooling were investigated using the Yap modified Jones and Launder low Reynolds number k-epsilon turbulence model. For the channel flow, predictions were in adequate agreement with experiment for constant property flow, with the results for friction superior to those for heat transfer. For impingement cooling, the agreement with experiment was generally good, but the results suggest that improved modelling of the dissipation rate of turbulence kinetic energy is required in order to obtain improved heat transfer prediction, especially near the stagnation point. The k-epsilon turbulence model was used to predict the mean flow and heat transfer for constant and variable property flows. The effect of variable properties for channel flow was investigated using the same turbulence model, but comparison with experiment yielded no clear conclusions. Also, the wall function method was modified for use in the variable properties flow with a non-adiabatic surface, and an empirical model is suggested to correctly account for the behavior of the viscous sublayer with heating.

Chang, Byong Hoon↗

Spectroscopic Determination of the Physical Conditions in Hot Optically Thin Sources

The Astrophysics Plasma Emission Code and Database (APEC/APED), developed in part under this grant, have been upgraded to ATOMDB Version 1.3.1: and are now beginning to find widespread applications t o X-ray spectral data from Chandra and XMM-Newton (37 citations in published work, according to the ADS, plus numerous other conference and prepublication papers).ATOMDB is now linked through the Plasma Gate website: http://plasma-gate.weizmann.ac.il/DBfAPP.html. The major difference from Version 1.3.0 is that the new models naw ex- tend t o 50 keV rather than stopping at 10 keV. This means that ATOMDB can be used with redshifted observations. There are minor differences in emissivities due t o radiative recombination and cascades. Stellar coronae are being used to benchmark the atomic data in APED as part of the Emission Line Project. The models appear to be in good agreement with the observations for most of the strong lines; however, we have identified significant discrepancies in the 3s/3d line ratios not only for Fe XVII, but also for Fe XVIII and XIX. The Fe XVII problem has been known from solar observations, and is currently being tested under EBIT laboratory conditions by two groups. The Fe XVIII problem is substantially worse, but perhaps will shed light on the relevant underlying theoretical issues. Ming-Feng Gu has recently published new calculations, which we are comparing with APEC and with the obser- vations. His calculations appear to improve the emissivities of lines affected by cascades, but other problems remain.

Brickhouse, Nancy S.↗

Relativistic nuclear magnetic resonance J-coupling with ultrasoft pseudopotentials and the zeroth-order regular approximation

We present a method for the first-principles calculation of nuclear magnetic resonance (NMR) J-coupling in extended systems using state-of-the-art ultrasoft pseudopotentials and including scalar-relativistic effects. The use of ultrasoft pseudopotentials is allowed by extending the projector augmented wave (PAW) method of Joyce et al. [J. Chem. Phys. 127, 204107 (2007)]. We benchmark it against existing local-orbital quantum chemical calculations and experiments for small molecules containing light elements, with good agreement. Scalar-relativistic effects are included at the zeroth-order regular approximation level of theory and benchmarked against existing local-orbital quantum chemical calculations and experiments for a number of small molecules containing the heavy row six elements W, Pt, Hg, Tl, and Pb, with good agreement. Finally, {sup 1}J(P-Ag) and {sup 2}J(P-Ag-P) couplings are calculated in some larger molecular crystals and compared against solid-state NMR experiments. Some remarks are also made as to improving the numerical stability of dipole perturbations using PAW.

97 MATHEMATICS AND COMPUTING↗

An investigation of DTNS2D for use as an incompressible turbulence modelling test-bed

This paper documents an investigation of a two dimensional, incompressible Navier-Stokes solver for use as a test-bed for turbulence modelling. DTNS2D is the code under consideration for use at the Center for Modelling of Turbulence and Transition (CMOTT). This code was created by Gorski at the David Taylor Research Center and incorporates the pseudo compressibility method. Two laminar benchmark flows are used to measure the performance and implementation of the method. The classical solution of the Blasius boundary layer is used for validating the flat plate flow, while experimental data is incorporated in the validation of backward facing step flow. Velocity profiles, convergence histories, and reattachment lengths are used to quantify these calculations. The organization and adaptability of the code are also examined in light of the role as a numerical test-bed.

Steffen, Christopher J., Jr.↗