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At least 307 records · Page 17

Novel nonwetting solid-infused surfaces for superior fouling mitigation

Fouling is a ubiquitous issue in several environmental and energy applications. Here we introduce novel nonwetting solid-infused surfaces (SIS) with superior anti-fouling characteristics that are durable than conventional nonwetting surfaces in a dynamic flow environment. A systematic study is presented to elucidate the fouling mitigation performance of SIS in comparison to lubricant-infused surface (LIS) and conventional smooth surface. Copper tubes with SIS, LIS or smooth inner walls are fabricated and subjected to accelerated calcium sulfate fouling in a flow fouling experimental setup. Fouling on the various surface types is quantified in terms of asymptotic fouling resistance, and the fundamental morphological differences in the interactions of the foulant and the various surface types are analyzed. Based on a systematic sweep of the parameter combinations using design of experiments and Taguchi analysis, an analytical dependence of asymptotic fouling resistance on the governing parameters namely, Reynolds number, foulant concentration and temperature is derived. The analytical model is shown to predict the asymptotic fouling resistance to within 20% accuracy with a 95% confidence. In addition, for the first time, the effects of shear durability on the fouling mitigation performance of LIS vis-à-vis SIS are studied. It is shown that the novel nonwetting SIS offers a robust option for superior fouling mitigation over LIS in the long run.

42 ENGINEERING↗

Reactive particle-tracking solutions to a benchmark problem on heavy metal cycling in lake sediments

Geochemical systems are known to exhibit highly variable spatiotemporal behavior. This may be observed both in non-smooth concentration curves in space for a single sampling time and also in variability between samples taken from the same location at different times. However, most models that are designed to simulate these systems provide only single-solution smooth curves and fail to capture the noise and variability seen in the data. We apply a recently developed reactive particle-tracking method to a system that displays highly complex geochemical behavior. When the method is made to most closely resemble a corresponding Eulerian method, in its unperturbed form, we see near-exact match between solutions of the two models. More importantly, we consider two approaches for perturbing the model and find that the spatially-perturbed condition is able to capture a greater degree of the variability present in the data. This method of perturbation is a task to which particle methods are uniquely suited and Eulerian models are not well-suited. Additionally, because of the nature of the algorithm, noisy spatial gradients can be highly resolved by a large number of mobile particles, and this incurs negligible computational cost, as compared to expensive chemistry calculations.

54 ENVIRONMENTAL SCIENCES↗

Adaptive Activation Functions Accelerate Convergence in Deep and Physics-informed Neural Networks

We employ adaptive activation functions for regression in deep and physics-informed neural networks (PINNs) to approximate smooth and discontinuous functions as well as solutions of linear and nonlinear partial differential equations. In particular, we solve the nonlinear Klein-Gordon equation, which has smooth solutions, the nonlinear Burgers equation, which can admit high gradient solutions, and the Helmholtz equation. We introduce a scalable hyper-parameter in the activation function, which can be optimized to achieve best performance of the network as it changes dynamically the topology of the loss function involved in the optimization process. The adaptive activation function has better learning capabilities than the traditional one (fixed activation) as it improves greatly the convergence rate, especially at early training, as well as the solution accuracy. To better understand the learning process, we plot the neural network solution in the frequency domain to examine how the network captures successively different frequency bands present in the solution. We consider both forward problems, where the approximate solutions are obtained, as well as inverse problems, where parameters involved in the governing equation are identified. Our simulation results show that the proposed method is a very simple and effective approach to increase the efficiency, robustness and accuracy of the neural network approximation of nonlinear functions as well as solutions of partial differential equations, especially for forward problems. We theoretically prove that in the proposed method, gradient descent algorithms are not attracted to suboptimal critical points or local minima.

machine leaning, Bad minima, Inverse problems, Phy↗

Higher-order particle representation for particle-in-cell simulations

In this paper we present an alternative approach to the representation of simulation particles for unstructured electrostatic and electromagnetic PIC simulations. In our modified PIC algorithm we represent particles as having a smooth shape function limited by some specified finite radius, r 0 . A unique feature of our approach is the representation of this shape by surrounding simulation particles with a set of virtual particles with delta shape, with fixed offsets and weights derived from Gaussian quadrature rules and the value of r 0 . As the virtual particles are purely computational, they provide the additional benefit of increasing the arithmetic intensity of traditionally memory bound particle kernels. The modified algorithm is implemented within Sandia National Laboratories' unstructured EMPIRE-PIC code, for electrostatic and electromagnetic simulations, using periodic boundary conditions. We show results for a representative set of benchmark problems, including electron orbit, a transverse electromagnetic wave propagating through a plasma, numerical heating, and a plasma slab expansion. In this work, good error reduction across all of the chosen problems is achieved as the particles are made progressively smoother, with the optimal particle radius appearing to be problem-dependent.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A short note on the accuracy of the discontinuous Galerkin method with reentrant faces

In this work, we study the convergence of the discontinuous Galerkin (DG) method applied to the advection–reaction equation on meshes with reentrant faces. On such meshes, the upwind numerical flux is not smooth, and so the numerical integration of the resulting face terms can only be expected to be first-order accurate. Despite this inexact integration, we prove that the DG method converges with order $\mathscr{O}$(h p+1/2 ), which is the same rate as in the case of exact integration. Consequently, specialized quadrature rules that accurately integrate the non-smooth numerical fluxes are not required for high-order accuracy. These results are numerically corroborated on examples of linear advection and discrete ordinates transport equations.

97 MATHEMATICS AND COMPUTING↗

A coupled discontinuous Galerkin-Finite Volume framework for solving gas dynamics over embedded geometries

Herein, we present a computational framework for solving the equations of inviscid gas dynamics using structured grids with embedded geometries. The novelty of the proposed approach is the use of high-order discontinuous Galerkin (dG) schemes and a shock-capturing Finite Volume (FV) scheme coupled via an hp adaptive mesh refinement (hp-AMR) strategy that offers high-order accurate resolution of the embedded geometries. The hp-AMR strategy is based on a multi-level block-structured domain partition in which each level is represented by block-structured Cartesian grids and the embedded geometry is represented implicitly by a level set function. The intersection of the embedded geometry with the grids produces the implicitly-defined mesh that consists of a collection of regular rectangular cells plus a relatively small number of irregular curved elements in the vicinity of the embedded boundaries. High-order quadrature rules for implicitly-defined domains enable high-order accuracy resolution of the curved elements with a cell-merging strategy to address the small-cell problem. The hp-AMR algorithm treats the system with a second-order finite volume scheme at the finest level to dynamically track the evolution of solution discontinuities while using dG schemes at coarser levels to provide high-order accuracy in smooth regions of the flow. On the dG levels, the methodology supports different orders of basis functions on different levels. The space-discretized governing equations are then advanced explicitly in time using high-order Runge-Kutta algorithms. Numerical tests are presented for two-dimensional and three-dimensional problems involving an ideal gas. The results are compared with both analytical solutions and experimental observations and demonstrate that the framework provides high-order accuracy for smooth flows and accurately captures solution discontinuities.

97 MATHEMATICS AND COMPUTING↗

A Moving Embedded Boundary Approach for the Compressible Navier-Stokes Equations in a Block-Structured Adaptive Refinement Framework

A computational technique has been developed to perform compressible flow simulations involving moving boundaries using an embedded boundary approach within the block-structured adaptive mesh refinement (SAMR) framework of AMReX [1], [91], [92]. We leverage the SAMR capability to obtain quantitatively accurate results whilst using robust, second-order finite volume schemes. A conservative, unsplit, cut-cell approach is utilized and a ghost-cell approach is developed for computing the flux on the moving, embedded boundary faces. A third-order least-squares formulation has been developed to compute the wall velocity gradients, and was found to significantly improve the performance of the solver in terms of the quantitative comparison of surface quantities such as the skin friction coefficient. Various test cases are performed to validate the method, and compared with analytical, experimental, and other numerical results in literature. Inviscid and viscous test cases are performed that span a wide regime of flow speeds - acoustic (harmonically pulsating sphere), smooth flows (expansion fan created by a receding piston) and flows with shocks (shock-cylinder interaction, shock-wedge interaction, pitching NACA 0012 airfoil and shock-cone interaction). A closed system with moving boundaries - an oscillating piston in a cylinder, showed that the percentage error in mass within the system decreases with refinement, demonstrating that the numerical scheme is conservative with grid refinement, but is not discretely conservative. Viscous test cases involve that of a horizontally moving cylinder at Re = 40, an inline oscillating cylinder at Re = 100, and a transversely oscillating cylinder at Re = 185. The judicious use of adaptive mesh refinement with appropriate refinement criteria to capture the regions of interest leads to well-resolved flow features, and good quantitative comparison is observed with the results available in literature.

adaptive refinement↗

A family of independent Variable Eddington Factor methods with efficient preconditioned iterative solvers

We present a family of discretizations for the Variable Eddington Factor (VEF) equations that have high-order accuracy on curved meshes and efficient preconditioned iterative solvers. The VEF discretizations are combined with the Discontinuous Galerkin transport discretization from to form effective high-order, linear transport methods. The VEF discretizations are derived by extending the unified analysis of Discontinuous Galerkin methods for elliptic problems presented by Arnold et al. to the VEF equations. This framework is used to define analogs of the interior penalty, second method of Bassi and Rebay, minimal dissipation local Discontinuous Galerkin, and continuous finite element methods. The analysis of subspace correction preconditioners, which use a continuous operator to iteratively precondition the discontinuous discretization, is extended to the case of the non-symmetric VEF system. Numerical results demonstrate that the VEF discretizations have arbitrary-order accuracy on curved meshes, preserve the thick diffusion limit, and are effective on a proxy problem from thermal radiative transfer in both outer transport iterations and inner preconditioned linear solver iterations. We demonstrate that the VEF solution converges to the S N transport solution as the mesh is refined on both problems with smooth and non-smooth behavior in angle. Parallel performance studies show that the interior penalty VEF discretization's linear solve weak scales out to 1024 processors and strong scales well on a single node. Particular attention is paid to the parallel performance of the VEF algorithm when used in combination with a parallel block Jacobi transport sweep.

97 MATHEMATICS AND COMPUTING↗

On the design of stable, consistent, and conservative high-order methods for multi-material hydrodynamics

Obtaining stable and high-order numerical solutions for multi-material hydrodynamics is an open challenge. Although slope limiters are widely used to maintain monotonicity near discontinuities, typical limiting procedures violate closure laws at the discrete level when applied to multi-material hydrodynamics equations. Due to this, the high-order expansions of quantities related by the closure laws are no longer consistent. The commonly observed symptom of this consistency-violation is that the numerical method fails to maintain constant pressure and velocity across material interfaces. This leads to sub-optimal convergence rates for smooth multi-material problems as well. Specialized limiting procedures that satisfy consistency while maintaining conservation need to be developed for such equations. A novel procedure that re-instates consistency into slope-limited high-order discretizations applied to the multi-material hydrodynamics equations is presented here. Using simple examples, it is demonstrated that the presented method satisfies closure laws at the discrete level, while maintaining conservative properties of the high-order method. Furthermore, this procedure involves a projection step which relies on the compact basis of the underlying spatial discretization, i.e. for discontinuous schemes (viz. DG and FV) the projection is local, and does not involve global matrix solves. Comparisons with conventional approaches emphasizes the necessity of the consistent closure-law preserving limiting approach, in order to maintain design order of accuracy for smooth multi-material problems.

36 MATERIALS SCIENCE↗

A block-spectral adaptive H-/$p$-refinement strategy for shock-dominated problems

An adaptive H-/p-refinement strategy using a novel sensor is devised and tested in a block-spectral compressible Euler code equipped with adaptive-mesh refinement (AMR) and high-order flux-reconstruction numerics. At each Gauss quadrature point (or solution point) within each spectral block (or mesh element) the discrete velocity jump ΔU = ∂U/∂y 1 Δy 1 + ∂V/∂y 2 Δy 2 + ∂W/∂y 3 Δy 3 is calculated and normalized by the local speed of sound, a. Here, the grid spacing, Δx i , is calculated in each direction as the distance between auxiliary Gauss-Lobatto points, staggered relative to the solution points. The polynomial order is increased from p = 0 to p = p max in regions of weak compression, (ΔU/a) crit < ΔU/a < 0 and kept at p = p max in regions of flow expansion ΔU/a ≥ 0, while staying at the H = 0 base mesh level. Regions experiencing strong compressions, i.e. ΔU/a < (ΔU/a) crit , are H-refined up to H = H max where H max is applied at the location of maximum compression, ΔU/a = min(ΔU/a) in the domain, while keeping p = 0 to guarantee robustness and monotonicity of the solution in the H refined region. The critical value of (ΔU/a) crit = -0.06 is found to effectively separate smooth and non-smooth solution regions, supported by a 1D detonation initiation test case in ideal gas and a shock-to-detonation transition in high explosives. Using this value, the Sod shock tube, Shu-Osher problem, double Mach reflection and a 2D detonation in a high-explosive are simulated with the proposed adaptive H-/p-refinement. In the Sod shock tube case, p-refinement resolves the (weak) contact discontinuity while H-refinement enhances the grid resolution in the shock exploiting the monotonicity of the p = 0 reconstruction. For the Shu-Osher problem, p-refinement captures the small-scale oscillations trailing the shock that would be otherwise attenuated, while H-refinement triggered by the ΔU-sensor appropriately tracks the shock. In the double Mach reflection problem, H-refinement confines the numerical diffusion around the reflected shock while p-refinement recaptures many physical features trailing the shock. Finally, in the 2D high-explosive detonation case, H-refinement follows the leading shock and resolves the curvature of the detonation wave, while p-refinement adds resolution to the trailing reaction zone. Finally, the proposed methodology is tested in a detonation-wave propagation test case in high-explosives with numerical predictions comparing favorably against experiments.

97 MATHEMATICS AND COMPUTING↗

Enabling probabilistic learning on manifolds through double diffusion maps

Here, we present a generative learning framework for probabilistic sampling that extends Probabilistic Learning on Manifolds (PLoM), which is designed to generate statistically consistent realizations of a random vector in a finite-dimensional Euclidean space, informed by a (representative) set of observations. In its original form, PLoM constructs a reduced-order probabilistic model by combining three main components: (a) kernel density estimation to approximate the underlying probability measure, (b) Diffusion Maps to characterize the manifold of the data, and (c) a reduced-order Itô Stochastic Differential Equation (ISDE) to sample from the learned distribution. However, its sampling dynamics are posed in the ambient space and the retained number of reduced coordinates is chosen by projection-reconstruction error. In practice, this often (i) requires more coordinates than the data’s intrinsic dimension to achieve stable sampling and (ii) lacks a smooth, basis-independent lifting back to the data domain; moreover, standard Diffusion Maps emphasize harmonic eigenfunctions and can miss non-harmonic latent structure. We address these limitations by decoupling geometry learning from sampling: a first Diffusion Maps pass identifies non-harmonic coordinates on which we formulate a full-order ISDE directly in the latent space, while Double Diffusion Maps captures multiscale geometric features and Geometric Harmonics (GH) learns a smooth lifting map to the ambient variables that is independent of the particular diffusion basis. This hybrid design preserves the system’s dynamical richness with a compact geometric representation and enables principled out-of-sample inference. The effectiveness and robustness of the proposed method are illustrated through two numerical studies: one based on data generated from two-dimensional Hermite polynomial functions and another based on high-fidelity simulations of a detonation wave in a reactive flow.

Double diffusion maps↗

An efficient level set method for tracking many materials

Here, we present an efficient level set method to track an arbitrary number of materials. The algorithm is optimal in the sense that it only needs to store a single unsigned distance-like function and a single integer indicator function, independent of the number of materials or distinct regions being tracked. Furthermore, for smooth velocity fields and smooth interface shape, arbitrarily high order solutions can be demonstrated. For interfaces that are or become kinked, the solution is limited to second-order convergence rates in the L 1 norm and first-order in the L ∞ norm.

97 MATHEMATICS AND COMPUTING↗

Epitaxial columnar growth of strain-free antiferromagnetic Weyl semimetal Mn 3 Sn on wurtzite c -plane GaN/Al 2 O 3 (0001)

Weyl semimetal thin films with excellent crystalline quality are of great interest for antiferromagnetic spintronics. Mn 3 Sn is one Weyl semimetal with great properties and promise for exciting science and applications. It has proven very challenging, however, to grow Mn 3 Sn thin films with smooth surfaces, negligible strain, and excellent crystallinity. In this work, we discuss the successful preparation of epitaxial Mn 3 Sn (0001)-oriented thin films via molecular beam epitaxial growth on c -plane wurtzite GaN which was grown by MBE on Al 2 O 3 (0001). We present the reflection high energy electron diffraction analysis along with x-ray diffraction in order to demonstrate the crystalline quality of the film, and we give atomic models to explain the epitaxial orientation relationships between the crystal lattices of the substrate, GaN layer, and Mn 3 Sn layer. Importantly, we discuss the film lattice parameters as compared to expected values, demonstrating negligible strain both in-plane and out-of-plane . Atomic force microscopy reveals an epitaxial columnar growth mode characterized by flat-top-mesa islands, while scanning tunneling microscopy shows the atomically smooth surfaces of the mesa-top structures. Finally, Rutherford backscattering informs the stoichiometry of the film as well as the layer thicknesses.

Chiral antiferromagnetic material↗

Computer-controlled finishing via dynamically constraint position-velocity-time scheduler

In a Computer Numerical Controlled (CNC) finishing process, the target material removal from an optical surface is guided by the convolution between the influence function of a machine tool and its dwell time at certain points over the surface. To reduce dynamics stressing and increase machining efficiency, the dwell time must be converted to varying velocities, which are the actual inputs to the machine tool controller. Conventionally, the conversion assumed constant acceleration and relied on linear motion interpolation, which caused discontinuities in velocities. This unsmooth motion affects the material removal distribution, and, thus, the accuracy of the finished surface shape. Many modern CNC machines support the smoother, cubic-polynomial interpolated Position-Velocity-Time (PVT) motion mode; however, the conventional scheduler may fail to provide suitable velocities for the PVT. Here in this study answers this challenge by proposing a novel PVT-based velocity scheduler that achieves smooth motion while considering CNC dynamic limits. Firstly, the principle of the PVT is explained, and the PVT-based velocity scheduler is formulated. Secondly, a quadratic programming is used to optimize the velocities by imposing the CNC dynamic constraints and the C 1 continuities (zeroth and first derivatives are continuous) simultaneously. Thirdly, the smoothness and accuracy of the scheduled velocities are studied on different kinds of tool paths via simulation. Finally, a sub-0.3 nm level surface finishing experiment using ion beam figuring is demonstrated to verify the feasibility of the proposed method. The PVT-based scheduler and simulator code is open-sourced.

36 MATERIALS SCIENCE↗

ICP etching of GaN microstructures in a Cl 2 –Ar plasma with subnanometer-scale sidewall surface roughness

In this work, substrate temperature, RF power, and ICP power were investigated for their effects on GaN micropillar sidewall roughness and etch characteristics. Elevated substrate temperature was shown to improve the sidewall etch morphology at low RF powers (reduced physical bombardment) and low ICP powers (lower plasma densities). Increased lateral etching is observed with both increased ICP power and substrate temperature, which both act to increase the chemical component of the etch. Etch conditions with a high chemical driving force resulted in faceting along the a-plane on the sidewalls. This faceting produced extremely smooth surfaces with root-meansquare roughness (R q ) as low as 0.20 nm which is comparable to typical epitaxy-ready surfaces and smaller than the a-plane lattice spacing of 0.3186 nm. The smooth surfaces produced in this study enable possibilities for laser facets or for new device structures that require high quality surfaces for GaN regrowth.

36 MATERIALS SCIENCE↗

Infinitely rugged intra-cage potential energy landscape in metallic glasses caused by many-body interaction

The absence of translational symmetry in glassy materials poses a significant challenge in establishing effective structure-property relationships in real space. Consequently, the potential energy landscape (PEL) in phase space is widely utilized to comprehend the complex phenomena in glasses. The classical PEL features a two-scale profile comprising mega-basins and sub-basins, corresponding to α-relaxations (e.g. glass transition) and β-relaxations (e.g. local cage-breaking atomic rearrangements), respectively. Recent studies, however, reveal that sub-basins are not smooth and contain finer structures, the origins of which remain elusive. Here we probe the smoothness of sub-basin bottoms in glasses' PEL by introducing small intra-cage cyclic loading and then measuring the net changes in atomic-level stresses. Compared to glasses with pair interaction, glasses with many-body interaction exhibit orders-of-magnitude larger and loading-dependent stress changes even before the first cage-breaking event takes place, which reflect much more feature-rich sub-basins. We further demonstrate this stark contrast stems from the spatial distribution of individual atom's constraining force field. Specifically, at vanishing perturbations, many-body interactions disrupt the positive-definite synchrony in energy variations of the perturbed atom and the whole system, causing inherently less confined atomic responses and infinitely rugged sub-basins. The implications of these findings for the selective addition or removal of fine structures in the PEL and the subsequent tuning of glassy materials' responses to external stimuli are also explored.

36 MATERIALS SCIENCE↗

Electropolishing parameters study for surface smoothening of low-$\beta$650 MHz five-cell niobium superconducting radio frequency cavity

Electropolishing (EP) is applied to niobium (Nb) superconducting radio frequency (SRF) cavities, which are used in particle accelerators for their surface treatment. The EP process for 1.3 GHz cavities has been extensively studied earlier. In this work, a parametric study on EP of low-β (0.61) 650 MHz Nb SRF cavities (LB650), which will be used in pre-production cryomodule for proton improvement plan-II (PIP-II) linear accelerator, was conducted to determine adequate EP conditions for attaining a smooth surface of the cavities. EP performed with the standard parameters and an initial cathode (cathode-I) having a cathode surface area of ~5% of the cavity surface area yielded a rough equator surface of the cavity. The grain step height on the equator weld position was measured to be ~ 32 μm. The rough surface was attributed to preferential grain etching confirmed by a polarization curve showing a linear relationship between the EP current and voltage and the absence of the current plateau region. The cathode was modified to make its surface area twice that of cathode-I. The modified cathode (cathode-M) provided a current plateau region in the corresponding I-V curves measured at different cavity temperatures. The onset voltage for the plateau was found to be higher at higher cavity temperatures. Here this study revealed that even with cathode-M, the standard 18 V was low for EP of such large-sized cavities when the cavity temperature was 18 °C. EP performed at a higher voltage of 22–24.5 V with cathode-M yielded a smooth surface with a grain step height of only 0.6 μm. The applied EP conditions also improved removal uniformity along the cavity length. In contrast to the cavity treated with cathode-I, the cavities treated with cathode-M achieved a significantly higher accelerating gradient (E acc ) in vertical tests conducted in a cryostat at 2 K. The modified EP was found efficient to produce the cavities that achieved E acc of 22.4 MV/m, required by PIP II project in the baseline RF tests, to qualify for further surface processing used to enhance their quality factors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

An Open-Source Virtual Testbed for a Real Net-Zero Energy Community

Net zero energy communities (NZECs) are critical to ensure sustainability and resilience of modernized power systems. System modeling helps overcome technical challenges in designing and operating NZECs. In this paper, we present the modeling work based on a real NZEC. Two sets of models are developed: higher-fidelity physics-based models considering the interaction between subsystems of the studied NZEC and capturing fast-dynamics; and lower-fidelity data-driven models requiring less resource to establish and/or run. All models are validated against measurements from this real NZEC. In addition, we create a simulation framework which streamlines the processes for simulation and thus allows using developed models to form a virtual testbed. To demonstrate the usage of the virtual testbed, a case study is conducted where a building-to-grid integration control is evaluated via simulation. The evaluation results suggest that the tested control significantly smooths the power draw of the studied community and doesn’t sacrifice the thermal comfort to a great extent.

Huang, Sen↗