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Dirichlet-type absorbing boundary conditions for peridynamic scalar waves in two-dimensional viscous media
Construction of absorbing boundary conditions (ABCs) for nonlocal models is generally challenging, primarily due to the fact that nonlocal operators are commonly associated with volume constrained boundary conditions. Moreover, application of Fourier and Laplace transforms, which are essential for the majority of available methods for ABCs, to nonlocal models is complicated. In this paper, we propose a simple method to construct accurate ABCs for peridynamic scalar wave-type problems in viscous media. The proposed ABCs are constructed in the time and space domains and are of Dirichlet type. Consequently, their implementation is relatively simple, since no derivatives of the wave field are required. The proposed ABCs are derived at the continuum level, from a semi-analytical solution of the exterior domain using harmonic exponential basis functions in space and time (plane-wave modes). The numerical implementation is done using a meshfree collocation approach employed within a boundary layer adjacent to the interior domain boundary. The modes satisfy the peridynamic numerical dispersion relation, resulting in a compatible solution of the interior region (near-field) with that of the exterior region (far-field). The accuracy and stability of the proposed ABCs are demonstrated with several numerical examples in two-dimensional unbounded domains.
Peridynamic elastic waves in two-dimensional unbounded domains: Construction of nonlocal Dirichlet-type absorbing boundary conditions
The focus of this paper is on application of peridynamics (PD) to propagation of elastic waves in unbounded domains. We construct absorbing boundary conditions (ABCs) derived from a semi-analytical solution of the PD governing equation at the exterior region. This solution is made up of a finite series of plane waves, as fundamental solutions (modes), which satisfy the PD dispersion relations. The modes are adjusted to transmit the energy from the interior region (near field) to the exterior region (far field). The corresponding unknown coefficients of the series are found in terms of the displacement field at a layer of points adjacent to the absorbing boundary. This is accomplished through a collocation procedure at subregions (clouds) around each absorbing point. The proposed ABCs offer appealing advantages, which facilitate their application to PD. They are of Dirichlet-type, hence their implementation is relatively simple as no derivatives of the field variables are required. They are constructed in the time and space domains and thus application of Fourier and Laplace transforms, cumbersome for nonlocal models, is not required. At the discrete level, the modes satisfy the same numerical dispersion relations of the near field, which makes the far-field solution compatible with that of the near field. We scrutinize the performance of the proposed ABCs through several examples. So our investigation shows that the proposed ABCs perform stably in time with an appropriate level of accuracy even in problems characterized by highly-dispersive propagating waves, including crack propagation in semi-unbounded brittle solids.
Absorbing boundary conditions in material point method adopting perfectly matched layer theory
This study focuses on solving the numerical challenges of imposing absorbing boundary conditions for dynamic simulations in the material point method (MPM). To attenuate elastic waves leaving the computational domain, the current work integrates the Perfectly Matched Layer (PML) theory into the implicit MPM framework. The proposed approach introduces absorbing particles surrounding the computational domain that efficiently absorb outgoing waves and reduce reflections, allowing for accurate modeling of wave propagation and its further impact on geotechnical slope stability analysis. The study also includes several benchmark tests to validate the effectiveness of the proposed method, such as several types of impulse loading and symmetric and asymmetric base shaking. The conducted numerical tests also demonstrate the ability to handle large deformation problems, including the failure of elasto-plastic soils under gravity and dynamic excitations. The findings extend the capability of MPM in simulating continuous analysis of earthquake-induced landslides, from shaking to failure.
Dirichlet absorbing boundary conditions for classical and peridynamic diffusion-type models
Diffusion-type problems in (nearly) unbounded domains play important roles in various fields of fluid dynamics, biology, and materials science. The aim of this paper is to construct accurate absorbing boundary conditions (ABCs) suitable for classical (local) as well as nonlocal peridynamic (PD) diffusion models. The main focus of the present study is on the PD diffusion formulation. The majority of the PD diffusion models proposed so far are applied to bounded domains only. In this study, we propose an effective way to handle unbounded domains both with PD and classical diffusion models. For the former, we employ a meshfree discretization, whereas for the latter the finite element method (FEM) is employed. The proposed ABCs are time-dependent and Dirichlet-type, making the approach easy to implement in the available models. The performance of the approach, in terms of accuracy and stability, is illustrated by numerical examples in 1D, 2D, and 3D.
Extended particle absorber for efficient modeling of intense laser-solid interactions
Here, an extended thermal particle boundary condition is devised to more efficiently and accurately model laser–plasma interactions in overdense plasmas. Particle-in-cell simulations of such interactions require many particles per cell, and a large region of background plasma is often necessary to correctly mimic a semi-infinite plasma and avoid electron refluxing from a truncated plasma. For long-pulse lasers of many picoseconds, such constraints can become prohibitively expensive. Here, an extended particle boundary condition (absorber) is designed that instantaneously stops and re-emits energetic particles streaming toward the simulation boundary over a defined region, allowing sufficient time and space for a suitably cool return current to develop in the background plasma. Tunable parameters of the absorber are explained, and simulations using the absorber with a 3-ps laser are shown to accurately reproduce those of a causally separated boundary while requiring only 20% the number of particles.
Entanglement wedge reconstruction and the information paradox
When absorbing boundary conditions are used to evaporate a black hole in AdS/CFT, we show that there is a phase transition in the location of the quantum Ryu-Takayanagi surface, at precisely the Page time. The new RT surface lies slightly inside the event horizon, at an infalling time approximately the scrambling time β/2 π logS BH into the past. We can immediately derive the Page curve, using the Ryu-Takayanagi formula, and the Hayden-Preskill decoding criterion, using entanglement wedge reconstruction. Because part of the interior is now encoded in the early Hawking radiation, the decreasing entanglement entropy of the black hole is exactly consistent with the semiclassical bulk entanglement of the late-time Hawking modes, despite the absence of a firewall.By studying the entanglement wedge of highly mixed states, we can understand the state dependence of the interior reconstructions. A crucial role is played by the existence of tiny, non-perturbative errors in entanglement wedge reconstruction. Directly after the Page time, interior operators can only be reconstructed from the Hawking radiation if the initial state of the black hole is known. As the black hole continues to evaporate, reconstructions become possible that simultaneously work for a large class of initial states. Using similar techniques, we generalise Hayden-Preskill to show how the amount of Hawking radiation required to reconstruct a large diary, thrown into the black hole, depends on both the energy and the entropy of the diary. Finally we argue that, before the evaporation begins, a single, state-independent interior reconstruction exists for any code space of microstates with entropy strictly less than the Bekenstein-Hawking entropy, and show that this is sufficient state dependence to avoid the AMPSS typical-state firewall paradox.
Field–potential finite-difference time-domain (FiPo FDTD) technique for computational electromagnetics
Modeling light–matter interactions at the nanoscale requires accurate handling of coupled quantum and electromagnetic systems. This coupling requires information about the electric scalar potential Φ and the magnetic vector potential A, which are not typically calculated in standard computational electromagnetics implementations. To that end, we have developed a field–potential finite-difference time-domain (FiPo FDTD) algorithm, which solves a set of first-order equations for Φ and A alongside equations for the electric and magnetic fields E and H. The FiPo Basic code is essentially conventional FDTD, but with an added module that calculates the potentials. The FiPo Hybrid code self-consistently calculates both fields and potentials and is particularly suitable for coupling with quantum electronic transport solvers because it can be sourced by the potentials themselves. To terminate the domain and mimic infinite space, we have derived and implemented a convolutional perfectly matched layer (CPML) absorbing boundary condition for FiPo FDTD whose performance is on par with state-of-the-art CPMLs for standard FDTD. We present FiPo simulation results on several example systems.
Fast meta-solvers for 3D complex-shape scatterers using neural operators trained on a non-scattering problem
Three-dimensional target identification using scattering techniques requires high accuracy solutions and very fast computations for real-time predictions in some critical applications. We first train a deep neural operator (DeepONet) to solve wave propagation problems described by the Helmholtz equation in a domain without scatterers but at different wavenumbers and with a complex absorbing boundary condition. We then design two classes of fast meta-solvers by combining DeepONet with either relaxation methods, such as Jacobi and Gauss-Seidel, or with Krylov methods, such as GMRES and BiCGStab, using the trunk basis of DeepONet as a coarse-scale preconditioner. We leverage the spectral bias of neural networks to account for the lower part of the spectrum in the error distribution while the upper part is handled inexpensively using relaxation methods or fine-scale preconditioners. The meta-solvers are then applied to solve scattering problems with different shape of scatterers, at no extra training cost. We first demonstrate that the resulting meta-solvers are shape-agnostic, fast, and robust, whereas the standard standalone solvers may even fail to converge without the DeepONet. We then apply both classes of meta-solvers to scattering from a submarine, a complex three-dimensional problem. We achieve very fast solutions, especially with the DeepONet-Krylov methods, which require orders of magnitude fewer iterations than any of the standalone solvers.
Variational, stable, and self-consistent coupling of 3D electromagnetics to 1D transmission lines in the time domain
This work presents a new multiscale method for coupling the 3D Maxwell's equations to the 1D telegrapher's equations. While Maxwell's equations are appropriate for modeling complex electromagnetics in arbitrary-geometry domains, simulation cost for many applications (e.g. pulsed power) can be dramatically reduced by representing less complex transmission line regions of the domain with a 1D model. By assuming a transverse electromagnetic (TEM) ansatz for the solution in a transmission line region, we reduce the Maxwell's equations to the telegrapher's equations. Here, we propose a self-consistent finite element formulation of the fully coupled system that uses boundary integrals to couple between the 3D and 1D domains and supports arbitrary unstructured 3D meshes. Additionally, by using a Lagrange multiplier to enforce continuity at the coupling interface, we allow for an absorbing boundary condition to also be applied to non-TEM modes on this boundary. We demonstrate that this feature reduces non-physical reflection and ringing of non-TEM modes off of the coupling boundary. By employing implicit time integration, we ensure a stable coupling, and we introduce an efficient method for solving the resulting linear systems. We demonstrate the accuracy of the new method on two verification problems, a transient O-wave in a rectilinear prism and a steady-state problem in a coaxial geometry, and show the efficiency and weak scalability of our implementation on a cold test of the Z-machine MITL and post-hole convolute.
Electron dynamics in extended systems within real-time time-dependent density-functional theory
Due to a beneficial balance of computational cost and accuracy, real-time time-dependent density-functional theory has emerged as a promising first-principles framework to describe electron real-time dynamics. Here we discuss recent implementations around this approach, in particular in the context of complex, extended systems. Results include an analysis of the computational cost associated with numerical propagation and when using absorbing boundary conditions. Here we extensively explore the shortcomings for describing electron–electron scattering in real time and compare to many-body perturbation theory. Modern improvements of the description of exchange and correlation are reviewed. In this work, we specifically focus on the Qb@ll code, which we have mainly used for these types of simulations over the last years, and we conclude by pointing to further progress needed going forward.
Direct E&M Field Solver for a Plane Wave without Sources
A three dimensional direct field solver for the electric and magnetic fields using the Finite Difference Time Domain (FDTD) method is described. Example simulations using periodic and absorbing boundary conditions in a vacuum medium for a plane wave propagating in three dimensions are explored and are compared to theory.
Deep Learning Approaches to Surrogates for Solving the Diffusion Equation for Mechanistic Real-World Simulations
In many mechanistic medical, biological, physical, and engineered spatiotemporal dynamic models the numerical solution of partial differential equations (PDEs), especially for diffusion, fluid flow and mechanical relaxation, can make simulations impractically slow. Biological models of tissues and organs often require the simultaneous calculation of the spatial variation of concentration of dozens of diffusing chemical species. One clinical example where rapid calculation of a diffusing field is of use is the estimation of oxygen gradients in the retina, based on imaging of the retinal vasculature, to guide surgical interventions in diabetic retinopathy. Furthermore, the ability to predict blood perfusion and oxygenation may one day guide clinical interventions in diverse settings, i.e., from stent placement in treating heart disease to BOLD fMRI interpretation in evaluating cognitive function (Xie et al., 2019; Lee et al., 2020). Since the quasi-steady-state solutions required for fast-diffusing chemical species like oxygen are particularly computationally costly, we consider the use of a neural network to provide an approximate solution to the steady-state diffusion equation. Machine learning surrogates, neural networks trained to provide approximate solutions to such complicated numerical problems, can often provide speed-ups of several orders of magnitude compared to direct calculation. Surrogates of PDEs could enable use of larger and more detailed models than are possible with direct calculation and can make including such simulations in real-time or near-real time workflows practical. Creating a surrogate requires running the direct calculation tens of thousands of times to generate training data and then training the neural network, both of which are computationally expensive. Often the practical applications of such models require thousands to millions of replica simulations, for example for parameter identification and uncertainty quantification, each of which gains speed from surrogate use and rapidly recovers the up-front costs of surrogate generation. We use a Convolutional Neural Network to approximate the stationary solution to the diffusion equation in the case of two equal-diameter, circular, constant-value sources located at random positions in a two-dimensional square domain with absorbing boundary conditions. Such a configuration caricatures the chemical concentration field of a fast-diffusing species like oxygen in a tissue with two parallel blood vessels in a cross section perpendicular to the two blood vessels. To improve convergence during training, we apply a training approach that uses roll-back to reject stochastic changes to the network that increase the loss function. The trained neural network approximation is about 1000 times faster than the direct calculation for individual replicas. Because different applications will have different criteria for acceptable approximation accuracy, we discuss a variety of loss functions and accuracy estimators that can help select the best network for a particular application. We briefly discuss some of the issues we encountered with overfitting, mismapping of the field values and the geometrical conditions that lead to large absolute and relative errors in the approximate solution.
A boundary value “reservoir problem” and boundary conditions for multi-moment multifluid simulations of sheaths
Multifluid simulations of plasma sheaths are increasingly used to model a wide variety of problems in plasma physics ranging from global magnetospheric flows around celestial bodies to plasma–wall interactions in thrusters and fusion devices. For multifluid problems, accurate boundary conditions to model an absorbing wall that resolves a classical sheath remain an open research area. This work justifies the use of vacuum boundary conditions for absorbing walls to show comparable accuracy between a multifluid sheath and lower moments of a continuum-kinetic sheath.
Numerical study of heat transfer enhancement in laminar and turbulent flow in enhanced tubes with uniform and non-uniform thermal boundary conditions
Various types of tube enhancements have been proposed in order to increase heat transfer while minimizing any associated increases in pressure drop. This paper presents a numerical study of two different types of enhanced tubes: the relatively common twisted tape insert tube, and a novel tube with airfoil shaped pins on the inner surface. Each tube is studied in both the laminar and turbulent flow regime. In addition to the typical constant temperature and constant flux boundary conditions, a non-constant heat flux boundary condition is applied on one half of the tube, a situation which may be encountered when absorbing solar radiation. In general, each type of enhanced tube offers a thermal performance factor greater than unity at certain Re. In addition, the non-uniform heat flux boundary condition appears to function similarly as the uniform heat flux boundary condition.
Numerical study of heat transfer enhancement in laminar and turbulent flow in enhanced tubes with uniform and non-uniform thermal boundary conditions
Various types of tube enhancements have been proposed in order to increase heat transfer while minimizing any associated increases in pressure drop. This paper presents a numerical study of two different types of enhanced tubes: the relatively common twisted tape insert tube, and a novel tube with airfoil shaped pins on the inner surface. Each tube is studied in both the laminar and turbulent flow regime. In addition to the typical constant temperature and constant flux boundary conditions, a non-constant heat flux boundary condition is applied on one half of the tube, a situation which may be encountered when absorbing solar radiation. In general, each type of enhanced tube offers a thermal performance factor greater than unity at certain Re. In addition, the non-uniform heat flux boundary condition appears to function similarly as the uniform heat flux boundary condition.
Generalized master equation for particle transport in binary random media with renewal statistics
Particle transport in binary stochastic mixtures is classically modeled assuming Markovian or exponential mixing statistics but in many applications material memory invalidates the Markov assumption. For non-Markovian mixing characterized by alternating renewal processes, a transport-theoretic framework is presented that provides an exact description of transport in nonscattering random binary media with general non-exponential statistics. Our approach is to Markovianize the problem by augmenting the {material type, particle flux} state space with the age or distance from the last interface. A Chapman-Kolmogorov equation is formulated for the joint probability density of the material type, particle flux, and age, and subsequently reduced to a generalized Master equation (GME) in differential form. This constitutes the primary result of this work. A state-updating Monte Carlo algorithm consistent with the GME is developed and benchmarked against analytical solutions for multiple chord-length laws. For purely absorbing renewal statistical media, the GME reproduces analytical benchmarks for the equilibrium age distribution, interior mean/variance of material-conditioned fluxes, and boundary transmittance. Simulations further demonstrate that a Markov (exponential) approximation of non-exponential statistics can introduce large errors in transmittance and interior flux profiles. Lastly, the reintroduction of memory due to scattering is briefly addressed through heuristic considerations.
Molecular dynamics studies of helium bubble effects on grain boundary fracture vulnerabilities in an Fe 70 Ni 11 Cr 19 –1%H austenitic stainless steel
Comprehensive molecular dynamics tensile test simulations have been performed to study the delamination processes of seven different grain boundaries / cleavage planes (Σ1{111}, Σ3{111}, Σ5{100}, Σ7{111}, Σ9{411}, Σ11{311}, and R{100}/{411}) containing a helium bubble. Combinations of a variety of conditions are explored including different strain rates, system dimensions, bubble density, bubble radius, bubble pressure, and temperature. We found that in general, grain boundaries absorb less energies with decreasing strain rate but increasing bubble areal density, bubble pressure, bubble radius, and temperature. The propensity of grain boundary delamination is sensitive to grain boundary type: The random grain boundary R{100}/{411} is one of the most brittle boundaries whereas the Σ1{111} cleavage plane and the Σ3{111} twin boundary are two of the toughest boundaries. The sorted list of grain boundary fracture vulnerability obtained from our dynamic tensile test simulations differs from the one obtained from our decohesion energy calculations, confirming the important role of plastic deformation during fracture. Finally, detailed mechanistic analyses are performed to interpret the simulated results.