A Jacobian-free Newton–Krylov algorithm for compressible turbulent fluid flows

Despite becoming increasingly popular in many branches of computational physics, Jacobian-free Newton–Krylov (JFNK) methods have not become the approach of choice in the solution of the compressible Navier–Stokes equations for turbulent aerodynamic flows. To a degree, this is related to some subtle aspects of JFNK methods that are not well understood, and, if poorly handled, can lead to inefficient and unreliable performance. These are described here, along with strategies for addressing them, leading to an efficient JFNK algorithm for turbulent aerodynamic flows applicable to multi-block structured grids and a one-equation turbulence model. Development of globalization strategies for field-equation turbulence models represents one of the key contributions of the paper. Numerous examples of subsonic and transonic flows over single and multi-element airfoils are presented in order to demonstrate the efficiency and reliability of the algorithm. In addition, a number of guidelines are presented to aid in diagnosing problems with JFNK algorithms.     

Improving the numerical convergence of viscous-plastic sea ice models with the Jacobian-free Newton–Krylov method

We have implemented the Jacobian-free Newton–Krylov (JFNK) method to solve the sea ice momentum equation with a viscous-plastic (VP) formulation. The JFNK method has many advantages: the system matrix (the Jacobian) does not need to be formed and stored, the method is parallelizable and the convergence can be nearly quadratic in the vicinity of the solution. The convergence rate of our JFNK implementation is characterized by two phases: an initial phase with slow convergence and a fast phase for which the residual norm decreases significantly from one Newton iteration to the next. Because of this fast phase, the computational gain of the JFNK method over the standard solver used in existing VP models increases with the required drop in the residual norm (termination criterion). The JFNK method is between 3 and 6.6 times faster (depending on the spatial resolution and termination criterion) than the standard solver using a preconditioned generalized minimum residual method. Resolutions tested in this study are 80, 40, 20 and 10 km. For a large required drop in the residual norm, both JFNK and standard solvers sometimes do not converge. The failure rate for both solvers increases as the grid is refined but stays relatively small (less than 2.3% of failures). With increasing spatial resolution, the velocity gradients (sea ice deformations) get more and more important. Nonlinear solvers such as the JFNK method tend to have difficulties when there are such sharp structures in the solution. This lack of robustness of both solvers is however a debatable problem as it mostly occurs for large required drops in the residual norm. Furthermore, when it occurs, it usually affects only a few grid cells, i.e., the residual is small for all the velocity components except in very localized regions. Globalization approaches for the JFNK solver, such as the line search method, have not yet proven to be successful. Further investigation is needed.     

A comparison of the Jacobian-free Newton–Krylov method and the EVP model for solving the sea ice momentum equation with a viscous-plastic formulation: A serial algorithm study

Numerical convergence properties of a recently developed Jacobian-free Newton–Krylov (JFNK) solver are compared to the ones of the widely used EVP model when solving the sea ice momentum equation with a Viscous-Plastic (VP) formulation. To do so, very accurate reference solutions are produced with an independent Picard solver with an advective time step of 10 s and a tight nonlinear convergence criterion on 10, 20, 40, and 80-km grids. Approximate solutions with the JFNK and EVP solvers are obtained for advective time steps of 10, 20 and 30 min. Because of an artificial elastic term, the EVP model permits an explicit time-stepping scheme with a relatively large subcycling time step. The elastic waves excited during the subcycling are intended to damp out and almost entirely disappear such that the approximate solution should be close to the VP solution. Results show that residual elastic waves cause the EVP approximate solution to have notable differences with the reference solution and that these differences get more important as the grid is refined. Compared to the reference solution, additional shear lines and zones of strong convergence/divergence are seen in the EVP approximate solution. The approximate solution obtained with the JFNK solver is very close to the reference solution for all spatial resolutions tested.     

Implementation of the Jacobian-free Newton–Krylov method for solving the first-order ice sheet momentum balance

We have implemented the Jacobian-free Newton–Krylov (JFNK) method for solving the first-order ice sheet momentum equation in order to improve the numerical performance of the Glimmer-Community Ice Sheet Model (Glimmer-CISM), the land ice component of the Community Earth System Model (CESM). Our JFNK implementation is based on significant re-use of existing code. For example, our physics-based preconditioner uses the original Picard linear solver in Glimmer-CISM. For several test cases spanning a range of geometries and boundary conditions, our JFNK implementation is 1.8–3.6 times more efficient than the standard Picard solver in Glimmer-CISM. Importantly, this computational gain of JFNK over the Picard solver increases when refining the grid. Global convergence of the JFNK solver has been significantly improved by rescaling the equation for the basal boundary condition and through the use of an inexact Newton method. While a diverse set of test cases show that our JFNK implementation is usually robust, for some problems it may fail to converge with increasing resolution (as does the Picard solver). Globalization through parameter continuation did not remedy this problem and future work to improve robustness will explore a combination of Picard and JFNK and the use of homotopy methods.     

A high-order accurate unstructured finite volume Newton–Krylov algorithm for inviscid compressible flows

A fast implicit Newton–Krylov finite volume algorithm has been developed for high-order unstructured steady-state computation of inviscid compressible flows. The matrix-free generalized minimal residual (GMRES) algorithm is used for solving the linear system arising from implicit discretization of the governing equations, avoiding expensive and complex explicit computation of the high-order Jacobian matrix. The solution process has been divided into two phases: start-up and Newton iterations. In the start-up phase an approximate solution with the general characteristics of the steady-state flow is computed by using a defect correction procedure. At the end of the start-up phase, the linearization of the flow field is accurate enough for steady-state solution, and a quasi-Newton method is used, with an infinite time step and very rapid convergence. A proper limiter implementation for efficient convergence of the high-order discretization is discussed and a new formula for limiting the high-order terms of the reconstruction polynomial is introduced. The accuracy, fast convergence and robustness of the proposed high-order unstructured Newton–Krylov solver for different speed regimes is demonstrated for the second, third and fourth-order discretization. The possibility of reducing computational cost required for a given level of accuracy by using high-order discretization is examined.     

Fast algebra algorithm of shape-from-shading with specular reflectance

Shape-from-shading (SFS) is to reconstruct three-dimensionai (3D) shape from a single gray image,which is an important problem in computer vision.We propose a novel SFS method based on hybrid reflection model which contains both diffuse reflectance and specular reflectance.The intensity gradient of image is in the direction that the shape of surface changes most,so we use directional derivative of the reflectance map as parts of objective function.When discrete characteristic of digital images is considered,finite difference approximates differential operator.So the reflectance map equation described by a partial differential equation (PDE) turns into an algebra equation about the unknown surface height correspondingly.Using iterative numeric computation,a new SFS method is gained.Experiments on synthesis and real images show that the proposed SFS method is accurate and fast.     

Solution of the equation of radiative transfer using a Newton–Krylov approach and adaptive mesh refinement

The discrete ordinates method (DOM) and finite-volume method (FVM) are used extensively to solve the radiative transfer equation (RTE) in furnaces and combusting mixtures due to their balance between numerical efficiency and accuracy. These methods produce a system of coupled partial differential equations which are typically solved using space-marching techniques since they converge rapidly for constant coefficient spatial discretization schemes and non-scattering media. However, space-marching methods lose their effectiveness when applied to scattering media because the intensities in different directions become tightly coupled. When these methods are used in combination with high-resolution limited total-variation-diminishing (TVD) schemes, the additional non-linearities introduced by the flux limiting process can result in excessive iterations for most cases or even convergence failure for scattering media. Space-marching techniques may also not be quite as well-suited for the solution of problems involving complex three-dimensional geometries and/or for use in highly-scalable parallel algorithms. A novel pseudo-time marching algorithm is therefore proposed herein to solve the DOM or FVM equations on multi-block body-fitted meshes using a highly scalable parallel-implicit solution approach in conjunction with high-resolution TVD spatial discretization. Adaptive mesh refinement (AMR) is also employed to properly capture disparate solution scales with a reduced number of grid points. The scheme is assessed in terms of discontinuity-capturing capabilities, spatial and angular solution accuracy, scalability, and serial performance through comparisons to other commonly employed solution techniques. The proposed algorithm is shown to possess excellent parallel scaling characteristics and can be readily applied to problems involving complex geometries. In particular, greater than 85% parallel efficiency is demonstrated for a strong scaling problem on up to 256 processors. Furthermore, a speedup of a factor of at least two was observed over a standard space-marching algorithm using a limited scheme for optically thick scattering media. Although the time-marching approach is approximately four times slower for absorbing media, it vastly outperforms standard solvers when parallel speedup is taken into account. The latter is particularly true for geometrically complex computational domains.     

Computation of invariant tori by Newton–Krylov methods in large-scale dissipative systems

A method to compute invariant tori in high-dimensional systems, obtained as discretizations of PDEs, by continuation and Newton–Krylov methods is described. Invariant tori are found as fixed points of a generalized Poincaré map so that the dimension of the system of equations to be solved is that of the original system. Due to the dissipative nature of the problems studied, the convergence of the linear solvers is extremely fast. The computation of periodic orbits inside the Arnold’s tongues is also considered. Thermal convection of a binary mixture of fluids, in a rectangular cavity, has been used to test the method.     

Fast Fourier single-pixel imaging based on Sierra–Lite dithering algorithm

The single-pixel imaging(SPI) technique is able to capture two-dimensional(2 D) images without conventional array sensors by using a photodiode. As a novel scheme, Fourier single-pixel imaging(FSI) has been proven capable of reconstructing high-quality images. Due to the fact that the Fourier basis patterns(also known as grayscale sinusoidal patterns)cannot be well displayed on the digital micromirror device(DMD), a fast FSI system is proposed to solve this problem by binarizing Fourier pattern through a dithering algorithm. However, the traditional dithering algorithm leads to low quality as the extra noise is inevitably induced in the reconstructed images. In this paper, we report a better dithering algorithm to binarize Fourier pattern, which utilizes the Sierra–Lite kernel function by a serpentine scanning method. Numerical simulation and experiment demonstrate that the proposed algorithm is able to achieve higher quality under different sampling ratios.     

Numerical simulation of four-field extended magnetohydrodynamics in dynamically adaptive curvilinear coordinates via Newton–Krylov–Schwarz

Numerical simulations of the four-field extended magnetohydrodynamics (MHD) equations with hyper-resistivity terms present a difficult challenge because of demanding spatial resolution requirements. A time-dependent sequence of r-refinement adaptive grids obtained from solving a single Monge–Ampère (MA) equation addresses the high-resolution requirements near the x-point for numerical simulation of the magnetic reconnection problem. The MHD equations are transformed from Cartesian coordinates to solution-defined curvilinear coordinates. After the application of an implicit scheme to the time-dependent problem, the parallel Newton–Krylov–Schwarz (NKS) algorithm is used to solve the system at each time step. Convergence and accuracy studies show that the curvilinear solution requires less computational effort than a pure Cartesian treatment. This is due both to the more optimal placement of the grid points and to the improved convergence of the implicit solver, nonlinearly and linearly. The latter effect, which is significant (more than an order of magnitude in number of inner linear iterations for equivalent accuracy), does not yet seem to be widely appreciated.     

Fast Generation of GHZ States with Bose–Einstein Condensate in a Cavity

It is shown that strong coupling of Bose–Einstein condensates to an optical cavity can be realized experimentally. With an additional driven microwave field, we show that a highly nonlinear coupling among atoms in a Bose–Einstein condensate can be induced with the assistance of the cavity mode. With such interaction, we can investigate the generation of many body entangled states. In particularly, we show that multipartite entangled GHZ states can be obtained in such architecture with current available techniques.     

Stable loosely-coupled-type algorithm for fluid–structure interaction in blood flow

We introduce a novel loosely coupled-type algorithm for fluid–structure interaction between blood flow and thin vascular walls. This algorithm successfully deals with the difficulties associated with the “added mass effect”, which is known to be the cause of numerical instabilities in fluid–structure interaction problems involving fluid and structure of comparable densities. Our algorithm is based on a time-discretization via operator splitting which is applied, in a novel way, to separate the fluid sub-problem from the structure elastodynamics sub-problem. In contrast with traditional loosely-coupled schemes, no iterations are necessary between the fluid and structure sub-problems; this is due to the fact that our novel splitting strategy uses the “added mass effect” to stabilize rather than to destabilize the numerical algorithm. This stabilizing effect is obtained by employing the kinematic lateral boundary condition to establish a tight link between the velocities of the fluid and of the structure in each sub-problem. The stability of the scheme is discussed on a simplified benchmark problem and we use energy arguments to show that the proposed scheme is unconditionally stable. Due to the crucial role played by the kinematic lateral boundary condition, the proposed algorithm is named the “kinematically coupled scheme”.     

Effective Dynamics for a Kinetic Monte–Carlo Model with Slow and Fast Time Scales

We consider several multiscale-in-time kinetic Monte Carlo models, in which some variables evolve on a fast time scale, while the others evolve on a slow time scale. In the first two models we consider, a particle evolves in a one-dimensional potential energy landscape which has some small and some large barriers, the latter dividing the state space into metastable regions. In the limit of infinitely large barriers, we identify the effective dynamics between these macro-states, and prove the convergence of the process towards a kinetic Monte Carlo model. We next consider a third model, which consists of a system of two particles. The state of each particle evolves on a fast time-scale while conserving their respective energy. In addition, the particles can exchange energy on a slow time scale. Considering the energy of the first particle, we identify its effective dynamics in the limit of asymptotically small ratio between the characteristic times of the fast and the slow dynamics. For all models, our results are illustrated by representative numerical simulations.     

Fast Generation of Einstein–Podolsky–Rosen States for Two Cavity Modes with a Collection of Driven Atoms

We propose an efficient scheme for realizing two-mode squeezing for two cavity modes with an atomic ensemble trapped in the cavity and driven by two classical fields. Through a suitable choice of the driving classical fields, the evolution dynamics of the two cavity modes is decoupled with the atomic system and described by a two-mode squeezing operator. We show that a highly squeezed state can be obtained at the output even with a bad cavity. The required experimental techniques are within the scope of what can be obtained in the BEG-cavity setup.     

Fast joining of melt textured Y–Ba–Cu–O bulks with high quality

Y–Ba–Cu–O bulk superconductors were fast joined using Ag-doped Y–Ba–Cu–O solder (metallic Ag powder additive). The joining process was relatively shorter (around 24 h) comparing with the traditional joining method. The microstructures and the superconducting properties of the joints were evaluated carefully. Microstructure analysis revealed that the crystal pattern in the joint was almost the same as that of the base material. This indicated that the bonding zone grew along the growth direction of the base material. The trapped-field distribution of the joined bulk was almost uniform and only single peak was found. This demonstrated that strong bonding was achieved in the joining process. The ratio of joined bulk’s levitation force to that of original base material was up to 93.5%.     

Impact of autocatalysis chemical reaction on nonlinear radiative heat transfer of unsteady three-dimensional Eyring–Powell magneto-nanofluid flow

The structure of the chaotic attractor of a system is mainly determined by the nonlinear functions in system equations. By using a new saw-tooth wave function and a new stair function, a novel complex grid multiwing chaotic system which belongs to non-Shil’nikov chaotic system with non-hyperbolic equilibrium points is proposed in this paper. It is particularly interesting that the complex grid multiwing attractors are generated by increasing the number of non-hyperbolic equilibrium points, which are different from the traditional methods of realising multiwing attractors by adding the index-2 saddle-focus equilibrium points in double-wing chaotic systems. The basic dynamical properties of the new system, such as dissipativity, phase portraits, the stability of the equilibria, the time-domain waveform, power spectrum, bifurcation diagram, Lyapunov exponents, and so on, are investigated by theoretical analysis and numerical simulations. Furthermore, the corresponding electronic circuit is designed and simulated on the Multisim platform. The Multisim simulation results and the hardware experimental results are in good agreement with the numerical simulations of the same system on Matlab platform, which verify the feasibility of this new grid multiwing chaotic system.     

Uncovering dynamic behaviors underlying experimental oil–water two-phase flow based on dynamic segmentation algorithm

Characterizing complex dynamic behaviors arising from various inclined oil–water two-phase flow patterns is a challenging problem in the fields of nonlinear dynamics and fluid mechanics. We systematically carried out inclined oil–water two-phase flow experiments for measuring the time series conductance fluctuating signals of different flow patterns. We using the dynamic segmentation algorithm incorporating with phase space reconstruction analyze the measured experimental signals to uncover the dynamic behaviors underlying different flow patterns. Specifically, given a time series from a two-phase flow, we move a sliding pointer over the time series and for each position of the pointer we calculate the dynamic difference measure of the phase space orbits generated from the segment to the left and to the right of the pointer. A number of experimental signals under different flow conditions are investigated in order to reveal the dynamical characteristics of inclined oil–water flows. The results indicate that the heterogeneity of dynamic difference measure series is sensitive to the transition among different flow patterns and the standard deviation of dynamic difference measure series can yield quantitative insights into the nonlinear dynamics of the two-phase flow. These properties render the dynamic segmentation algorithm-based approach particularly useful for uncovering the dynamic behaviors of inclined oil–water two-phase flows.     

Studies of high-temperature electron–phonon interactions with inelastic neutron scattering and first-principles computations

Several recent studies of phonons combining inelastic neutron scattering and first-principles calculations are summarized. Inelastic neutron scattering was used to measure the phonon densities of states of the A15 compounds V₃Si, V₃Ge, and V₃Co at temperatures from 10 K to 1273 K. It was found that phonons in V₃Si and V₃Ge, which are superconducting at low temperatures, exhibit an anomalous stiffening with increasing temperature, whereas phonons in V₃Co have a normal softening behavior. Additional measurements of the phonon DOS of BCC V alloys were performed, and it was found that a stiffening anomaly present in pure V is suppressed upon introduction of extra d-electrons by alloying. First-principles calculations of the electronic and phonon densities of states show that in both these systems, the anomalous phonon stiffening originates with an adiabatic electron–phonon coupling mechanism. The anomaly is caused by the thermally-induced broadening of sharp peaks in the electronic density of states, which tends to decrease the electronic density at the Fermi level. These results illustrate how the combined use of first-principles calculations and inelastic neutron scattering provides powerful insights into couplings of excitations in condensed-matter.     

Cholesteric–nematic transitions induced by a shear flow and a magnetic field

The untwisting of the helical structure of a cholesteric liquid crystal under the action of a magnetic field and a shear flow has been studied theoretically. Both factors can induce the cholesteric–nematic transition independently; however, the difference in the orienting actions of the magnetic field and the shear flow leads to competition between magnetic and hydrodynamic mechanisms of influence on the cholesteric liquid crystal. We have analyzed different orientations of the magnetic field relative to the direction of the flow in the shear plane. In a number of limiting cases, the analytic dependences are obtained for the pitch of the cholesteric helix deformed by the shear flow. The phase diagrams of the cholesteric–nematic transitions and the pitch of the cholesteric helix are calculated for different values of the magnetic field strength and the angle of orientation, the flow velocity gradient, and the reactive parameter. It is shown that the magnetic field stabilizes the orientation of the director in the shear flow and expands the boundaries of orientability of cholesterics. It has been established that the shear flow shifts the critical magnetic field strength of the transition. It is shown that a sequence of reentrant orientational cholesteric–nematic–cholesteric transitions can be induced by rotating the magnetic field in certain intervals of its strength and shear flow velocity gradients.