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Publication date: Available online 8 July 2020
Source: Computers & Fluids
Author(s): K.K. Chode, H. Viswanathan, K. Chow
Publication date: Available online 7 July 2020
Source: Computers & Fluids
Author(s): Brendan Walsh, Fergal J. Boyle
Publication date: Available online 5 July 2020
Source: Computers & Fluids
Author(s): Gregorio Gerardo Spinelli, Bayram Celik
Publication date: Available online 4 July 2020
Source: Computers & Fluids
Author(s): Bo Li, Yachao Lee, Wei Yao, Yang Lu, Xuejun Fan
Publication date: Available online 8 July 2020
Source: Computers & Fluids
Author(s): Chung-Ming Wu, You-Sheng Zhou, Chao-An Lin
Publication date: Available online 9 July 2020
Source: Computers & Fluids
Author(s): Malú Grave, José J. Camata, Alvaro L.G.A. Coutinho
Publication date: 15 August 2020
Source: Computers & Fluids, Volume 208
Author(s): Gabi Luttwak
Publication date: 15 August 2020
Source: Computers & Fluids, Volume 208
Author(s): Adi Ditkowski, Sigal Gottlieb, Zachary J. Grant
Publication date: 15 August 2020
Source: Computers & Fluids, Volume 208
Author(s): Matej Klima, Andrew Barlow, Milan Kucharik, Mikhail Shashkov
Publication date: Available online 10 July 2020
Source: Computers & Fluids
Author(s): Jonathan Viquerat, Elie Hachem
In this paper, we describe a parallel adaptive mesh refinement strategy for two‐phase flows using tetrahedral meshes. The proposed methodology consists of combining a conservative level‐set method with tetrahedral adaptive meshes within a finite volume framework. Our adaptive algorithm applies a cell‐based refinement technique and adapts the mesh according to physics‐based refinement criteria defined by the two‐phase application. The new adapted tetrahedral mesh is obtained from mesh manipulations of an input mesh: operations of refinement and coarsening until a maximum level of refinement is achieved. For the refinement method of tetrahedral elements, geometrical characteristics are taking into consideration to preserve the shape quality of the subdivided elements. The present method is used for the simulation of two‐phase flows, with surface tension, to show the capability and accuracy of 3D adapted tetrahedral grids to bring new numerical research in this context. Finally, the applicability of this approach is shown in the study of the gravity‐driven motion of a single bubble/droplet in a quiescent viscous liquid on regular and complex domains.
Computational fluid dynamics (CFD) has emerged as a successful tool for industry applications and basic science during the last decades. However, accurate solutions involving vortex propagation, and separated and turbulent flows, are still associated with high computing costs. In particular, large eddy simulations (LES) of complex geometries, such as a complete automobile, require several days on thousands of cores in order to obtain solutions with statistically relevant information. With an increase in the number of available cores, the number of degrees of freedom (DOF) per core can be reduced accordingly. When the number of DOF percore is below a certain threshold the total simulation time is not bounded by floating point operations (FLOPS), but by the time spend on communication between cores. To overcome this impediment we have identified and tested a class of twostep Runge‐Kutta (TSRK) methods of high order with low number of stages, for time discretization of differential systems resulting from space discretization of weakly compressible Navier‐Stokes equations. These methods have not been used before in CFD simulations. The advantage of using these methods is reduction in communication times between cores. The numerical experiments indicate that the gains in computational performance of this new class of TSRK methods, as compared with classical Runge‐Kutta (RK) methods or low storage Runge‐Kutta (LSRK) schemes, are of the order of 25~, with no loss in accuracy.
Reduced‐order models are more and more considered for use in aerodynamic applications. Benefits of these methods can be expected for optimization problems or predicting aerodynamic loads for the entire flight envelope. For these applications it is often possible to perform computations for various parameter combinations before any ROM evaluations are needed. The order reduction of the CFD solutions in this paper is done using Proper Orthogonal Decomposition. Coupled with an interpolation method predictions for unknown parameter combinations can be made. The CFD solutions are computed using a Discontinuous Galerkin finite element method combined with a nonlinear multigrid scheme. The nonlinear multigrid solver algorithms depend on a good initial guess of the flow field to be computed. Typically, the initial guess on a fine mesh is obtained by solving the problem on a agglomerated mesh. Alternatively, an initial guess could be obtained from a ROM prediction, if available. The main objective is to identify the benefits of using a ROM in a higher‐order multigrid environment. Integral as well as distributed surface quantities of the ROM predictions originating from several multigrid levels will be compared to fully converged flow solutions on the top level of the multigrid algorithm. Furthermore, initializing the flow solver with predictions from several multigrid levels will be analyzed in comparison to full multigrid computations as well as to a scenario where already converged solutions for similar parameter combinations are used as initial flow solutions on the top multigrid level.
In this paper, we consider a non‐local (in time) two‐phase flow model. The nonlocality is introduced through the wettability alteration induced dynamic capillary pressure function. We present a monotone fixed‐point iterative linearization scheme for the resulting non‐standard model. The scheme treats the dynamic capillary pressure functions semi‐implicitly and introduces an L ‐scheme type1,2 stabilization term in the pressure as well as the transport equations. We prove the convergence of the proposed scheme theoretically under physically acceptable assumptions, and verify the theoretical analysis with numerical simulations. The scheme is implemented and tested for a variety of reservoir heterogeneities in addition to the dynamic change of the capillary pressure function. The proposed scheme satisfies the predefined stopping criterion within a few number of iterations.We also compared the performance of the proposed scheme against the iterative IMplicit Pressure Explicit Saturation scheme.
In the present paper, an improved multiphase weakly compressible smoothed particle hydrodynamics model for balancing the accuracy and stability of the long‐term simulations is proposed to model the forced liquid sloshing in a tank. The governing equations of the multiphase flow are discretized by considering the density discontinuity over the interface. To suppress the pressure oscillation, a previous density correction term suitable only for single phase problems is modified and incorporated into the discrete continuity equation to suit multiphase problems. The modified density re‐initialization algorithm is implemented to calculate the pressure of the boundary particles, and the coupled dynamic solid boundary treatment is employed to determine the rigid wall condition. For convenience, a numerical probe algorithm is also proposed to accurately measure the wave height. The present model exhibits a better numerical stability than the previous multiphase smoothed particle hydrodynamics model, and its results well confirm with the experimental data of the forced sloshing of liquid excited by swaying or rolling.
A coupled version of the improved divergence‐free‐condition compensated method is proposed to simulate time‐varying geometries by direct forcing immersed boundary method. The proposed quasi‐multi‐moment framework due to the fact that the momentum equations are discretized by both cell‐centered and cell‐face velocity. A semi‐implicit iterative method is proposed for calculating the direct forcing terms. Treatments for suppressing spurious force oscillations, calculating drag/lift forces, and evaluating velocity and pressure for freshly cells will also be addressed.
In this article a coupled version of the improved divergence‐free‐condition compensated method will be proposed to simulate time‐varying geometries by direct forcing immersed boundary method. The proposed method can be seen as a quasi‐multi‐moment framework due to the fact that the momentum equations are discretized by both cell‐centered and cell‐face velocity. For simulating time‐varying geometries, a semi‐implicit iterative method is proposed for calculating the direct forcing terms. Treatments for suppressing spurious force oscillations, calculating drag/lift forces, and evaluating velocity and pressure for freshly cells will also be addressed. In order to show the applicability and accuracy, analytical as well as benchmark problems will be investigated by the present framework and compared with other numerical and experimental results.
In this article, we present two improved third‐order weighted essentially nonoscillatory (WENO) schemes for recovering their design‐order near first‐order critical points. The schemes are constructed in the framework of third‐order WENO‐Z scheme. Two new global smoothness indicators, τ L 3 and τ L 4, are devised by a nonlinear combination of local smoothness indicators (IS k ) and reference values (IS G ) based on Lagrangian interpolation polynomial. Numerical results indicate the presented schemes provide less dissipation and higher resolution than the original WENO3‐JS and subsequent WENO3‐N scheme.
In this article, we present two improved third‐order weighted essentially nonoscillatory (WENO) schemes for recovering their design‐order near first‐order critical points. The schemes are constructed in the framework of third‐order WENO‐Z scheme. Two new global smoothness indicators, τ L 3 and τ L 4, are devised by a nonlinear combination of local smoothness indicators (IS k ) and reference values (IS G ) based on Lagrangian interpolation polynomial. The performances of the proposed schemes are evaluated on several numerical tests governed by one‐dimensional linear advection equation or one‐ and two‐dimensional Euler equations. Numerical results indicate that the presented schemes provide less dissipation and higher resolution than the original WENO3‐JS and subsequent WENO3‐N scheme.
No abstract is available for this article.
1. An improved DI method with interface compression is proposed and validated.
2. Interface dispersion is suppressed effectively and properly by using the magnitude of local vorticity as the interface compression factor.
3. Tiny interfacial structure can be captured accurately in flow field.
An improved diffuse interface (DI) method is proposed for accurately capturing complex interface deformation in simulations of three‐dimensional (3D) multiphase flows. In original DI methods, the unphysical phenomenon of interface thickening or blurring can affect the accuracy of numerical simulations, especially for flows with large density ratio and high Reynolds number. To remove this drawback, in this article, an interface‐compression term is introduced into the Cahn‐Hilliard equation to suppress the interface dispersion. The additional term only takes effect in the interface region and works normal to the interface. The difference of the current method from the previous work is that the compression rate can be adjusted synchronously according to the magnitude of local vorticity, which is strongly correlated to the interface dispersion and changes with the computational time and interface position. Numerical validations of the proposed method are implemented by simulating problems of Laplace law, Rayleigh‐Taylor instability, bubble rising in a channel, and binary droplet collision. The obtained results agree well with the analytical solutions and published data. The numerical results show that the phenomenon of interface dispersion is suppressed effectively and the tiny interfacial structures in flow field can be captured accurately.
1. The gas‐kinetic unified algorithm is developed for the plane external force‐driven flows covering the rarefied free‐molecule flow to the continuum flow regimes by the computable modeling of the Boltzmann equation. 2. The non‐equilibrium flow phenomena including the bimodal temperature, nonconstant pressure, flow velocity and heat flux profiles in the external force‐driven Poiseuille flows are revealed and analyzed by the current algorithm. 3. For the lid‐driven cavity flow under gravitational field, with an increase in rarefaction of Knudsen numbers Kn = 5 × 10−5 ∼ 10, both expansion cooling and gravity play greater roles in determining the heat transfer characteristics from the continuum to the free‐molecule flow regimes.
The nonequilibrium steady gas flows under the external forces are essentially associated with some extremely complicated nonlinear dynamics, due to the acceleration or deceleration effects of the external forces on the gas molecules by the velocity distribution function. In this article, the gas‐kinetic unified algorithm (GKUA) for rarefied transition to continuum flows under external forces is developed by solving the unified Boltzmann model equation. The computable modeling of the Boltzmann equation with the external force terms is presented at the first time by introducing the gas molecular collision relaxing parameter and the local equilibrium distribution function integrated in the unified expression with the flow state controlling parameter, including the macroscopic flow variables, the gas viscosity transport coefficient, the thermodynamic effect, the molecular power law, and molecular models, covering a full spectrum of flow regimes. The conservative discrete velocity ordinate (DVO) method is utilized to transform the governing equation into the hyperbolic conservation forms at each of the DVO points. The corresponding numerical schemes are constructed, especially the forward‐backward MacCormack predictor‐corrector method for the convection term in the molecular velocity space, which is unlike the original type. Some typical numerical examples are conducted to test the present new algorithm. The results obtained by the relevant direct simulation Monte Carlo method, Euler/Navier‐Stokes solver, unified gas‐kinetic scheme, and moment methods are compared with the numerical analysis solutions of the present GKUA, which are in good agreement, demonstrating the high accuracy of the present algorithm. Besides, some anomalous features in these flows are observed and analyzed in detail. The numerical experience indicates that the present GKUA can provide potential applications for the simulations of the nonequilibrium external‐force driven flows, such as the gravity, the electric force, and the Lorentz force fields covering all flow regimes.
Publication date: Available online 10 July 2020
Source: Journal of Computational Physics
Author(s): Matthias Taus, Leonardo Zepeda-Núñez, Russell J. Hewett, Laurent Demanet
Publication date: 1 October 2020
Source: Journal of Computational Physics, Volume 418
Author(s): Baolin Tian, Junsheng Zeng, Baoqing Meng, Qian Chen, Xiaohu Guo, Kun Xue
Publication date: 1 October 2020
Source: Journal of Computational Physics, Volume 418
Author(s): Jie Ding, Zhongming Wang, Shenggao Zhou
Publication date: 1 October 2020
Source: Journal of Computational Physics, Volume 418
Author(s): Chuchu Chen, Jialin Hong, Chol Sim, Kwang Sonwu
Publication date: Available online 9 July 2020
Source: Journal of Computational Physics
Author(s): Tom H. Anderson, Benjamin J. Civiletti, Peter B. Monk, Akhlesh Lakhtakia
Publication date: Available online 9 July 2020
Source: Journal of Computational Physics
Author(s): Alec M. Dunton, Lluís Jofre, Gianluca Iaccarino, Alireza Doostan
Publication date: Available online 9 July 2020
Source: Journal of Computational Physics
Author(s): Marcos Sandim, Afonso Paiva, Luiz Henrique de Figueiredo
Publication date: Available online 9 July 2020
Source: Journal of Computational Physics
Author(s): Søren Taverniers, Daniel M. Tartakovsky
Publication date: Available online 9 July 2020
Source: Journal of Computational Physics
Author(s): Kaixuan Feng, Zhenzhou Lu, Lu Wang
Publication date: Available online 9 July 2020
Source: Journal of Computational Physics
Author(s): M. Maurer, A. Bañón Navarro, T. Dannert, M. Restelli, F. Hindenlang, T. Görler, D. Told, D. Jarema, G. Merlo, F. Jenko
In this study, we propose a novel computational model for simulating the coffee-ring phenomenon. The proposed method is based on a phase-field model and Monte Carlo simulation. We use the Allen–Cahn equation with a pinning boundary condition to model a drying droplet. The coffee particles inside the droplet move according to a random walk function with a truncated standard normal distribution under gravitational force. We perform both two-dimensional and three-dimensional computational experiments to demonstrate the accurate simulation of the coffee-ring phenomenon by the proposed model.
Effect of finite ion size on the transport of a neutral solute across the porous wall of a nanotube is presented in this study. Modified Poisson–Boltzmann equation without the Debye–Huckel approximation is used to determine the potential distribution within the tube. Power law fluid is selected for the study, as its rheology resembles closely to the real-life physiological fluids. The flow within the tube is actuated by the combined effects of pressure and electroosmotic forces. Steady-state solute balance equation is solved by the similarity technique in order to track the solute transport across the tube. The effects of ionic radius, ionic concentration, and flow behavioral index on the length-averaged Sherwood number, permeate flux, and permeate concentration are analyzed. This study will be extremely helpful in predicting the transport characteristics of a neutral solute in real physiological systems and also to fine-tune the performance of microfluidic devices having porous wall.
The paper describes the longitudinal dispersion of passive tracer materials released into an incompressible viscous fluid, flowing through a channel with walls having first-order reaction. Its model is based on a steady advection–diffusion equation with Dirichlet’s and mixed boundary conditions, and whose solution represents the concentration of the tracers in different downstream stations. For imposing the boundary conditions properly, artanh transformation is used to convert the infinite solution space to a finite one. A finite difference implicit scheme is used to solve the advection–diffusion equation in the computational region, and an inverse transformation is employed for the solution in the physical region. It is shown how the mixing of the tracer molecule influenced by the shear flow and due to the action of the absorption parameter at both the walls of the channel. For convection-dominated flow, uniform mesh is failed to capture the layer phenomena along the different downstream stations and a piecewise uniform mesh; namely, Shishkin mesh is used. The results are compared with existing experimental and numerical data available in the literature, and we have achieved an excellent agreement with them. The study plays a significant role to understand the basic mechanisms of sewage dispersion.
Identifying accurate and yet interpretable low-order models from data has gained a renewed interest over the past decade. In the present work, we illustrate how the combined use of dimensionality reduction and sparse system identification techniques allows us to obtain an accurate model of the chaotic thermal convection in a two-dimensional annular thermosyphon. Taking as guidelines the derivation of the Lorenz system, the chaotic thermal convection dynamics simulated using a high-fidelity computational fluid dynamics solver are first embedded into a low-dimensional space using dynamic mode decomposition. After having reviewed the physical properties the reduced-order model should exhibit, the latter is identified using SINDy, an increasingly popular and flexible framework for the identification of nonlinear continuous-time dynamical systems from data. The identified model closely resembles the canonical Lorenz system, having the same structure and exhibiting the same physical properties. It moreover accurately predicts a bifurcation of the high-dimensional system (corresponding to the onset of steady convection cells) occurring at a much lower Rayleigh number than the one considered in this study.
This study presents two different machine learning approaches for the modeling of hydrodynamic force on particles in a particle-laden multiphase flow. Results from particle-resolved direct numerical simulations (PR-DNS) of flow over a random array of stationary particles for eight combinations of particle Reynolds number ( \({\mathrm {Re}}\) ) and volume fraction ( \(\phi \) ) are used in the development of the models. The first approach follows a two-step process. In the first flow prediction step, the perturbation flow due to a particle is obtained as an axisymmetric superposable wake using linear regression. In the second force prediction step, the force on a particle is evaluated in terms of the perturbation flow induced by all its neighbors using the generalized Faxén form of the force expression. In the second approach, the force data on all the particles from the PR-DNS simulations are used to develop an artificial neural network (ANN) model for direct prediction of force on a particle. Due to the unavoidable limitation on the number of fully resolved particles in the PR-DNS simulations, direct force prediction with the ANN model tends to over-fit the data and performs poorly in the prediction of test data. In contrast, due to the millions of grid points used in the PR-DNS simulations, accurate flow prediction is possible, which then allows accurate prediction of particle force. This hybridization of multiphase physics and machine learning is particularly important, since it blends the strength of each, and the resulting pairwise interaction extended point-particle model cannot be developed by either physics or machine learning alone.
This work deals with the characterization of the closed-loop control performance aiming at the delay of transition. We focus on convective wavepackets, typical of the initial stages of transition to turbulence, starting with the linearized Kuramoto–Sivashinsky equation as a model problem representative of the transitional 2D boundary layer; its simplified structure and reduced order provide a manageable framework for the study of fundamental concepts involving the control of linear wavepackets. The characterization is then extended to the 2D Blasius boundary layer. The objective of this study is to explore how the sensor–actuator placement affects the optimal control problem, formulated using linear quadratic Gaussian (LQG) regulators. This is carried out by evaluating errors of the optimal estimator at positions where control gains are significant, through a proposed metric, labelled as \(\gamma \). Results show, in quantitative manner, why some choices of sensor–actuator placement are more effective than others for flow control: good (respectively, bad) closed-loop performance is obtained when estimation errors are low (respectively, high) in the regions with significant gains in the full-state-feedback problem. Unsatisfactory performance is further understood as dominant estimation error modes that overlap spatially with control gains, which shows directions for improvement of a given set-up by moving sensors or actuators. The proposed metric and analysis explain most trends in closed-loop performance as a function of sensor and actuator position, obtained for the model problem and for the 2D Blasius boundary layer. The spatial characterization of the \(\gamma \)-metric provides thus a valuable and intuitive tool for the problem of sensor–actuator placement, targeting here transition delay but possibly extending to other amplifier-type flows.
The mixing in three-dimensional enclosures is investigated numerically using flow in cubical cavity as a geometrically simple model of various natural and engineering flows. The mixing rate is evaluated for up to the value of Reynolds number \(\hbox {Re}=2000\) for several representative scenarios of moving cavity walls: perpendicular motion of the parallel cavity walls, motion of a wall in its plane along its diagonal, motion of two perpendicular walls outward the common edge, and the parallel cavity walls in motion either in parallel directions or in opposite directions. The mixing rates are compared to the well-known benchmark case in which one cavity wall moves along its edge. The intensity of mixing for the considered cases was evaluated for (i) mixing in developing cavity flow initially at rest, which is started by the impulsive motion of cavity wall(s), and (ii) mixing in the developed cavity flow. For both cases, the initial interface of the two mixing fluids is a horizontal plane located at the middle of the cavity. The mixing rates are ranked from fastest to slowest for twenty time units of flow mixing. The pure convection mixing is modeled as a limit case to reveal convective mechanism of mixing. Mixing of fluids with different densities is modeled to show the advantage in terms of mixing rate of genuinely 3D cases. Grid convergence study and comparison with published numerical solutions for 3D and 2D cavity flows are presented. The effects of three-dimensionality of cavity flow on the mixing rate are discussed.
This paper considers membranes of globular structure in the framework of the cell model technique. The flow of a micropolar fluid through a spherical cell consisting of a solid core, porous layer and liquid envelope is modeled using coupled micropolar and Brinkman-type equations. The solution is obtained in analytical form. Boundary value problems with different conditions on the hypothetical cell surface are considered and compared. The hydrodynamic permeability of the membrane is investigated as a function of micropolar and porous media characteristics.
A major aim of the present study is to understand and thoroughly document the fluid dynamics in three-dimensional branching networks when an intermediate branch is partially or completely obstructed. Altogether, 26 different three-dimensional networks each comprising six generations of branches (involving 63 straight portions and 31 bifurcation modules) are constructed and appropriately meshed to conduct a systematic study of the effects of varying the locations of a blockage of a given relative extent and varying the extent of a blockage at a fixed location. The side-by-side consideration of two branching configurations (in-plane and \(90^{\circ }\) out-of-plane) gives a quantitative assessment of the dependence of flow alteration due to blockage on the three-dimensional arrangement of the same individual branches. A blockage in any branch affects the flow in both downstream and upstream branches. The presence of a blockage can make three-dimensional asymmetric alteration to the flow field, even when the blockage itself is geometrically symmetric. The overall mass flow rate entering the network is found to remain nearly unaltered if a blockage is shifted within the same generation but is progressively reduced if the blockage is shifted to upstream generations. A blockage anywhere in the network increases the degree of mass flow asymmetry \(\delta _{\mathrm{G}n} \) in any generation. The order of magnitude disparity in \(\delta _{\mathrm{G}n} \) between the in-plane and out-of-plane configurations, characteristic of unobstructed networks, can be significantly reduced in the presence of a single blockage. The present three-dimensional computations show that the effects of blockage on the mass flow distribution in a large network are complex, often non-intuitive and sometimes dramatic, and cannot be captured by any simple one-dimensional model.
Circulating tumor cells (CTCs) are regarded as important biomarkers for early cancer detection and treatment. Decades of research have made progress in CTC detection using deformability-based microfilters; however, developing a high-throughput CTC microfilter remains a challenging task due to the lack of the essential understanding of microscopic multiphase flow. To design and optimize a CTC microfilter, in-depth studies of the dynamics of a CTC squeezing through a confined constriction are necessary. In this study, numerical simulation was employed. Utilizing the octree-based Adaptive-Mesh-Refinement algorithm, a CTC was modeled as a compound Newtonian droplet moving through a microfilter with non-uniform cross sections. The immiscible interface was tracked by the volume-of-fluid method with the surface tension accounted for using the continuum surface force method. Pressure signature, shear stress and instantaneous cell velocity during the passing process through a conical microfilter were investigated in great detail in order to understand the fluid dynamics affecting the cell squeezing process. Then, the crucial design parameters including pore angles and operating flow rates were analyzed. The shear stress and critical pressure under different flow rates were investigated as well. Results reveal that the deformation-induced surface tension pressure of the cell nucleus is the dominant component of the critical pressure. Additionally, the maximum instantaneous cell velocity, shear stress and pressure all occur at the same critical stage, as the nucleus passes through the exit of the microfilter channel. Our study provides insights into the dynamics of a compound droplet squeezing through a conical-shaped microfilter and offers constructive guidance for the design and optimization of high-throughput CTC microfilters.
