A segregated method for compressible flow computation. Part II: general divariant compressible flows

Typically, segregated methods have been used for the computation of incompressible flows whereas coupled solvers, for compressible flows. Compared to coupled solvers, segregated methods present the advantage of computational savings in RAM memory and CPU time, although at the cost of an inferior robustness. However, previously published segregated algorithms for general compressible flows are known to present pitfalls, like convergence to wrong solutions, lack of robustness in the presence of strong discontinuities, such as normal and oblique shocks, and complicated boundary condition imposition. Therefore, in this paper a segregated method for non‐isothermal compressible flows is proposed that preserves the thermodynamic coupling and overcomes the criticisms of existing methods. Copyright © 2005 John Wiley & Sons, Ltd.     

Non‐oscillatory relaxation methods for the shallow‐water equations in one and two space dimensions

In this paper, a new family of high‐order relaxation methods is constructed. These methods combine general higher‐order reconstruction for spatial discretization and higher order implicit‐explicit schemes or TVD Runge–Kutta schemes for time integration of relaxing systems. The new methods retain all the attractive features of classical relaxation schemes such as neither Riemann solvers nor characteristic decomposition are needed. Numerical experiments with the shallow‐water equations in both one and two space dimensions on flat and non‐flat topography demonstrate the high resolution and the ability of our relaxation schemes to better resolve the solution in the presence of shocks and dry areas without using either Riemann solvers or front tracking techniques. Copyright © 2004 John Wiley & Sons, Ltd.     

Preconditioned Krylov subspace methods used in solving two‐dimensional transient two‐phase flows

This paper investigates the performance of preconditioned Krylov subspace methods used in a previously presented two‐fluid model developed for the simulation of separated and intermittent gas–liquid flows. The two‐fluid model has momentum and mass balances for each phase. The equations comprising this model are solved numerically by applying a two‐step semi‐implicit time integration procedure. A finite difference numerical scheme with a staggered mesh is used. Previously, the resulting linear algebraic equations were solved by a Gaussian band solver. In this study, these algebraic equations are also solved using the generalized minimum residual (GMRES) and the biconjugate gradient stabilized (Bi‐CGSTAB) Krylov subspace iterative methods preconditioned with incomplete LU factorization using the ILUT(p, τ) algorithm. The decrease in the computational time using the iterative solvers instead of the Gaussian band solver is shown to be considerable. Copyright © 1999 John Wiley & Sons, Ltd.     

On nonlinear preconditioners in Newton–Krylov methods for unsteady flows

The application of nonlinear schemes like dual time stepping as preconditioners in matrix‐free Newton–Krylov‐solvers is considered and analyzed, with a special emphasis on unsteady viscous flows. We provide a novel formulation of the left preconditioned operator that says it is in fact linear in the matrix‐free sense, but changes the Newton scheme. This allows to get some insight in the convergence properties of these schemes, which is demonstrated through numerical results. Copyright © 2009 John Wiley & Sons, Ltd.     

Nonlinear acceleration of coupled fluid–structure transient thermal problems by Anderson mixing

Conjugate heat‐transfer problems are typically solved using partitioned methods where fluid and solid subdomains are evaluated separately by dedicated solvers coupled through a common boundary. Strongly coupled schemes for transient analysis require fluid and solid problems to be solved many times each time step until convergence to a steady state. In many practical situations, a fairly simple and frequently employed fixed‐point iteration process is rather ineffective; it leads to a large number of iterations per time step and consequently to long simulation times. In this article, Anderson mixing is proposed as a fixed‐point convergence acceleration technique to reduce computational cost of thermal coupled fluid–solid problems. A number of other recently published methods with applications to similar fluid–structure interaction problems are also reviewed and analyzed. Numerical experiments are presented to illustrate relative performance of these methods on a test problem of rotating pre‐swirl cavity air flow interacting with a turbine disk. It is observed that performance of Anderson mixing method is superior to that of other algorithms in terms of total iteration counts. Additional computational savings are demonstrated by reusing information from previously solved time steps. Copyright © All rights reserved 2012 Rolls‐Royce plc.     

MESHLESS METHOD FOR NUMERICAL SIMULATION OF SHOCK-INDUCED COMBUSTION

发展了基于无网格方法的激波诱导燃烧流场数值模拟算法. 该算法采用二维多组分Euler方程,在点云离散的基础上采用曲面逼近计算空间导数,引入多组分HLLC （Harten-Lax-van Leer-contact） 格式计算无黏通量,运用四阶Runge-Kutta 法进行时间显式推进,化学动力学采用有限速率反应模型. 对不同预混气体中的激波诱导燃烧流场进行了数值模拟,结果同相关文献吻合较好,验证了算法的正确性.     

Space–Time Method for Detonation Problems with Finite-rate Chemical Kinetics

The space–time conservation element and solution element (CE/SE) method originally developed for non-reacting flows is extended to accommodate finite-rate chemical kinetics for multi-component systems. The model directly treats the complete conservation equations of mass, momentum, energy, and species concentrations. A subtime-step integration technique is established to handle the stiff chemical source terms in the formulation. In addition, a local grid refinement algorithm within the framework of the CE/SE method is incorporated to enhance the flow resolution in areas of interest. The capability and accuracy of the resultant scheme are validated against several detonation problems, including shock-induced detonation with detailed chemical kinetics and multi-dimensional detonation initiation and propagation.     

Parallel algorithms for panel methods

A parallel algorithm for the solution of potential flow problems using the panel method of Hess and Smith and conjugate and bi-conjugate gradient techniques is presented. Analysis of the parallelism for the matrix. solvers shows the algorithms to have scalable properties as the problem size grows indefinitely large. Speed-up and efficiency values are presented along with experimental and theoretical values for the optimum number of processors for maximum speed-up. It is envisaged that the parallel techniques presented here have applications using other boundary integral methods for solving engineering problems of a more complex nature.     

Theoretical analysis for achieving high‐order spatial accuracy in Lagrangian/Eulerian source terms

In a fully coupled Lagrangian/Eulerian two‐phase calculation, the source terms from computational particles must be agglomerated to nearby gas‐phase nodes. Existing methods are capable of accomplishing this particle‐to‐gas coupling with second‐order accuracy. However, higher‐order methods would be useful for applications such as two‐phase direct numerical simulation and large eddy simulation. A theoretical basis is provided for producing high spatial accuracy in particle‐to‐gas source terms with low computational cost. The present work derives fourth‐ and sixth‐order accurate methods, and the procedure for even higher accuracy is discussed. The theory is also expanded to include two‐ and three‐dimensional calculations. One‐ and two‐dimensional tests are used to demonstrate the convergence of this method and to highlight problems with statistical noise. Finally, the potential for application in computational fluid dynamics codes is discussed. It is concluded that high‐order kernels have practical benefits only under limited ranges of statistical and spatial resolution. Additionally, convergence demonstrations with full CFD codes will be extremely difficult due to the worsening of statistical errors with increasing mesh resolution. Copyright © 2006 John Wiley & Sons, Ltd.     

Macro modelling and homogenization for transformation induced plasticity of a low-alloy steel

Metal forming processes are important technologies for the production of engineering structures. In order to optimize the resulting material properties, it becomes necessary to simulate the entire forming process by taking into account physical effects such as phase transformations. In this work, we concentrate on the phase change from austenite to martensite and present a macroscopic material model, which combines the effect of classical plasticity with the effect of transformation induced plasticity (TRIP). An extensive experimental database for a low-alloy steel is used for parameter identification, thus taking into account the effects of uniaxial compressive and tensile stress on the kinetics of phase transformation at different temperatures. For temperatures below the martensite start temperature with simultaneous stresses above the yield limit, it is difficult to obtain experimental data. Consequently, a numerical homogenization technique is employed for this case. In a further part of this paper, an effective integration scheme is provided, which is implemented into a commercial finite element program. In a finite element simulation, the austenite to martensite phase transformation in a shaft subjected to thermal loading is investigated.     

A finite element model for shape memory alloys considering thermomechanical couplings at large strains

In the present work we propose a new thermomechanically coupled material model for shape memory alloys (SMA) which describes two important phenomena typical for the material behaviour of shape memory alloys: pseudoelasticity as well as the shape memory effect. The constitutive equations are derived in the framework of large strains since the martensitic phase transformation involves inelastic deformations up to 8%, or even up to 20% if the plastic deformation after the phase transformation is taken into account. Therefore, we apply a multiplicative split of the deformation gradient into elastic and inelastic parts, the latter concerning the martensitic phase transformation. An extended phase transformation function has been considered to include the tension–compression asymmetry particularly typical for textured SMA samples. In order to apply the concept in the simulation of complex structures, it is implemented into a finite element code. This implementation is based on an innovative integration scheme for the existing evolution equations and a monolithic solution algorithm for the coupled mechanical and thermal fields. The coupling effect is accurately investigated in several numerical examples including pseudoelasticity as well as the free and the suppressed shape memory effect. Finally, the model is used to simulate the shape memory effect in a medical foot staple which interacts with a bone segment.     

Convergence acceleration of continuous adjoint solvers using a reduced‐order model

A novel acceleration technique using a reduced‐order model is presented to speed up convergence of continuous adjoint solvers. The acceleration is achieved by projecting to an improved solution within an iterative process solely using early solution results. This is achieved by forming basis vectors from early iteration adjoint solutions to perform model order reduction of the adjoint equations. The reduced‐order model of the adjoint equations is then substituted into the full‐order discretized governing equations to determine weighting coefficients for each basis vector. With these coefficients, a linear combination of the basis vectors is used to project to an improved solution. The method is applied to 3 inviscid quasi‐1D nozzle flow cases including fully subsonic flow, subsonic inlet to supersonic outlet flow, and transonic flow with a shock. Significant cost reductions are achieved for a single application as well as repeated applications of the convergence acceleration technique.     

非线性结构动力学瞬态分析的摄动法

在用直接积分法求解非线性结构的动力响应时,常常需要做迭代运算。本文引入摄动方法后,加快了收敛速度,提高了计算效益。     

The back and forth nudging algorithm applied to a shallow water model,comparison and hybridization with the 4D‐VAR

We study in this paper a new data assimilation algorithm, called the back and forth nudging (BFN). This scheme has been very recently introduced for simplicity reasons, as it does not require any linearization, or adjoint equation, or minimization process in comparison with variational schemes, but nevertheless it provides a new estimation of the initial condition at each iteration. We study its convergence properties as well as efficiency on a 2D shallow water model. All along the numerical experiments, comparisons with the standard variational algorithm (called 4D‐VAR) are performed. Finally, a hybrid method is introduced, by considering a few iterations of the BFN algorithm as a preprocessing tool for the 4D‐VAR algorithm. We show that the BFN algorithm is extremely powerful in the very first iterations and also that the hybrid method can both improve notably the quality of the identified initial condition by the 4D‐VAR scheme and reduce the number of iterations needed to achieve convergence. Copyright © 2008 John Wiley & Sons, Ltd.     

An arbitrary Lagrangian–Eulerian method based on the adaptive Riemann solvers for general equations of state

Approximate or exact Riemann solvers play a key role in Godunov‐type methods. In this paper, three approximate Riemann solvers, the MFCAV, DKWZ and weak wave approximation method schemes, are investigated through numerical experiments, and their numerical features, such as the resolution for shock and contact waves, are analyzed and compared. Based on the analysis, two new adaptive Riemann solvers for general equations of state are proposed, which can resolve both shock and contact waves well. As a result, an ALE method based on the adaptive Riemann solvers is formulated. A number of numerical experiments show good performance of the adaptive solvers in resolving both shock waves and contact discontinuities. Copyright © 2008 John Wiley & Sons, Ltd.     

AN IMPLICIT SURFACE TENSION ALGORITHM FOR PICARD SOLVERS OF SURFACE–TENSION–DOMINATED FREE AND MOVING BOUNDARY PROBLEMS

One of the methods for solving a free or moving boundary problem is the use of Picard solvers which solve the geometry and the velocity field successively. When, however, the kinematic condition is used for updating the geometry in this technique, numerical stability problems occur for surface-tension-dominated flow. These problems are shown here to originate from the unstable integration of the local smoothing of the surface by surface tension. By an extension of the surface tension contribution to the flow field an implicit treatment of surface tension is obtained which overcomes these stability problems. The algorithm is applicable to both free and moving boundary problems, as will be shown by examples in this paper.     

Numerical modeling of ice behavior under high velocity impacts

In this work a constitutive relation for ice at high strain rates and an algorithm for its numerical integration are developed. This model is based on the Drucker–Prager plasticity criteria, which allows a different behavior in tension and in compression. In addition a failure criteria, based on pressure cut-offs, is implemented to describe the ice damage. In order to validate the constitutive model, numerical simulations were compared with experimental results, in which ice cylinders were impacted against a steel plate, allowing the measurement of the contact load. Three different numerical solvers are used in order to analyze its performance to appropriately modeling the ice behavior.     

Diffusion-based coarse graining in hybrid continuum–discrete solvers: Theoretical formulation and a priori tests

Coarse graining is an important ingredient in many multi-scale continuum–discrete solvers such as CFD–DEM (computational fluid dynamics–discrete element method) solvers for dense particle-laden flows. Although CFD–DEM solvers have become a mature technique that is widely used in multiphase flow research and industrial flow simulations, a flexible and easy-to-implement coarse graining algorithm that can work with CFD solvers of arbitrary meshes is still lacking. In this work, we proposed a new coarse graining algorithm for continuum–discrete solvers for dense particle-laden flows based on solving a transient diffusion equation. Via theoretical analysis we demonstrated that the proposed method is equivalent to the statistical kernel method with a Gaussian kernel, but the current method is much more straightforward to implement in CFD–DEM solvers. A priori numerical tests were performed to obtain the solid volume fraction fields based on given particle distributions, the results obtained by using the proposed algorithm were compared with those from other coarse graining methods in the literature (e.g., the particle centroid method, the divided particle volume method, and the two-grid formulation). The numerical tests demonstrated that the proposed coarse graining procedure based on solving diffusion equations is theoretically sound, easy to implement and parallelize in general CFD solvers, and has improved mesh-convergence characteristics compared with existing coarse graining methods. The diffusion-based coarse graining method has been implemented into a CFD–DEM solver, the results of which are presented in a separate work.     

Non-local continuum model and its numerical simulation for localization problem

A non-local continuum model for strain-softening simply taking plastic strain or damage variable as a non-local variable is derived by using the additive decomposition principle of finite deformation gradient. At the same time, variational equations, their finite element formulations and numerical convoluted integration algorithm of the model in current configuration usually called co-moving coordinate system are given. Stability and convergence of the model are proven by means of the weak convergence theorem of general function and the convoluted integration theory. Mathematical and physical properties of the characteristic size for material or structure are accounted for within the context of a statistical weighted or kernel function, and way is investigated. Numerical simulation shows that this model is suitable for to analyzing deformation localization problems. The project supported by the National Natural Science Foundation of China (No. 19632030).     

Lattice‐Boltzmann and meshless point collocation solvers for fluid flow and conjugate heat transfer

The applicability and performance of the lattice‐Boltzmann (LB) and meshless point collocation methods as CFD solvers in flow and conjugate heat transfer processes are investigated in this work. Lid‐driven cavity flow and flow in a slit with an obstacle including heat transfer are considered as case studies. A comparison of the computational efficiency accuracy of the two methods with that of a finite volume method as implemented in a commercial package (ANSYS CFX, ANSYS Inc., Canonsburg, PA) is made. Utilizing the analogy between heat and mass transfer, an advection–diffusion LB model was adopted to simulate the heat transfer part of the slit flow problem followed by a rigorous mapping of the mass transfer variables to the heat transfer quantities of interest, thus circumventing the need for a thermal LB model. Direct comparison among the results of the three methods revealed excellent agreement over a wide range of Reynolds and Prandtl number values. Furthermore, an integrated computational scheme is proposed, utilizing the rapid convergence of the LB model in the flow part of the conjugate heat transfer problem with that of the meshless collocation method for the heat transfer part. The meshless treatment remains sufficiently rapid even for conduction‐controlled processes in contrast to the LB method, which is very rapid in the convection‐controlled case only. A single, common computational grid, composed of regularly distributed nodes is used, saving significant computational and coding time and ensuring convergence of the discrete Laplacian operator in the heat transfer part of the computations. Copyright © 2012 John Wiley & Sons, Ltd.