三维对流扩散方程的稀疏存储及预条件迭代

基于四阶紧致格式对三维对流扩散方程进行离散,并给出所得到的离散线性方程组的块三角稀疏矩阵形式。以带双阈值的不完全因子化LU分解[(ILUT(τ,s))]作为预条件子,分别用FGMRES、BICGSTAB和TFQMR作为迭代加速器,对离散线性方程组进行求解验证了格式精度并比较了不同迭代法的CPU时间和迭代步。此外,通过比较传统迭代法和预条件迭代法的计算效率,表明预条件迭代法不仅能够保证格式的四阶精度,还能极大地提高收敛效率。     

求解二维对流扩散方程的格子Boltzmann方法

针对二维对流扩散方程,基于D2Q4格子速度,用Chapman-Enskog多尺度分析技术,将时间尺度取为二阶,空间尺度取为一阶,推导了各个速度方向上的平衡态分布函数所满足的条件,给出了简单且对称的平衡态分布函数表达式,所得到的平衡态分布函数能正确地恢复出二维对流扩散方程,从而构建了一种新的求解二维对流扩散方程的D2Q4格子Boltzmann（LB）模型。用所给LB模型对扩散方程和两个不同初边界条件的对流扩散方程进行了数值求解,数值实验结果表明数值解与精确解吻合较好,与相关文献结果比较边界误差要小得多,验证了模型的有效性。     

TVD格式求解对流扩散方程的最优限制器研究

为探究不同通量限制器应用于TVD(Total Variation Diminishing)格式求解对流扩散方程时的适用性,基于3种典型的TVD格式与10种常用的通量限制器,分别求解了线性对流扩散方程、非线性对流扩散方程、拟线性对流扩散方程。数值结果表明,相比于MUSCL(Monotonic Upstream-centered Scheme for Conservation Laws)和MTVDLF(Modified TVDLF)格式,采用TVDLF(TVD Lax-Friedrichs)格式时,计算结果出现了较为严重的数值耗散;对MUSCL和MTVDLF格式进行具体分析发现,关于阶跃型纯对流问题,Superbee限制器的误差最小,Minmod误差最大。关于高斯型对流扩散问题,Minmod误差最大,Woodward误差最小。而关于阶跃型对流扩散问题及Burgers方程,限制器的类型对实验结果影响并不明显。     

二维带分数阶Laplacian算子的对流扩散方程的格子Boltzmann模型研究

带有分数阶Laplacian算子的对流扩散方程常被用来刻画自然界与社会系统中的反常扩散现象.本文提出了一种新的格子Boltzmann模型,用于求解二维带分数阶Laplacian算子的对流扩散方程.首先,基于分数阶Laplacian算子的Fourier变换和Gauss型求积公式,得到控制方程的近似方程.然后,将速度空间、时间和空间进行离散,并构造合适的平衡态分布函数和离散作用力,建立有效的格子Boltzmann-BGK模型.通过Chapman-Enskog分析,可由建立的格子Boltzmann-BGK模型恢复出宏观方程,从而证明了模型的有效性.最后,将模型应用于求解带有解析解的数值算例和Allen-Cahn方程,数值结果进一步验证了模型的正确性和有效性.     

求解双曲守恒律及其对流扩散方程的中心迎风方法

提出了一种新的求解双曲守恒律方程(组)的四阶半离散中心迎风差分方法．空间导数项的离散采用四阶CWENO(central weighted essentially non—oscillatory)的构造方法,使所得到的新方法在提高精度的同时,具有更高的分辨率．使用该方法产生的数值粘性要比交错的中心格式小,而且由于数值粘性与时间步长无关,从而时间步长可根据稳定性需要尽可能的小．     

对流扩散方程并行求解方法研究综述

对流扩散方程是一类典型的偏微分方程,其并行求解方法对其他微积分方程的并行求解具有借鉴意义。对对流扩散方程的并行求解方法进行综述,分为显式直接并行、隐式迭代并行、交替分组显式并行和Monte Carlo并行四种并行求解方法,对其中涉及的计算原理进行描述,给出示例,并指出进一步研究方向。     

二维线性对流扩散问题的NURBS等几何分析

基于NURBS的等几何分析法有机地结合了CAGD和有限元分析.为将该方法应用于线性对流扩散问题的求解,提出将SUPG(streamline upwind Petrov-Galerkin)法与等几何法相结合的稳定化离散方案.首先对空间域进行等几何离散,然后用θ加权法离散时间域建立了完全离散的等几何求解格式;同时引入罚函数法处理NURBS基函数的非插值性所造成的本质边界处理误差.最后通过数值算例验证了文中方法的有效性.     

广义平均值差分格式在对流—扩散方程中的应用

§1.引言 从逼近的角度看,微分方程的各种数值方法均可认为是对解函数的某种方式的逼近。当解具有大梯度时,线性逼近的效果往往不好。一般的克服办法是细分网格或采用高阶多项式插值。本文考虑从非线性逼近的角度处理微分方程大梯度问题。前几年孙家昶导出广义平均值以及一类半线性数值微分公式,并且运用这种工具解常微分方程的初边值问题,取得良好效果。本文在此基础上对于对流—扩散方程用广义平均值构造了一种自适应的差分格式,使之具有根据解的局部性态选择格式的特点,并分析了格式的截断误差和所引入参数的选取,以及格式的稳定性和保单调性条件。对于一维及二维问题的一     

一维非定常对流扩散方程的高阶组合紧致迎风格式

通过将对流项采用四五阶组合迎风紧致格式离散,扩散项采用四阶对称紧致格式离散之后,对得到的半离散格式在时间方向采用四阶龙格库塔方法求解,从而得到了一种求解非定常对流扩散方程问题的高精度组合紧致有限差分格式,其收敛阶为O(h~4+τ~4).经Fourier精度分析和数值验证,证实了格式的良好性能.三个数值算例包括线性常系数问题,矩形波问题和非线性问题,数值结果表明:该格式具有很高的分辨率,且适用于对高雷诺数问题的数值模拟.     

二维扩散方程的GPU加速

近几年来,GPU因拥有比CPU更强大的浮点性能备受瞩目。NVIDIA推出的CUDA架构,使得GPU上的通用计算成为现实。本文将计算流体力学中Benchmark问题的二维扩散方程移植到GPU,并采用了全局存储和纹理存储两种方法。结果显示,当网格达到百万量级的时候,得到了34倍的加速。     

A stencil of the finite-difference method for the 2D convection diffusion equation and its new iterative scheme

The paper gives the numerical stencil for the two-dimensional convection diffusion equation and the technique of elimination, and builds up the new iterative scheme to solve the implicit difference equation. The scheme's convergence and its higher rate of convergence than the Jacobi iteration are proved. And the numerical example indicates that the new scheme has the same parallelism and a higher rate of convergence than the Jacobi iteration.     

A 15-point high-order compact scheme with multigrid computation for solving 3D convection diffusion equations

We propose a method with sixth-order accuracy to solve the three-dimensional (3D) convection diffusion equation. We first use a 15-point fourth-order compact discretization scheme to obtain fourth-order solutions on both fine and coarse grids using the multigrid method. Then an iterative mesh refinement technique combined with Richardson extrapolation is used to approximate the sixth-order accurate solution on the fine grid. Numerical results are presented for a variety of test cases to demonstrate the efficiency and accuracy of the proposed method, compared with the standard fourth-order compact scheme.     

A symmetric preserving iterative method for generalized Sylvester equation

The generalized Sylvester matrix equation AX + YB = C is encountered in many systems and control applications, and also has several applications relating to the problem of image restoration, and the numerical solution of implicit ordinary differential equations. In this paper, we construct a symmetric preserving iterative method, basing on the classic Conjugate Gradient Least Squares (CGLS) method, for AX + YB = C with the unknown matrices X, Y having symmetric structures. With this method, for any arbitrary initial symmetric matrix pair, a desired solution can be obtained within finitely iterate steps. The unique optimal (least norm) solution can also be obtained by choosing a special kind of initial matrix. We also consider the matrix nearness problem. Some numerical results confirm the efficiency of these algorithms. It is more important that some numerical stability analysis on the matrix nearness problem is given combined with numerical examples, which is not given in the earlier papers. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

An efficient method based on the second kind Chebyshev wavelets for solving variable-order fractional convection diffusion equations

In this paper, a class of variable-order fractional convection diffusion equations have been solved with assistance of the second kind Chebyshev wavelets operational matrix. The operational matrix of variable-order fractional derivative is derived for the second kind Chebyshev wavelets. By implementing the second kind Chebyshev wavelets functions and also the associated operational matrix, the considered equations will be reduced to the corresponding Sylvester equation, which can be solved by some appropriate iterative solvers. Also, the convergence analysis of the proposed numerical method to the exact solutions and error estimation are given. A variety of numerical examples are considered to show the efficiency and accuracy of the presented technique.     

A numerical method for solving a nonlinear 2-D optimal control problem with the classical diffusion equation

This paper presents a numerical solution for solving a nonlinear 2-D optimal control problem (2DOP). The performance index of a nonlinear 2DOP is described with a state and a control function. Furthermore, dynamic constraint of the system is given by a classical diffusion equation. It is preferred to use the Ritz method for finding the numerical solution of the problem. The method is based upon the Legendre polynomial basis. By using this method, the given optimisation nonlinear 2DOP reduces to the problem of solving a system of algebraic equations. The benefit of the method is that it provides greater flexibility in which the given initial and boundary conditions of the problem are imposed. Moreover, compared with the eigenfunction method, the satisfactory results are obtained only in a small number of polynomials order. This numerical approach is applicable and effective for such a kind of nonlinear 2DOP. The convergence of the method is extensively discussed and finally two illustrative examples are included to observe the validity and applicability of the new technique developed in the current work.     

New iterative method for solving non-linear equations with fourth-order convergence

In this work, we introduce an extension of the classical Newton's method for solving non-linear equations. This method is free from second derivative. Similar to Newton's method, the proposed method will only require function and first derivative evaluations. The order of convergence of the introduced method for a simple root is four. Numerical results show that the new method can be of practical interest.     

A Newton-like method for solving a non-smooth elliptic equation

In this paper, we use finite element method to discrete a non-smooth elliptic equation and present some error estimates. Non-smooth Newton-like method is applied to solve the discrete problem. Since Newton's equations have a very bad conditioner when the mesh-size is finer, multigrid technique is used to solve the subproblems. It is shown that if we use V-cycle or cascadic multigrid as an inner iterator, an (nearly) optimal property can be obtained. Numerical results are illustrated to confirm the error estimates we obtained and the efficiency of the non-smooth Newton-like method combining with multigrid technique. Especially, if the mesh-size h becomes much smaller, the method can save substantial computational work.