非线性方程组的非交替Newton-PHSS迭代法

大型稀疏非Hermite正定Jacobi矩阵对应的非线性方程组的迭代求解历来受到重视.结合不精确Newton法和非交替PHSS迭代法,提出了迭代求解非线性方程组的NewtonNPHSS方法,给出了迭代法的局部收敛定理,并演算了数值例子,阐明了Newton-NPHSS是有效的迭代法.     

一些迭代矩阵的特征值和特征向量及其收敛性

在大型科学计算中,大量的计算都归结为线性代数方程组求解,而线性代数方程组的迭代法求解是求解线性方程组的最有效的方法之一,因而,引起世界上大型科学计算界的许多著名学者的重视。1980年EVANS,MISSIRLS建立了迭代求解线性代数方程组的PSD方法并讨论了矩阵A是对称正定时的收敛性。1983年EVANS在[2]中说,“遗憾的是,除δ_1外,PJ方法(即PSD方法的特殊情况)的迭代矩阵的特征值没有象SOR方法那样,建立起与JACOBI迭代矩阵的特征值之间的关系式”。本文在系数矩阵A是T(q,r)阵的情况下,建立了PSD,PJ方法的迭代矩阵的特征值和特征向量与JACOBI方法的迭代矩阵的特征值和特征向量的关系式并在系数矩阵A是T(1,1)和T(1,2)阵的情况下讨论了PSD,PJ的收敛性。     

双变量矩阵方程组对称最小二乘解的迭代算法

本文研究了求双变量线性矩阵方程组的对称最小二乘解的问题.利用求解线性代数方程组的共轭梯度法的基本思想,通过对有关矩阵和系数的变形与近似处理,建立了一种迭代算法.拓宽了共轭梯度法的适用范围.算例表明,迭代算法是有效的.     

关于线性代数方程的一种迭代解法的收敛性问题

用迭代法求解线性代数方程组,已有大量的文献与专著,例如[4、6、7]。最常用的是逐次超松弛,及其种种变形。但是,许多情况表明这些方法并非完全令人满意的,特别对病态线性代数方程组,即方程组的系数矩阵有大的条件数,用这些方法求解时,收敛得相当慢。 [1]对求解病态常微分方程初值问题构造了一种恒稳格式。从线性代数方程组的解,等价于某一常微分方程组初值问题的稳态解,这一事实出发,从而构造了一种新的求解线性代数方程组的迭代解法。[1、2]某些计算实例表明,此迭代法特别适合于求解病态线性     

一类Toeplitz线性代数方程组的预处理GMRES方法

本文研究一类来源于分数阶特征值问题的Toeplitz线性代数方程组的求解.构造Strang循环矩阵作为预处理矩阵来求解该Toeplitz线性代数方程组,分析了预处理后系数矩阵的特征值性质.提出求解该线性代数方程组的预处理广义极小残量法（PGMRES）,并给出该算法的计算量.数值算例表明了该方法的有效性.     

一类非线性方程组的Newton-PSS迭代法

正定反Hermite分裂(PSS)方法是求解大型稀疏非Hermite正定线性代数方程组的一类无条件收敛的迭代算法.将其作为不精确Newton方法的内迭代求解器,我们构造了一类用于求解大型稀疏且具有非Hermite正定Jacobi矩阵的非线性方程组的不精确Newton-PSS方法,并对方法的局部收敛性和半局部收敛性进行了详细的分析.数值结果验证了该方法的可行性与有效性.     

提高有限元数值计算速度的一种途径

用有限元方法求解定解问题有许多优点.但由于它需要计算单体矩阵和合成总体矩阵,因此往往在形成线性代数方程组的过程中要花费较多的时间.这一点在求解的空间维数高、节点总数多,参数分布非均匀的情况下,矛盾尤为突出.本文对特定的定解问题,给出一种形成有限元方程组的方法,它比常规的方法能节省时耗.     

解可分离结构变分不等式的一种新的交替方向法

交替方向法是求解可分离结构变分不等式问题的经典方法之一, 它将一个大型的变分不等式问题分解成若干个小规模的变分不等式问题进行迭代求解. 但每步迭代过程中求解的子问题仍然摆脱不了求解变分不等式子问题的瓶颈. 从数值计算上来说, 求解一个变分不等式并不是一件容易的事情.因此, 本文提出一种新的交替方向法, 每步迭代只需要求解一个变分不等式子问题和一个强单调的非线性方程组子问题. 相对变分不等式问题而言, 我们更容易、且有更多的有效算法求解一个非线性方程组问题. 在与经典的交替方向法相同的假设条件下, 我们证明了新算法的全局收敛性. 进一步的数值试验也验证了新算法的有效性.     

带凸约束的非线性方程组的无导数记忆法

基于无导数线搜索技术和投影方法,本文提出了一种新的求解带凸约束的非线性方程组的无导数记忆法.该方法在每步迭代时不需要计算和贮存任何矩阵,因而适合求解大规模非线性方程组问题.在较弱条件下,该算法具有全局收敛性.数值试验结果及其相关的比较表明该算法是比较有效的.     

求解大型超定线性代数方程组的块Kaczmarz算法

正1 引言考虑大型超定线性代数方程组Ax=b,(1)其中 A ∈ C~(m×n) (m n),b ∈C~m.当m=n时,线性代数方程组求解的相关理论和算法较为成熟,但在很多实际问题中,系数矩阵A的行数和列数不相等(m≠n),如超定或欠定线性代数方程组.因此,有必要研究此类线性代数方程组的数值解法.在结构分析,计算机辅助几何设计,图像恢复,模型参数估计等众多领域中,经常需要求解大型超定线性代数方程组.Vuik [1]研究了大型超定线性代数方程组最小二乘问题的预处理Krylov迭代方法;Bai [2]提出列分解松弛法;Yin[3]提出了求解大型稀疏最小二乘问题的不完备Givens正交化的预处理GMRES方法;Hayami[4]考虑引入一个新的矩阵将GMRES方法应用到最小二乘问题,求得方程组的最小二乘解;Finta [5]推导了加权超定线性代数方程组的梯度法,并证明该方法是收敛的.     

约束Fractional Tikhonov正则化的模迭代方法

反问题是现在数学物理研究中的一个热点问题,而反问题求解面临的一个本质性困难是不适定性。求解不适定问题的普遍方法是:用与原不适定问题相“邻近”的适定问题的解去逼近原问题的解,这种方法称为正则化方法.如何建立有效的正则化方法是反问题领域中不适定问题研究的重要内容.当前,最为流行的正则化方法有基于变分原理的Tikhonov正则化及其改进方法,此类方法是求解不适定问题的较为有效的方法,在各类反问题的研究中被广泛采用,并得到深入研究.     

Preconditioned iterative methods for a class of nonlinear eigenvalue problems

This paper proposes new iterative methods for the efficient computation of the smallest eigenvalue of symmetric nonlinear matrix eigenvalue problems of large order with a monotone dependence on the spectral parameter. Monotone nonlinear eigenvalue problems for differential equations have important applications in mechanics and physics. The discretization of these eigenvalue problems leads to nonlinear eigenvalue problems with very large sparse ill-conditioned matrices monotonically depending on the spectral parameter. To compute the smallest eigenvalue of large-scale matrix nonlinear eigenvalue problems, we suggest preconditioned iterative methods: preconditioned simple iteration method, preconditioned steepest descent method, and preconditioned conjugate gradient method. These methods use only matrix-vector multiplications, preconditioner-vector multiplications, linear operations with vectors, and inner products of vectors. We investigate the convergence and derive grid-independent error estimates for these methods. Numerical experiments demonstrate the practical effectiveness of the proposed methods for a model problem.     

一种迭代格式的有限元并行算法*

本文提出了一种求解有限元方程的迭代格式的并行算法.该方法在线性代数方程迭代解法的基础上,引进并行运算步骤;并且运用加权残数方法,通过选择适当的权函数,推导了该并行算法的有限元基本格式.该方法在西安交通大学BLXSI-6400并行计算机上程序实现.计算结果表明它能有效地提高运算速度,减少计算时间,是一种有效的求解大型结构有限元方程的并行算法.     

A coupled finite element-differential quadrature element method and its accuracy for moving load problem

In this paper a mixed method, which combines the finite element method and the differential quadrature element method (DQEM), is presented for solving the time dependent problems. In this study, the finite element method is first used to discretize the spatial domain. The DQEM is then employed as a step-by-step DQM in time domain to solve the resulting initial value problem. The resulting algebraic equations can be solved by either direct or iterative methods. Two general formulations using the DQM are also presented for solving a system of linear second-order ordinary differential equations in time. The application of the formulation is then shown by solving a sample moving load problem. Numerical results show that the present mixed method is very efficient and reliable.     

Robust AMLI methods for parabolic Crouzeix-Raviart FEM systems

For the iterative solution of linear systems of equations arising from finite element discretization of elliptic problems there exist well-established techniques to construct numerically efficient and computationally optimal preconditioners. Among those, most often preferred choices are Multigrid methods (geometric or algebraic), Algebraic MultiLevel Iteration (AMLI) methods, Domain Decomposition techniques.In this work, the method in focus is AMLI. We extend its construction and the underlying theory over to systems arising from discretizations of parabolic problems, using non-conforming finite element methods (FEM). The AMLI method is based on an approximated block two-by-two factorization of the original system matrix. A key ingredient for the efficiency of the AMLI preconditioners is the quality of the utilized block two-by-two splitting, quantified by the so-called Cauchy-Bunyakowski-Schwarz (CBS) constant, which measures the abstract angle between the two subspaces, associated with the two-by-two block splitting of the matrix.The particular choice of space discretization for the parabolic equations, used in this paper, is Crouzeix-Raviart non-conforming elements on triangular meshes. We describe a suitable splitting of the so-arising matrices and derive estimates for the associated CBS constant. The estimates are uniform with respect to discretization parameters in space and time as well as with respect to coefficient and mesh anisotropy, thus providing robustness of the method.     

Coupled FEM-BEM for elastoplastic contact problems using Lagrange multipliers

The coupling of the elastoplastic finite element and elastic boundary element methods for two-dimensional frictionless contact stress analysis is presented. Interface traction matching (boundary element approach), which involves the force terms in the finite element analysis being transformed to tractions, is chosen for the coupling method. The analysis at the contact region is performed by the finite element method, and the Lagrange multiplier approach is used to apply the contact constraints. Since the analyses of elastoplastic problems are non-linear and involve iterative solution, the reduced size of the final system of equations introduced by combining the two methods is very advantageous, especially for contact problems where the nature of the problem also involves an iterative scheme.     

A stable primal–dual approach for linear programming under nondegeneracy assumptions

This paper studies a primal–dual interior/exterior-point path-following approach for linear programming that is motivated on using an iterative solver rather than a direct solver for the search direction. We begin with the usual perturbed primal–dual optimality equations. Under nondegeneracy assumptions, this nonlinear system is well-posed, i.e. it has a nonsingular Jacobian at optimality and is not necessarily ill-conditioned as the iterates approach optimality. Assuming that a basis matrix (easily factorizable and well-conditioned) can be found, we apply a simple preprocessing step to eliminate both the primal and dual feasibility equations. This results in a single bilinear equation that maintains the well-posedness property. Sparsity is maintained. We then apply either a direct solution method or an iterative solver (within an inexact Newton framework) to solve this equation. Since the linearization is well posed, we use affine scaling and do not maintain nonnegativity once we are close enough to the optimum, i.e. we apply a change to a pure Newton step technique. In addition, we correctly identify some of the primal and dual variables that converge to 0 and delete them (purify step). We test our method with random nondegenerate problems and problems from the Netlib set, and we compare it with the standard Normal Equations NEQ approach. We use a heuristic to find the basis matrix. We show that our method is efficient for large, well-conditioned problems. It is slower than NEQ on ill-conditioned problems, but it yields higher accuracy solutions.     

多孔介质二相驱动问题一种修正特征有限元方法的迭代解法及其收敛性分析

0 引言 多孔介质二相驱动问题的数学模型是由压力方程与浓度方程组成的偏微分方程组的初边值问题.关于该问题的数值解问题,已有大量的文献.为了得到最优的L~2-模误差估计,好多方法用混合元方法解压力方程.我们知道,混合元法得到的方程组系数矩阵是非正定的,从而解混合元比解标准元要困难得多,虽然许多人研究了混合元方法的求解问题,但到目前为止,还没有看到令人满意的好的算法.为了避开对混合元的求解,著名学者T.F.Russell考虑了用标准有限元方法解压力方程,用特征有限元方法解浓度方程的求解方法及其迭代解法,对只有分子扩散的二相驱动问题得到了最优的L~2模误差估计,对有机械弥散的一般二相驱动问题得不到最优的L~2模误差估计,同时在收敛性证明中要求压力有限元空间的指数至少是二.     

不定最小二乘问题的改进的不完全双曲Gram-Schmidt预处理算法

应用改进的不完全双曲Gram-Schmidt(IHMGS)方法预处理不定最小二乘问题的共轭梯度法(CGILS)、正交分解法(ILSQR)与广义的最小剩余法(GMRES)等迭代算法来求解大型稀疏的不定最小二乘问题.数值实验表明,IHMGS预处理方法可有效提高相应算法的迭代速度,且当矩阵的条件数比较大时,效果更加显著.     

A fast iterative method for solving stationary heat conduction problems on regions partitioned into rectangles

Summary The paper deals with some finite element approximation of stationary heat conduction problems on regions which can be partitioned into rectangular subregions. By a special superelement-technique employing fast elimination of the inner nodal parameters, the original finite element problem is reduced to a smaller problem, which is only connected with the nodes on the boundary of the superelements. To solve the reduced system of finite element equations, an efficient iterative algorithm is proposed. This algorithm is based either on the conjugate gradient method or the Tshebysheff method, using a special matrix by vector multiplication procedure. The explicit form of the matrix is not used. The presented numerical method is asymptotically optimal with respect to the memory requirement as well as to the operation count.