On the Explicit Two-Stage Fourth-Order Accurate Time Discretizations

This paper continues to study the explicit two-stage fourth-order accurate time discretizations [5-7]. By introducing variable weights, we propose a class of more general explicit one-step two-stage time discretizations, which are different from the existing methods, e.g. the Euler methods, Runge-Kutta methods, and multistage multiderivative methods etc. We study the absolute stability, the stability interval, and the intersection between the imaginary axis and the absolute stability region. Our results show that our two-stage time discretizations can be fourth-order accurate conditionally, the absolute stability region of the proposed methods with some special choices of the variable weights can be larger than that of the classical explicit fourth- or fifth-order Runge-Kutta method, and the interval of absolute stability can be almost twice as much as the latter. Several numerical experiments are carried out to demonstrate the performance and accuracy as well as the stability of our proposed methods.     

多步Runge-Kutta型TVB时间离散

近年来TVD,TVB和ENO方法出现并得到广泛应用,见[1]—[8].特别,在[6]—[8]中利用线方法和时间离散的结合构造了TVD,TVB和 ENO差分格式.整个构造过程较Harten的工作简化得多,从而开辟了一条构造高精度无振荡差分格式的新途径.他在[6],[8]中讨论了线性多步TVB时间离散,在[7]中又讨论了Runge-Kutta型TVD时间离散,并得到了时间离散在TVD,TVB意义下所应满足的条件.本     

Spectral Optimization Methods for the Time Fractional Diffusion Inverse Problem

An inverse problem of reconstructing the initial condition for a time fractional diffusion equation is investigated. On the basis of the optimal control framework, the uniqueness and first order necessary optimality condition of the minimizer for the objective functional are established, and a time-space spectral method is proposed to numerically solve the resulting minimization problem. The contribution of the paper is threefold: 1) a priori error estimate for the spectral approximation is derived; 2) a conjugate gradient optimization algorithm is designed to efficiently solve the inverse problem; 3) some numerical experiments are carried out to show that the proposed method is capable to find out the optimal initial condition, and that the convergence rate of the method is exponential if the optimal initial condition is smooth.     

求解三维Wilson元离散化线性系统的PCG方法

非协调元方法是克服三维弹性问题体积闭锁的一种有效方法,它具有自由度少、精度高等优点,但要提高其有限元分析的整体效率还必须为相应的离散化系统设计快速求解算法.考虑了Wilson元离散化系统的快速求解.当Poisson(泊松)比ν→0.5时,该离散系统为一高度病态的正定方程组,预处理共轭梯度(PCG)法是求解这类方程组最为有效的方法之一.另外,在实际应用中,由于结构的特殊性,网格剖分时常常会产生具有大长宽比的各向异性网格,这也将大大影响PCG法的收敛性.该文设计了一种基于"距离矩阵"的代数多重网格(DAMG)法的PCG法,并应用于近不可压缩问题Wilson元离散系统的求解.这种基于"距离矩阵"的代数多重网格法,能更有效地求解各向异性网格问题,再结合有效的磨光算子,相应的PCG法对求解近不可压缩问题具有很好的鲁棒性(robustness)和高效性.     

On Polynomial Time Methods for Exact Low-Rank Tensor Completion

Foundations of Computational Mathematics - In this paper, we investigate the sample size requirement for exact recovery of a high-order tensor of low rank from a subset of its entries. We show that...     

Numerical Solution of Contact Problems using Level Set Methods on Voxel Discretizations

Fast solvers performing on a regular grid are often used for problems in elasticity, in order to avoid expensive mesh generations. However, if overlaps between solid materials occur without any interactions, these might deteriorate the results, especially for the stresses. Therefore, we want to present an approach for developing numerical methods for contact problems on a regular mesh with the help of signed distance data and multi-material voxels. In this contribution we will focus on problems in linear elastostatics with contact between several different bodies. Finally, we present the results from a numerical test for the two dimensional Hertz problem, solved on a triangular regular mesh. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

KdV方程的时间谱离散方法

本文提出了解KdV方程周期边值问题的安全港离散方法:在时间方向上采用Chebyshev拟谱逼近,在空间方向上采用Fourier Galerkin逼近。谱展开的系数由目标泛函的极小值来确定。同时证明了该方法的收敛性。     

二维不可压缩流的谱方法

本文以二维涡度方程为模型,介绍了谱方法和拟谱方法以及它们与差分方法和有限元法相结合的混合解法．这些方法可推广应用于其它一些类似的非线性问题．本文还给出了这些方法的某些数值例子和误差估计结果     

Spectral Gradient Methods for Linearly Constrained Optimization

Linearly constrained optimization problems with simple bounds are considered in the present work. First, a preconditioned spectral gradient method is defined for the case in which no simple bounds are present. This algorithm can be viewed as a quasi-Newton method in which the approximate Hessians satisfy a weak secant equation. The spectral choice of steplength is embedded into the Hessian approximation and the whole process is combined with a nonmonotone line search strategy. The simple bounds are then taken into account by placing them in an exponential penalty term that modifies the objective function. The exponential penalty scheme defines the outer iterations of the process. Each outer iteration involves the application of the previously defined preconditioned spectral gradient method for linear equality constrained problems. Therefore, an equality constrained convex quadratic programming problem needs to be solved at every inner iteration. The associated extended KKT matrix remains constant unless the process is reinitiated. In ordinary inner iterations, only the right-hand side of the KKT system changes. Therefore, suitable sparse factorization techniques can be applied and exploited effectively. Encouraging numerical experiments are presented.This research was supported by FAPESP Grant 2001-04597-4 and Grant 903724-6, FINEP and FAEP-UNICAMP, and the Scientific Computing Center of UCV. The authors thank two anonymous referees whose comments helped us to improve the final version of this paper.     

Spectral Methods in PDE

This is to review some recent progress in PDE. The emphasis is on (energy) supercritical nonlinear Schrödinger equations. The methods are applicable to other nonlinear equations.     

On Generalizations of the Pentagram Map: Discretizations of AGD Flows

In this paper we investigate discretizations of AGD flows whose projective realizations are defined by intersecting different types of subspace in $\mathbb{RP}^{m}$ . These maps are natural candidates to generalize the pentagram map, itself defined as the intersection of consecutive shortest diagonals of a convex polygon, and a completely integrable discretization of the Boussinesq equation. We conjecture that the r-AGD flow in m dimensions can be discretized using one (r?1)-dimensional subspace and r?1 different (m?1)-dimensional subspaces of $\mathbb{RP}^{m}$ .     

计算流体力学中的谱方法

本文论及偏微分方程数值解中的谱方法的理论基础和数值实现．评述近年来有关谱方法的最主要的几个研究领域，着重讨论区域分解技术，不同数学模型的耦合以及不同离散方法的耦合问题，并介绍一些最新结果．     

Spectral Deferred Correction Methods for Ordinary Differential Equations

We introduce a new class of methods for the Cauchy problem for ordinary differential equations (ODEs). We begin by converting the original ODE into the corresponding Picard equation and apply a deferred correction procedure in the integral formulation, driven by either the explicit or the implicit Euler marching scheme. The approach results in algorithms of essentially arbitrary order accuracy for both non-stiff and stiff problems; their performance is illustrated with several numerical examples. For non-stiff problems, the stability behavior of the obtained explicit schemes is very satisfactory and algorithms with orders between 8 and 20 should be competitive with the best existing ones. In our preliminary experiments with stiff problems, a simple adaptive implementation of the method demonstrates performance comparable to that of a state-of-the-art extrapolation code (at least, at moderate to high precision).Deferred correction methods based on the Picard equation appear to be promising candidates for further investigation.     

JACOBI SPECTRAL METHODS FOR MULTIPLE—DIMENSIONAL SINULAR DIFFERENTIAL EQUATIONS

Jacobi polynomial approximations in multiple dimensions are investigated.They are applied to numerical solutions of singular differential equations.The convergence analysis and numerical results show their advantages.     

Isogeometric Collocation: Cost Comparison with Galerkin Methods and Extension to Adaptive Hierarchical NURBS Discretizations

Collocation is based on the discretization of the strong form of the underlying partial differential equations, which requires basis functions of sufficient order and smoothness. Consequently, the use of isogeometric analysis (IGA) for collocation suggests itself, since splines can be readily adjusted to any order in polynomial degree and continuity required by the differential operators. In addition, they can be generated for domains of arbitrary geometric and topological complexity, directly linked to and fully supported by CAD technology. The major advantage of isogeometric collocation over Galerkin type IGA is the minimization of the computational effort for numerical quadrature. (© 2013 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Local Fourier Analysis for Edge-Based Discretizations on Triangular Grids

In this paper, we present a local Fourier analysis framework for analyzing the different components within multigrid solvers for edge-based discretizations on triangular grids. The different stencils associated with edges of different orientation in a triangular mesh make this analysis special. The resulting tool is demonstrated for the vector Laplace problem discretized by mimetic finite difference schemes. Results from the local Fourier analysis, as well as experimentally obtained results, are presented to validate the proposed analysis.     

非线性守恒方程的两种稳定化谱元方法

考虑非线性守恒方程的高阶数值解法,介绍了基于谱元法的两种稳定性方法,一种是谱粘性消去法(SVV),另一种是过滤法.在SVV方法中,我们推广并分析了传统的基于单区域的SVV算子的定义.在过滤法中,我们分析了SVV-H elm holtz过滤算子的性质.文中从分析和计算两方面对两种方法进行了比较,建立了两者之间的关系.最后通过一系列数值试验说明方法的有效性.     

Well-Conditioned Spectral Collocation Methods for Problems in Unbounded Domains

Based on the generalized Laguerre and Hermite functions, we construct two types of Birkhoff-type interpolation basis functions. The explicit expressions are derived, and fast and stable algorithms are provided for computing these basis functions. As applications, some well-conditioned collocation methods are proposed for solving various second-order differential equations in unbounded domains. Numerical experiments illustrate that our collocation methods are more efficient than the standard Laguerre/Hermite collocation approaches.