一类非线性对流扩散方程两重网格特征有限元方法及误差估计

主要研究了一类非线性对流扩散方程的全离散特征有限元方法的两重网格算法及其误差估计.首先在网格步长为H的粗网格上计算一个较小的非线性问题,然后利用一阶牛顿迭代和粗网格解将网格步长为h的细网格上的非线性问题转化为线性问题求解.由于非线性问题的求解仅在粗网格上进行,该两重网格算法可以节省大量的计算工作量,同时具有较高的精度,证明了该两重网格算法L~2模先验误差估计结果为O(△t+h~2+H~(4-d/2)),其中d为空间维数.     

求解Navier-Stokes方程最优控制问题的移动网格方法

提出了一种受偏微分方程约束最优控制问题的移动网格方法,并以NavierStokes方程为状态方程进行了研究.所采用的网格移动策略中节点距离的移动是通过求解一个扩散方程得到.设计出了有效的求解流体力学最优控制问题的算法,给出了算法的实施过程.提供的数值算例说明所提算法可以在保证高精度数值解的前提下稳定、高效的求解最优控制问题.     

求解复系数椭圆方程的两层网格算法

<正>1引言两层网格方法是用来求解非对称不定问题和非线性问题的一种非常有效的数值方法[1,2].其主要思想是,借助于两层网格空间,将细网格上的复杂问题转化为求解一个细网格空间的简单问题和一个粗网格上的问题.由于粗网格空间相对于细网格空间很小,所以减少了计算代价,并且仍能得到原问题的最优解.因此,两层网格算法被广泛研究并被用于求解多种问题,例如,求解非对称和非线性椭圆方程[1,2,3,4],非线性弹性方程[5],Navier-Stokes方程[6,7,8]及特征值问题[9,10].HSS迭代方法是求解大规模稀疏非埃尔米特正定     

求解定常不可压Stokes方程的两层罚函数方法

借助于两套有限元网格空间提出了一种求解定常不可压Stokes方程的两层罚函数方法.该方法只需要求解粗网格空间上的Stokes方程和细网格空间上的两个易于求解的罚参数方程（离散后的线性方程组具有相同的对称正定系数矩阵）.收敛性分析表明粗网格空间相对于细网格空间可以选择很小，并且罚参数的选取只与粗网格步长和问题的正则性有关.因此罚参数不必选择很小仍能够得到最优解.最后通过数值算例验证了上述理论结果，并且数值对比可知两层罚函数方法对于求解定常不可压Stokes方程具有很好的效果.     

耦合Navier-Stokes/Darcy模型多重网格方法的有限元实现(英文)

本文研究耦合Navier-Stokes/Darcy模型问题.构造一种从粗网格到细网格的有限元空间插值方法,不但简化了数值积分的单元匹配,也保证了数值积分的精度.利用基于有限元空间的多重网格方法,获得与直接法求解耦合问题误差相同的收敛阶,推广两重网格方法的结果.     

大Reynolds数Navier-Stokes方程带回溯技巧的两水平方法

本文考虑了一种求解大Reynolds数定常Navier-Stokes方程带回溯(backtracking)技巧的两水平有限元方法.其基本思想是,首先在一粗网格上求解带有亚格子模型稳定项的Navier-Stokes方程,然后在细网格上求解一个亚格子模型稳定化的线性Newton问题,最后又回到粗网格上求解线性化的校正问题.通过适当的稳定化参数和粗细网格尺寸的选取,本文的算法能取得最优渐近收敛阶.数值实验检验了理论分析的正确性和算法的有效性.     

Algorithm Research Based on the PDE Sensitivity Filter北大核心CSCD

采用PDE灵敏度滤波器可以消除连续体结构拓扑优化结果存在的棋盘格现象、数值不稳定等问题,且PDE灵敏度滤波器的实质是具有Neumann边界条件的Helmholtz偏微分方程.针对大规模PDE灵敏度滤波器的求解问题,有限元分析得到其代数方程,分别采用共轭梯度算法、多重网格算法和多重网格预处理共轭梯度算法对代数方程进行求解,并且研究精度、过滤半径以及网格数量对拓扑优化效率的影响.结果表明：与共轭梯度算法和多重网格算法相比,多重网格预处理共轭梯度算法迭代次数最少,运行时间最短,极大地提高了拓扑优化效率.     

基于卷积神经网络模型数值求解双曲型偏微分方程的研究

人工神经网络近年来得到了快速发展,将此方法应用于数值求解偏微分方程是学者们关注的热点问题.相比于传统方法其具有应用范围广泛（即同一种模型可用于求解多种类型方程）、网格剖分条件要求低等优势,并且能够利用训练好的模型直接计算区域中任意点的数值.该文基于卷积神经网络模型,对传统有限体积法格式中的权重系数进行优化,以得到在粗粒度网格下具有较高精度的新数值格式,从而更适用于复杂问题的求解.该网络模型可以准确、有效地求解Burgers方程和level set方程,数值结果稳定,且具有较高数值精度.     

有限元网格的超收敛测度及其应用

给出线性有限元求解二阶椭圆问题的有限元网格超收敛测度及其应用.有限元超收敛经常是在具有一定结构的特殊网格条件下讨论的,而本文从一般网格出发,导出一种网格的范数用来描述超收敛所需要的网格条件以及超收敛的程度.并且通过对这种网格范数性质的考察,可以证明对于通常考虑的一些特殊网格的超收敛的存在性.更进一步,我们可以通过正则细分的方式在一般区域上也可以自动获得超收敛网格.最后给出相关的数值结果来验证本文的理论分析.     

基于虚节点的多边形有限元法

虚节点法是一种新的基于单位分解理论的多边形有限元法.将虚节点法应用于求解弹性力学问题,并且通过大量数值实验测试虚节点法的计算效果.因为虚节点法具有多项式形式,所以有效地降低了传统多边形有限元法的积分误差.数值实验证明,在分片实验中虚节点法能得到比包括Wachspress法和mean value法在内的传统多边形有限元法更精确的数值结果.在收敛性试验中,虚节点法在相同节点数的条件下能取得比三角形一次单元更精确的数值结果.因为虚节点法能适应任意边数的多边形单元,所以对网格具有很强的适应性,在几何条件复杂、网格生成困难的问题中具有良好的应用价值.为了展示虚节点法潜在的应用价值,用虚节点法求解断裂力学应力强度因子和模拟裂纹扩展.同时,基于多边形单元的网格重划分技术和网格加密技术也应用于求解断裂力学应力强度因子和模拟裂纹扩展.     

计数型二次序贯网图检验

序贯概率比检验(SPRT)是应用非常广泛的抽样检验方法, 序贯网图检验在控制最大样本量方面很好地改进了SPRT, 但其结果还有进一步改进的余地, 为此, 我们建立了二次序贯网图检验, 计算结果表明, 它比原先的计数序贯网图检验有更好的效果.     

A modified Bakhvalov mesh

We consider a few numerical methods for solving a one-dimensional convection–diffusion singularly perturbed problem. More precisely, we introduce a modified Bakvalov mesh generated using some implicitly defined functions. Properties of this mesh and convergence results for several methods on it are given. Numerical results are presented in support of the theoretical considerations.     

A piecewise constant collocation method using cosine mesh grading for Symm's equation

Summary Here we study the piecewise constant collocation method using mesh grading to solve Symm's integral equation on [–1, 1]. We give a mesh grading for which this method achieves the optimal order of convergence even though the piecewise constant Galerkin method with the same mesh grading does not. Some numerical results are given.     

A TWO-LEVEL FINITE ELEMENT GALERKIN METHOD FOR THE NONSTATIONARY NAVIER-STOKES EQUATIONS II： TIME DISCRETIZATION

In this article we consider the fully discrete two-level finite element Galerkin method for the two-dimensional nonstationary incompressible Navier-Stokes equations. This method consists in dealing with the fully discrete nonlinear Navier-Stokes problem on a coarse mesh with width $H$ and the fully discrete linear generalized Stokes problem on a fine mesh with width $h << H$. Our results show that if we choose $H=O(h^{1/2}$) this method is as the same stability and convergence as the fully discrete standard finite element Galerkin method which needs dealing with the fully discrete nonlinear Navier-Stokes problem on a fine mesh with width $h$. However, our method is cheaper than the standard fully discrete finite element Galerkin method.     

A mathematical model of a mesh system and its implementation

We define and implement a mathematical model for a general 2-d mesh system, which is arrays of processors with a bounded mesh architecture. As one of the simplest distributed architecture with fixed-connection, the 2-d mesh system has found many applications in computer sciences and engineering, particularly in computer communication.

We use mathematical structures to characterize the mesh system and use C to have implemented an executable version of this model. In this paper, we will present the mathematical model itself, discuss some corresponding implementation issues and compare its behaviors with a simulator which we have been using to observe system behaviors.     

A conforming finite element method for overlapping and nonmatching grids

In this paper we propose a finite element method for nonmatching overlapping grids based on the partition of unity. Both overlapping and nonoverlapping cases are considered. We prove that the new method admits an optimal convergence rate. The error bounds are in terms of local mesh sizes and they depend on neither the overlapping size of the subdomains nor the ratio of the mesh sizes from different subdomains. Our results are valid for multiple subdomains and any spatial dimensions.

     

A TWO-LEVEL FINITE ELEMENT GALERKIN METHOD FOR THE NONSTATIONARY NAVIER-STOKES EQUATIONS I： SPATIAL DISCRETIZATION

In this article we consider a two-level finite element Galerkin method using mixed finite elements for the two-dimensional nonstationary incompressible Navier-Stokes equations. The method yields a $H^1$-optimal velocity approximation and a $L_2$-optimal pressure approximation. The two-level finite element Galerkin method involves solving one small, nonlinear Navier-Stokes problem on the coarse mesh with mesh size $H$, one linear Stokes problem on the fine mesh with mesh size $h << H$. The algorithm we study produces an approximate solution with the optimal, asymptotic in $h$, accuracy.     

A Modification of the Shishkin Discretization Mesh

In this paper we consider a modification of the Shishkin discretization mesh designed for the numerical solution of one-dimensional linear convection-diffusion singularly perturbed problems. The modification consists of a slightly different choice of the transition point between the fine and coarse parts of the mesh. This leads to a better layer-resolving mesh and to an improvement in the accuracy of the computed solution although the convergence order remains the same. (© 2013 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A mesh simplification strategy for a spatial regression analysis over the cortical surface of the brain

We present a new mesh simplification technique developed for a statistical analysis of a large data set distributed on a generic complex surface, topologically equivalent to a sphere. In particular, we focus on an application to cortical surface thickness data. The aim of this approach is to produce a simplified mesh which does not distort the original data distribution so that the statistical estimates computed over the new mesh exhibit good inferential properties. To do this, we propose an iterative technique that, for each iteration, contracts the edge of the mesh with the lowest value of a cost function. This cost function takes into account both the geometry of the surface and the distribution of the data on it. After the data are associated with the simplified mesh, they are analyzed via a spatial regression model for non-planar domains. In particular, we resort to a penalized regression method that first conformally maps the simplified cortical surface mesh into a planar region. Then, existing planar spatial smoothing techniques are extended to non-planar domains by suitably including the flattening phase. The effectiveness of the entire process is numerically demonstrated via a simulation study and an application to cortical surface thickness data.