Symbolic computation of conservation laws for nonlinear partial differential equations in multiple space dimensions

A method for symbolically computing conservation laws of nonlinear partial differential equations (PDEs) in multiple space dimensions is presented in the language of variational calculus and linear algebra. The steps of the method are illustrated using the Zakharov–Kuznetsov and Kadomtsev–Petviashvili equations as examples.The method is algorithmic and has been implemented in Mathematica. The software package, ConservationLawsMD.m, can be used to symbolically compute and test conservation laws for polynomial PDEs that can be written as nonlinear evolution equations.The code ConservationLawsMD.m has been applied to multi-dimensional versions of the Sawada–Kotera, Camassa–Holm, Gardner, and Khokhlov–Zabolotskaya equations.     

几个非线性偏微分方程的非古典对称及相似解

研究了一些非线性偏微分方程的非古典势对称和非古典对称,得到了某些方程的新的势对称和新的对称,同时也得到了其伴随系统的新的对称,并求出了一些相似解．这些解对进一步研究这些非线性偏微分方程所描述的物理现象具有广泛的应用价值．     

An efficient numerical algorithm for multi-dimensional time dependent partial differential equations

An efficient and robust numerical scheme based on Haar wavelets and finite differences is suggested for the solution of two-dimensional time dependent linear and nonlinear partial differential equations (PDEs). Excellent feature of the scheme is the conversion of linear and non-linear PDEs to algebraic equations which are comparatively easy to handle. Convergence of the scheme, which guarantees small error norm as the resolution level increases, is also an important part of this work. Different error norms are computed to check efficiency of the technique. Computations verify accuracy, flexibility and low computational cost of the method.     

求一类非线性偏微分方程解析解的简洁构造算法

通过引入一个变换,利用齐次平衡原理和选准一个待定函数来构造求解一类非线性偏微分方程解析解的算法.作为实例,我们将该算法应用到了mKdV方程,KdV-Burgers方程和KdV-Burgers-Kuramoto方程.借助符号计算软件Mathematica获得了这些方程的解析解.不难看出,该方法不仅简洁,而且有望进一步扩展.     

多模态多目标差分进化算法求解非线性方程组

针对当前算法在求解非线性方程组时面临解的个数不完整、精确度不高、收敛速度慢等问题进行了研究,提出一种多模态多目标差分进化算法。首先将非线性方程组转换为多模态多目标优化问题,初始化一个随机种群并对种群中全部个体进行评价;然后通过非支配解排序和决策空间拥挤距离选择机制,挑选种群中的一半优质个体进行变异;接着在变异过程中采用一种新的变异策略和边界处理方法以增加解的多样性;最后通过交叉和选择机制使优质个体进行进化,直到搜索到全部最优解。在所选测试函数集和工程实例上的实验结果表明,该算法能有效地搜索到非线性方程组的解,并通过与当前四个算法进行比较,该算法在解的数量和成功率上具有优越性。     

High performance computing for partial differential equations

When representing realistic physical phenomena by partial differential equations (PDE), it is crucial to approximate the underlying physics correctly, to get precise results, and to efficiently use the computer architecture. Incorrect results can appear in incompressible Navier–Stokes or Stokes problems when the numerical approach couples into spurious modes. In Maxwell or magnetohydrodynamic (MHD) equations the so-called spectrum pollution effect can occur, and the numerical solution does not stably converge to the physical one. Problems coming from a mesh that is not adapted to the underlying physical problem, or from an inadequate choice of the dependent and independent variables can lead to low precision. Efficiency of a code implementation can be improved by well adapting the parallel computer to the application. A new monitoring system enables to detect poor implementations, to find best suited resources to execute the job, and to adapt the processor frequency during.     

Linearly implicit generalized trapezoidal formulas for nonlinear differential equations

We describe a linearlized version of the class of generalized trapezoidal formulas (GTFs) introduced in Chawla et al.[3]. For nonlinear differential equations, the obtained one-parameter class of linearly implicit generalized trapezoidal formulas (LIGTF(α)) obviate the need to solve a nonlinear system at each time step of integration, while they retain the order of accuracy and stability properties of the (functionally implicit) GTFs. The performance of the present LIGTF(α) is compared with the linearized linearly implicit trapezoidal formula (Lintrap) for nonlinear stiff ordinary differential equations (ODEs), and for nonlinear partial differential equations (PDEs) which represent nonlinear transportation-diffusion, nonlinear diffusion and nonlinear reaction-diffusion. Lintrap is known to produce unwanted oscilliations if the ratio of the time step to the spatial step becomes large. In our numerical experiments, the significance of the role played by the parameter in LIGTF(α) becomes evident in providing both stability and accuracy of the computed solution in the presence of diffusivity.     

A reduce package for determining lie symmetries of ordinary and partial differential equations

Title of program: LIE0,LIE1,LIE2,LIE3,LIE4 Catalogue number: AAZB Program obtainable form: CPC Program library, Queen's University in Belfast, N. Ireland (see application form in this issue) Computer: Siemens 7.760 Operating system: BS 2000 Programming language used: LISP High speed storage required: depends on the problem, minimum about 400 000 bytes No. of bits in a word: 32 Number of cards in combined program and test deck: 200     

非线性偏微分方程数值求解的自适应方法研究

对小波理论在偏微分方程数值求解中的应用进行深入研究的基础上,提出了一种自适应求解非线性偏微分方程的算法——小波最优有限差分法。并以非线性Burgers方程为例,分别用小波最优有限差分法和直线法对它进行数值求解,显示了小波最优有限差分法在数值求解非线性问题时的自适应性、高效性和可行性。     

A multiprocessor architecture for solving nonlinear partial differential equations

This paper presents the architecture of a special-purpose multiprocessor system, which we call the Broadcast Cube System (BCS), for solving non-linear Partial Differential Equations (PDEs). The BCS has the following important features: (a) Being based on the conceptually simple bus interconnection scheme it is easily understood. The use of homogeneous Processing Elements (PEs) which can be realized as standard VLSI chips makes the hardware less costly. (b) The interconnection network is simple and regular. The network can easily be extended to vast number of PEs by adding buses with new PEs on them and by slightly increasing the number of PEs on existing buses. The interconnection pattern is highly redundant to support fault tolerance in the event of PE failures. (c) In terms of the switching delays, the delay a message undergoes between a pair of PEs connected to a common bus is zero. The maximum delay between any pair of PEs is one unit and thus a strong localization of communicating tasks is not needed to avoid long message delays even in networks of thousands of PEs. The effectiveness of the BCS has been demonstrated by both analytical and simulation methods using heat transfer and fluid flow simulation, which requires solution of non-linear PDEs, as a benchmark program.     

Moving mesh methods for solving parabolic partial differential equations

A new adaptive method is described for solving nonlinear parabolic partial differential equations with moving boundaries, using a moving mesh with continuous finite elements. The evolution of the mesh within the interior of the spatial domain is based upon conserving the distribution of a chosen monitor function across the domain throughout time, where the initial distribution is selected based upon the given initial data. The mesh movement at the boundary is governed by a second monitor function, which may or may not be the same as that used to drive the interior mesh movement. The method is described in detail and a selection of computational examples are presented using different monitor functions applied to the porous medium equation (PME) in one and two space dimensions.     

Second-order predictor-corrector schemes for nonlinear distributed-order space-fractional differential equations with non-smooth initial data

ABSTRACT

We propose second-order linearly implicit predictor-corrector schemes for diffusion and reaction-diffusion equations of distributed-order. For diffusion equations of distributed order, we propose an analytical solution based on the spectral representation of the fractional Laplacian. Numerically, we approximate the integral term of the equation by the midpoint quadrature rule to obtain a multi-term space-fractional differential equation. The matrix transfer technique is used for spatial discretization of the resulting differential equation and methods based on Padé approximations to the exponential function are used in time. In particular, we discuss the (0,2)- and (1,1)-Padé approximations to the exponential function. The method based on the (1,1)-Padé approximation to the exponential function are seen to produce oscillations for some time steps and we propose a constraint on the choice of the time step to avoid these unwanted oscillations. Stability and convergence of the schemes are discussed. Numerical experiments are performed to support our theoretical observations.     

混合整数非线性规划问题的改进差分进化算法*

提出一种改进差分进化算法求解混合整数非线性规划问题。该算法利用同态映射方法,解决差分进化算法无法直接处理整数决策变量问题;提出改进的自适应交替变异算子,提高算法的搜索性能;提出一种自适应保留不可行解的方法处理约束条件,并对差分进化算法的选择算子进行改进,提出一种直接处理约束条件的新选择算子。六个常用的混合整数非线性规划问题的实验结果表明了该方法的有效性和适用性。     

基于极大熵差分进化混合算法求解非线性方程组*

针对非线性方程组,给出了一种新的算法——极大熵差分进化混合算法。首先把非线性方程组转换为一个不可微优化问题;然后用一个称之为凝聚函数的光滑函数直接代替不可微的极大值函数,从而可把非线性方程组的求解转换为无约束优化问题,利用差分进化算法对其进行求解。计算结果表明,该算法在求解的准确性和有效性均优于其他算法。     

求解非线性方程的蛛网-迭代算法

用蛛网迭代算法求解非线性方程,只要求函数在定义域内存在反函数;由定理及其证明可知,不动点迭代是该迭代方法的特殊情况;通过数值实验进一步证明了该方法的有效性和实用性。     

基于伪谱展开的抛物型系统镇定与边界观测研究(英文)

模型截断设计方法在无限维系统控制中得到广泛的应用,但是其自身存在信息丢失的缺陷而限制了控制器对高频扰动抑制的性能.本文研究具有内部和Neumann边界控制的抛物型系统,其中系统采用边界测量.内部控制采用比例反馈形式,其中反馈增益核由Sturm-Liouville系统稳定性分析来待定;类似地,边界反馈的设计也采用待定反馈增益核的方式,最终对描述系统稳定性的Sturm-Liouville系统采用伪谱方法进行求解.数字仿真结果表明了该方法的有效性.     

闭包算子与邻域系的广义化

通过弱化一般拓扑中的闭包算子公理,引入了广义闭包算子的概念,研究了其与稍早引入的广义邻域系的关系。特别的,证明了二者之间存在着自然的完备格同构。     

一种新的多输入非线性控制系统线性化的计算方法

通常, 即使对于一个可逼近反馈线性化的非线性系统, 求得一个所需的坐标变换和反馈仍然是困难的, 原因在于需要求解一组偏微分方程. 在本文中, 为了求得逼近反馈线性化所需的非线性反馈及坐标变换, 首先引入了一个扩展的坐标空间, 针对一类线性可控的多输入非线性系统, 推导了系统新的矩阵表达式. 然后, 提出了一种新的有效的构造化算法, 它降低了计算所需的运算量. 最后通过一个例子介绍了本方法的应用.     

On the convergence of variational iteration method for nonlinear coupled system of partial differential equations

In this paper, the sufficient conditions that guarantee the convergence of the variational iteration method when applied to solve a coupled system of nonlinear partial differential equations are presented. Especial attention is given to the error bound of the nth term of the resultant sequence. Numerical examples to show the efficiency of the method are presented.