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Some new periodic solitary wave solutions of (3+1)-dimensional generalized shallow water wave equation by Lie symmetry approach

机译:用谎言对称方法(3 + 1) - 二维广义浅水波方程的一些新的周期性波解

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Many important physical situations such as fluid flows, marine environment, solid-state physics and plasma physics have been represented by shallow water wave equations. In this article, we construct new solitary wave solutions for the (3+1)-dimensional generalized shallow water wave (GSWW) equation by using optimal system of Lie symmetry vectors. The governing equation admits twelve Lie dimension space. A variety of analytic (closed-form) solutions such as new periodic solitary wave, cross-kink soliton and doubly periodic breather-type solutions have been obtained by using invariance of the concerned (3+1)-dimensional GSWW equation under one-parameter Lie group of transformations. Lie symmetry transformations have applied to generate the different forms of invariant solutions of the (3+1)-dimensional GSWW equation. For different Lie algebra, Lie symmetry method reduces (3+1)-dimensional GSWW equation into various ordinary differential equations (ODEs) while one of the Lie algebra, it is transformed into the well known (2+1)-dimensional BLMP equation. It is affirmed that the proposed techniques are convenient, genuine and powerful tools to find the exact solutions of nonlinear partial differential equations (PDEs). Under the suitable choices of arbitrary functions and parameters, 2D, 3D and contour graphics to the obtained results of GSWW equation are also analyzed. (C) 2019 Elsevier Ltd. All rights reserved.
机译:许多重要的物理情况,例如流体流动,海洋环境,固态物理和等离子体物理学已经由浅水波方程表示。在本文中,通过使用LIE对称向量的最优系统,为(3 + 1) - 二维广义浅水波(GSWW)方程构建新的孤波解。管理方程承认十二个谎言尺寸空间。通过在一个参数下使用所涉及的(3 + 1)-dimensional GSWW方程的不变性获得了新的周期性孤波,交叉扭结孤独和双周期性通气型解决方案的各种分析(闭合形式)解决方案谎言转换。 LID对称转换已应用于生成(3 + 1)-dimensional GSWW方程的不同形式的不变解。对于不同的Lie代数,Lie对称方法将(3 + 1) - 二维GSWW方程降低到各种常规方程(ODES)中,而LIE代数之一,它被转化为众所周知的(2 + 1)-dimensionalBLMP方程。肯定是拟议的技术方便,真正和强大的工具,用于找到非线性偏微分方程(PDES)的精确解。在合适的任意功能选择下,还分析了GSWW方程的所获得的结果的2D,3D和轮廓图形。 (c)2019 Elsevier Ltd.保留所有权利。

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