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Numerical study of three-dimensional Turing patterns using a meshless method based on moving Kriging element free Galerkin (EFG) approach

机译:基于无Kriging元素自由Galerkin(EFG)方法的无网格方法三维图灵模式的数值研究

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In this paper a numerical procedure is presented for solving a class of three-dimensional Turing system. First, we discrete the spatial direction using element free Galerkin (EFG) method based on the shape functions of moving Kriging interpolation. Then, to achieve a high-order accuracy, we use the fourth-order exponential time differencing Runge-Kutta (ETDRK4) method. Using this discretization for the temporal dimension, we obtain an explicit scheme and do not need to solve nonlinear system of equations. The EFG method uses a weak form of the considered equation that is similar to the finite element method with the difference that in the EFG method test and trial functions are moving least squares approximation (MLS) shape functions. Since the shape functions of moving least squares (MLS) approximation do not have Kronecker delta property, we cannot implement the essential boundary condition, directly. Also building shape functions of MLS approximation is a time consuming procedure. Because of the mentioned reasons we employ the shape functions of moving Kriging interpolation technique which have the mentioned property and less CPU time is required for building them. For testing this method on three-dimensional PDEs, we select some equations and system of PDEs such as Allen-Cahn, Gray-Scott, Ginzburg-Landau, Brusselator models, predator-prey model with additional food supply to predator. Several test problems are solved and numerical simulations are reported which confirm the efficiency of the proposed scheme. (C) 2016 Elsevier Ltd. All rights reserved.
机译:本文提出了一种求解一类三维图灵系统的数值程序。首先,我们基于移动克里格插值的形状函数,使用无元素伽勒金(EFG)方法离散空间方向。然后,为了获得高阶精度,我们使用四阶指数时间差Runge-Kutta(ETDRK4)方法。使用时间维的离散化,我们获得了一个显式方案,不需要求解非线性方程组。 EFG方法使用的考虑方程式的弱形式类似于有限元方法,不同之处在于EFG方法中的测试和试验函数为移动最小二乘近似(MLS)形状函数。由于移动最小二乘(MLS)逼近的形状函数不具有Kronecker delta属性,因此我们无法直接实现基本边界条件。建立MLS近似的形状函数也是一个耗时的过程。由于上述原因,我们采用了具有上述特性的移动Kriging插值技术的形状函数,并且构建它们所需的CPU时间更少。为了在三维PDE上测试该方法,我们选择了PDE的方程和系统,例如Allen-Cahn,Gray-Scott,Ginzburg-Landau,Brusselator模型,带有捕食者的额外食物的捕食者-猎物模型。解决了一些测试问题,并报告了数值模拟,证实了所提方案的有效性。 (C)2016 Elsevier Ltd.保留所有权利。

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