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Continuous Genetic Algorithm as a Novel Solver for Stokes and Nonlinear Navier Stokes Problems

机译:连续遗传算法作为斯托克斯和非线性南北斯托克斯问题的新求解器

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摘要

The one-dimensional continuous genetic algorithm (CGA) previously developed by the principal author is extended and enhanced to deal with two-dimensional spaces in this paper. The enhanced CGA converts the partial differential equations into algebraic equations by replacing the derivatives appearing in the differential equation with their proper finite difference formula in 2D spaces. This optimization methodology is then applied for the solution of steady-state two-dimensional Stokes and nonlinear Navier Stokes problems. The main advantage of using CGA for the solution of partial differential equations is that the algorithm can be applied to linear and nonlinear equations without any modification in its structure. A comparison between the results obtained using the 2D CGA and the known Galerkin finite element method using COMSOL is presented in this paper. The results showed that CGA has an excellent accuracy as compared to other numerical solvers.
机译:先前由主要作者开发的一维连续遗传算法(CGA)延长并增强,以处理本文的二维空间。增强的CGA通过用它们在2D空间中的适当有限差分公式替换出现在微分方程中的衍生物,将部分微分方程转换为代数方程。然后应用这种优化方法用于稳态二维斯托克斯和非线性Navier Stokes问题的解决方案。使用CGA对于偏微分方程的解决方案的主要优点是该算法可以应用于线性和非线性方程,而不在其结构中进行任何修改。本文介绍了使用2D CGA和已知的Galerkin有限元方法获得的结果与使用COMSOL的结果进行比较。结果表明,与其他数值溶剂相比,CGA具有优异的精度。

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