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Operator-splitting methods in respect of eigenvalue problems for nonlinear equations and applications for Burgers equations

机译:关于非线性方程特征值问题的算子分解方法及其在Burgers方程中的应用

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摘要

In this article we consider iterative operator-splitting methods for nonlinear differential equations with respect to their eigenvalues. The main focus of the proposed idea is the fixed-point iterative scheme that linearizes our underlying equations. Oil the basis of the approximated eigenvalues of such linearized systems we choose the order of the operators for our iterative splitting scheme. The convergence properties of such a mixed method are studied and demonstrated. We confirm with numerical applications the effectiveness of the proposed scheme in comparison with the standard operator-splitting methods by providing improved results and convergence rates. We apply our results to deposition processes.
机译:在本文中,我们考虑针对非线性微分方程的特征值的迭代算子分解方法。提出的想法的主要焦点是使我们的基本方程线性化的定点迭代方案。在此类线性化系统的近似特征值的基础上,我们选择迭代分裂方案的算子顺序。研究并证明了这种混合方法的收敛性。通过提供改进的结果和收敛速度,我们在数值应用中证实了与标准算子拆分方法相比,该方案的有效性。我们将结果应用于沉积过程。

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