4.4 Article

Numerical solution of Lane-Emden type equations using Adomian decomposition method with unequal step-size partitions

Journal

ENGINEERING COMPUTATIONS
Volume 38, Issue 1, Pages 1-18

Publisher

EMERALD GROUP PUBLISHING LTD
DOI: 10.1108/EC-02-2020-0073

Keywords

Singular ordinary differential equations; Modified Adomian decomposition method; Adomian polynomials; Convergence analysis; Error estimation

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The proposed method removes the singular behavior of the problems and provides high precision numerical solution in a large effective region of convergence compared to other existing methods, as shown in the tested examples. The method does not require linearization or perturbation to obtain an analytical and numerical solution of singular differential equations, making the obtained results more physically realistic.
Purpose The purpose of this paper is to obtain the highly accurate numerical solution of Lane-Emden-type equations using modified Adomian decomposition method (MADM) for unequal step-size partitions. Design/methodology/approach First, the authors describe the standard Adomian decomposition scheme and the Adomian polynomials for solving nonlinear differential equations. After that, for the fast calculation of the Adomian polynomials, an algorithm is presented based on Duan's corollary and Rach's rule. Then, MADM is discussed for the unequal step-size partitions of the domain, to obtain the numerical solution of Lane-Emden-type equations. Moreover, convergence analysis and an error bound for the approximate solution are discussed. Findings The proposed method removes the singular behaviour of the problems and provides the high precision numerical solution in the large effective region of convergence in comparison to the other existing methods, as shown in the tested examples. Originality/value Unlike the other methods, the proposed method does not require linearization or perturbation to obtain an analytical and numerical solution of singular differential equations, and the obtained results are more physically realistic.

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