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Laplace Adomian Decomposition Method for Multi Dimensional Time Fractional Model of Navier-Stokes Equation

Laplace Adomian decomposition method for multi dimensional time fractional model of Navier-Stokes equation
Authors: Shahid Mahmood; Rasool Shah; Hassan Khan 0003; Muhammad Arif 0001;

Laplace Adomian Decomposition Method for Multi Dimensional Time Fractional Model of Navier-Stokes Equation

Abstract

In this research paper, a hybrid method called Laplace Adomian Decomposition Method (LADM) is used for the analytical solution of the system of time fractional Navier-Stokes equation. The solution of this system can be obtained with the help of Maple software, which provide LADM algorithm for the given problem. Moreover, the results of the proposed method are compared with the exact solution of the problems, which has confirmed, that as the terms of the series increases the approximate solutions are convergent to the exact solution of each problem. The accuracy of the method is examined with help of some examples. The LADM, results have shown that, the proposed method has higher rate of convergence as compare to ADM and HPM.

Keywords

Multigrid methods; domain decomposition for initial value and initial-boundary value problems involving PDEs, Caputo operator, Caputo Operator, Laplace Adomian Decomposition Method (LADM), Navier-Stokes equations, Laplace Adomian decomposition method (LADM), Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems, Fractional partial differential equations, Navier-Stokes equation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
61
Top 1%
Top 10%
Top 1%
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