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Laplace residual power series method for the numerical solution of time-fractional Newell–Whitehead–Segel model.

Authors :
Luo, Xiankang
Nadeem, Muhammad
Source :
International Journal of Numerical Methods for Heat & Fluid Flow. 2023, Vol. 33 Issue 7, p2377-2391. 15p.
Publication Year :
2023

Abstract

Purpose: This study aims to investigate the approximate solution of the time fractional time-fractional Newell–Whitehead–Segel (TFNWS) model that reflects the appearance of the stripe patterns in two-dimensional systems. The significant results of plot distribution show that the proposed approach is highly authentic and reliable for the fractional-order models. Design/methodology/approach: The Laplace transform residual power series method (ℒT-RPSM) is the combination of Laplace transform (ℒT) and residual power series method (RPSM). The ℒT is examined to minimize the order of fractional order, whereas the RPSM handles the series solution in the form of convergence. The graphical results of the fractional models are represented through the fractional order α. Findings: The derived results are obtained in a successive series and yield the results toward the exact solution. These successive series confirm the consistency and accuracy of ℒT-RPSM. This study also compares the exact solutions with the graphical solutions to show the performance and authenticity of the visual solutions. The proposed scheme does not require the restriction of variables and produces the numerical results in terms of a series. This strategy is capable to handle the nonlinear terms very easily for the TFNWS model. Originality/value: This paper presents the original work. This study reveals that ℒT can perform the solution of fractional-order models without any restriction of variables. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09615539
Volume :
33
Issue :
7
Database :
Academic Search Index
Journal :
International Journal of Numerical Methods for Heat & Fluid Flow
Publication Type :
Periodical
Accession number :
163759168
Full Text :
https://doi.org/10.1108/HFF-01-2023-0001