JOURNAL ARTICLE

Prabhakar-fractional simulations for the exact solution of Casson-type fluid with experiencing the effects of magneto-hydrodynamics and sinusoidal thermal conditions.

  • Published In: International Journal of Modern Physics B: Condensed Matter Physics; Statistical Physics; Applied Physics, 2023, v. 37, n. 1. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Raza, Ali; Khan, Umair; Almusawa, M. Y; Hamali, Waleed; Galal, Ahmed M. 3 of 3

Abstract

This analysis inspects an unsteady and incompressible Casson-type fluid moving on a poured inclined oscillating plane with a ramped thermal profile. The physical effects of flow parameters cannot be investigated and studied using a memory effect, just like with regular PDEs. In this study, we have confabulated the solution of magnetised Casson-type fluid with the help of the best and most modified fractional definition, known as the Prabhakar-like thermal fractional derivative. An integral transforms scheme, namely Laplace transformation (LT) solves the dimensionless governed equations. The physical impacts of significant and fractional constraints are examined graphically and mathematically. As a result, we have confabulated that both thermal and momentum dynamics of flowing Casson fluid slow down with the increment in fractional constraint. Additionally, because of the thickness of the boundary layer, the Casson fluid parameter emphasises the dual character of flowing fluid dynamics. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Modern Physics B: Condensed Matter Physics; Statistical Physics; Applied Physics. 2023/01, Vol. 37, Issue 1, p1
  • Document Type:Article
  • Subject Area:Science
  • Publication Date:2023
  • ISSN:0217-9792
  • DOI:10.1142/S0217979223500108
  • Accession Number:160650123
  • Copyright Statement:Copyright of International Journal of Modern Physics B: Condensed Matter Physics; Statistical Physics; Applied Physics is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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