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Dual dynamical jumps on Lie group analysis of hydro-magnetic flow in a suspension of different shapes of water-based hybrid solid particles with Fourier flux

Authors :
M. Dinesh Kumar
C.S.K. Raju
Mansoor Alshehri
Shalan Alkarni
Nehad Ali Shah
Mohamed R. Ali
R. Sadat
Source :
Arabian Journal of Chemistry, Vol 16, Iss 8, Pp 104889- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

In recent times, the mixture of liquids has been referred to as “hybrid modelling.” Ternary hybrid models are advantageous for different systems such as production industries, aerosol particle processing, and experimental instrument design, to name a few. The regulating partial differential equation (PDE) for nonlinear systems is changed into a system of associate nonlinear (ODE) In this study, ordinary differential equations report utilizing new similarity scaling symmetry transformations produced via Lie group transformations analysis. Using a BVP4C with a shooting method approach, the resulting system is numerically resolved (MATLAB). For Cases: 1 CNT, Graphene, Aluminium oxide, Cases: 2 Cooper oxide, Magnesium oxide, and Zirconium oxide with different nanosized particle morphologies including platelet, cylindrical, and spherical, the rate of heat transmission and the magnetohydrodynamic flow of incompressible fluid friction were studied. It is observed that Nusselt number transfer is having more transmission rate in case-1 Al2o3+GNT+CNTwith water than in case-2 Mgo+Zro2+Cuowithwater, This shows that, due to the Case-1 hybrid nanofluid mixture's improved heat transmission rate, it can be used for cooling as well as other applications where a faster heat transfer rate is necessary, including rapid charging batteries. Where there is a lower heat transfer rate than in instance 1, the case-2 hybrid nanofluid mixture can be used. Even in cancer treatment also nanoparticles will be useful to kill the cancer cell by injecting the nanoparticles into the human body. In order to predict the outcomes of a response variable, a statistical technique known as multilinear regression analysis (MLR) makes use of a variety of explanatory variables.

Details

Language :
English
ISSN :
18785352
Volume :
16
Issue :
8
Database :
Directory of Open Access Journals
Journal :
Arabian Journal of Chemistry
Publication Type :
Academic Journal
Accession number :
edsdoj.49eed6dc1a094274ad4c0237930adb57
Document Type :
article
Full Text :
https://doi.org/10.1016/j.arabjc.2023.104889