Statistical Analysis of the Mathematical Model of Entropy Generation of Magnetized Nanofluid

This investigation introduces a mathematical model of entropy generation for Magnetohydrodynamic (MHD) peristaltic wave of nanofluid. The governing equations have been created by the supposition of low Reynolds number and long wavelength estimation. The scientific arrangement has been procured with...

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Main Authors: Munawwar Ali Abbas, Ibrahim Hussain
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Inventions
Subjects:
Online Access:https://www.mdpi.com/2411-5134/4/2/32
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spelling doaj-1c8d4a5cf4cf443dbec998152c3c46902020-11-25T00:25:58ZengMDPI AGInventions2411-51342019-06-01423210.3390/inventions4020032inventions4020032Statistical Analysis of the Mathematical Model of Entropy Generation of Magnetized NanofluidMunawwar Ali Abbas0Ibrahim Hussain1Department of Mathematics, University of Baltistan, Skardu, Gilgit-Baltistan 16100, PakistanDepartment of Business Management and Commerce, University of Baltistan, Skardu, Gilgit-Baltistan 16100, PakistanThis investigation introduces a mathematical model of entropy generation for Magnetohydrodynamic (MHD) peristaltic wave of nanofluid. The governing equations have been created by the supposition of low Reynolds number and long wavelength estimation. The scientific arrangement has been procured with the help of perturbation technique. The concentration profile, temperature profile, pressure distribution and friction forces are shown graphically for some important parameters. Further, the eventual outcomes of connection between the entropy generation and some various parameters have been plotted by means of correlation and regression. It is fundamental to find the affectability of each parameter on entropy generation.https://www.mdpi.com/2411-5134/4/2/32regressioncorrelationmagnetohydrodynamicsnanofluidentropy generation
collection DOAJ
language English
format Article
sources DOAJ
author Munawwar Ali Abbas
Ibrahim Hussain
spellingShingle Munawwar Ali Abbas
Ibrahim Hussain
Statistical Analysis of the Mathematical Model of Entropy Generation of Magnetized Nanofluid
Inventions
regression
correlation
magnetohydrodynamics
nanofluid
entropy generation
author_facet Munawwar Ali Abbas
Ibrahim Hussain
author_sort Munawwar Ali Abbas
title Statistical Analysis of the Mathematical Model of Entropy Generation of Magnetized Nanofluid
title_short Statistical Analysis of the Mathematical Model of Entropy Generation of Magnetized Nanofluid
title_full Statistical Analysis of the Mathematical Model of Entropy Generation of Magnetized Nanofluid
title_fullStr Statistical Analysis of the Mathematical Model of Entropy Generation of Magnetized Nanofluid
title_full_unstemmed Statistical Analysis of the Mathematical Model of Entropy Generation of Magnetized Nanofluid
title_sort statistical analysis of the mathematical model of entropy generation of magnetized nanofluid
publisher MDPI AG
series Inventions
issn 2411-5134
publishDate 2019-06-01
description This investigation introduces a mathematical model of entropy generation for Magnetohydrodynamic (MHD) peristaltic wave of nanofluid. The governing equations have been created by the supposition of low Reynolds number and long wavelength estimation. The scientific arrangement has been procured with the help of perturbation technique. The concentration profile, temperature profile, pressure distribution and friction forces are shown graphically for some important parameters. Further, the eventual outcomes of connection between the entropy generation and some various parameters have been plotted by means of correlation and regression. It is fundamental to find the affectability of each parameter on entropy generation.
topic regression
correlation
magnetohydrodynamics
nanofluid
entropy generation
url https://www.mdpi.com/2411-5134/4/2/32
work_keys_str_mv AT munawwaraliabbas statisticalanalysisofthemathematicalmodelofentropygenerationofmagnetizednanofluid
AT ibrahimhussain statisticalanalysisofthemathematicalmodelofentropygenerationofmagnetizednanofluid
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