Numerical Analysis of Electrohydrodynamic Flow in a Circular Cylindrical Conduit by Using Neuro Evolutionary Technique

This paper analyzes the mathematical model of electrohydrodynamic (EHD) fluid flow in a circular cylindrical conduit with an ion drag configuration. The phenomenon was modelled as a nonlinear differential equation. Furthermore, an application of artificial neural networks (ANNs) with a generalized n...

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Autores principales:	Naveed Ahmad Khan, Muhammad Sulaiman, Carlos Andrés Tavera Romero, Fawaz Khaled Alarfaj
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	electrohydrodynamic flow circular cylindrical conduit Hartmann electric number artificial neural networks generalized normal distribution optimization neuro soft computing Technology T
Acceso en línea:	https://doaj.org/article/e62336a5280347b3bbebe7921e3556f7
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spelling	oai:doaj.org-article:e62336a5280347b3bbebe7921e3556f72021-11-25T17:28:39ZNumerical Analysis of Electrohydrodynamic Flow in a Circular Cylindrical Conduit by Using Neuro Evolutionary Technique10.3390/en142277741996-1073https://doaj.org/article/e62336a5280347b3bbebe7921e3556f72021-11-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/22/7774https://doaj.org/toc/1996-1073This paper analyzes the mathematical model of electrohydrodynamic (EHD) fluid flow in a circular cylindrical conduit with an ion drag configuration. The phenomenon was modelled as a nonlinear differential equation. Furthermore, an application of artificial neural networks (ANNs) with a generalized normal distribution optimization algorithm (GNDO) and sequential quadratic programming (SQP) were utilized to suggest approximate solutions for the velocity, displacements, and acceleration profiles of the fluid by varying the Hartmann electric number (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><msup><mi>a</mi><mn>2</mn></msup></mrow></semantics></math></inline-formula>) and the strength of nonlinearity (α). ANNs were used to model the fitness function for the governing equation in terms of mean square error (MSE), which was further optimized initially by GNDO to exploit the global search. Then SQP was implemented to complement its local convergence. Numerical solutions obtained by the design scheme were compared with RK-4, the least square method (LSM), and the orthonormal Bernstein collocation method (OBCM). Stability, convergence, and robustness of the proposed algorithm were endorsed by the statistics and analysis on results of absolute errors, mean absolute deviation (MAD), Theil’s inequality coefficient (TIC), and error in Nash Sutcliffe efficiency (ENSE).Naveed Ahmad KhanMuhammad SulaimanCarlos Andrés Tavera RomeroFawaz Khaled AlarfajMDPI AGarticleelectrohydrodynamic flowcircular cylindrical conduitHartmann electric numberartificial neural networksgeneralized normal distribution optimizationneuro soft computingTechnologyTENEnergies, Vol 14, Iss 7774, p 7774 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	electrohydrodynamic flow circular cylindrical conduit Hartmann electric number artificial neural networks generalized normal distribution optimization neuro soft computing Technology T
spellingShingle	electrohydrodynamic flow circular cylindrical conduit Hartmann electric number artificial neural networks generalized normal distribution optimization neuro soft computing Technology T Naveed Ahmad Khan Muhammad Sulaiman Carlos Andrés Tavera Romero Fawaz Khaled Alarfaj Numerical Analysis of Electrohydrodynamic Flow in a Circular Cylindrical Conduit by Using Neuro Evolutionary Technique
description	This paper analyzes the mathematical model of electrohydrodynamic (EHD) fluid flow in a circular cylindrical conduit with an ion drag configuration. The phenomenon was modelled as a nonlinear differential equation. Furthermore, an application of artificial neural networks (ANNs) with a generalized normal distribution optimization algorithm (GNDO) and sequential quadratic programming (SQP) were utilized to suggest approximate solutions for the velocity, displacements, and acceleration profiles of the fluid by varying the Hartmann electric number (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>H</mi><msup><mi>a</mi><mn>2</mn></msup></mrow></semantics></math></inline-formula>) and the strength of nonlinearity (α). ANNs were used to model the fitness function for the governing equation in terms of mean square error (MSE), which was further optimized initially by GNDO to exploit the global search. Then SQP was implemented to complement its local convergence. Numerical solutions obtained by the design scheme were compared with RK-4, the least square method (LSM), and the orthonormal Bernstein collocation method (OBCM). Stability, convergence, and robustness of the proposed algorithm were endorsed by the statistics and analysis on results of absolute errors, mean absolute deviation (MAD), Theil’s inequality coefficient (TIC), and error in Nash Sutcliffe efficiency (ENSE).
format	article
author	Naveed Ahmad Khan Muhammad Sulaiman Carlos Andrés Tavera Romero Fawaz Khaled Alarfaj
author_facet	Naveed Ahmad Khan Muhammad Sulaiman Carlos Andrés Tavera Romero Fawaz Khaled Alarfaj
author_sort	Naveed Ahmad Khan
title	Numerical Analysis of Electrohydrodynamic Flow in a Circular Cylindrical Conduit by Using Neuro Evolutionary Technique
title_short	Numerical Analysis of Electrohydrodynamic Flow in a Circular Cylindrical Conduit by Using Neuro Evolutionary Technique
title_full	Numerical Analysis of Electrohydrodynamic Flow in a Circular Cylindrical Conduit by Using Neuro Evolutionary Technique
title_fullStr	Numerical Analysis of Electrohydrodynamic Flow in a Circular Cylindrical Conduit by Using Neuro Evolutionary Technique
title_full_unstemmed	Numerical Analysis of Electrohydrodynamic Flow in a Circular Cylindrical Conduit by Using Neuro Evolutionary Technique
title_sort	numerical analysis of electrohydrodynamic flow in a circular cylindrical conduit by using neuro evolutionary technique
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/e62336a5280347b3bbebe7921e3556f7
work_keys_str_mv	AT naveedahmadkhan numericalanalysisofelectrohydrodynamicflowinacircularcylindricalconduitbyusingneuroevolutionarytechnique AT muhammadsulaiman numericalanalysisofelectrohydrodynamicflowinacircularcylindricalconduitbyusingneuroevolutionarytechnique AT carlosandrestaveraromero numericalanalysisofelectrohydrodynamicflowinacircularcylindricalconduitbyusingneuroevolutionarytechnique AT fawazkhaledalarfaj numericalanalysisofelectrohydrodynamicflowinacircularcylindricalconduitbyusingneuroevolutionarytechnique
_version_	1718412318639915008

Numerical Analysis of Electrohydrodynamic Flow in a Circular Cylindrical Conduit by Using Neuro Evolutionary Technique

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