Falkner–Skan Flow with Stream-Wise Pressure Gradient and Transfer of Mass over a Dynamic Wall

In this work, an important model in fluid dynamics is analyzed by a new hybrid neurocomputing algorithm. We have considered the Falkner–Skan (FS) with the stream-wise pressure gradient transfer of mass over a dynamic wall. To analyze the boundary flow of the FS model, we have utilized the global sea...

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Autores principales:	Muhammad Fawad Khan, Muhammad Sulaiman, Carlos Andrés Tavera Romero, Ali Alkhathlan
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	fluid dynamics numerical methods computational science computational fluid dynamics differential equations Falkner–Skan system Science Q Astrophysics QB460-466 Physics QC1-999
Acceso en línea:	https://doaj.org/article/c74f938f10f748f484d02cc6873d6803
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id	oai:doaj.org-article:c74f938f10f748f484d02cc6873d6803
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spelling	oai:doaj.org-article:c74f938f10f748f484d02cc6873d68032021-11-25T17:29:44ZFalkner–Skan Flow with Stream-Wise Pressure Gradient and Transfer of Mass over a Dynamic Wall10.3390/e231114481099-4300https://doaj.org/article/c74f938f10f748f484d02cc6873d68032021-10-01T00:00:00Zhttps://www.mdpi.com/1099-4300/23/11/1448https://doaj.org/toc/1099-4300In this work, an important model in fluid dynamics is analyzed by a new hybrid neurocomputing algorithm. We have considered the Falkner–Skan (FS) with the stream-wise pressure gradient transfer of mass over a dynamic wall. To analyze the boundary flow of the FS model, we have utilized the global search characteristic of a recently developed heuristic, the Sine Cosine Algorithm (SCA), and the local search characteristic of Sequential Quadratic Programming (SQP). Artificial neural network (ANN) architecture is utilized to construct a series solution of the mathematical model. We have called our technique the ANN-SCA-SQP algorithm. The dynamic of the FS system is observed by varying stream-wise pressure gradient mass transfer and dynamic wall. To validate the effectiveness of ANN-SCA-SQP algorithm, our solutions are compared with state-of-the-art reference solutions. We have repeated a hundred experiments to establish the robustness of our approach. Our experimental outcome validates the superiority of the ANN-SCA-SQP algorithm.Muhammad Fawad KhanMuhammad SulaimanCarlos Andrés Tavera RomeroAli AlkhathlanMDPI AGarticlefluid dynamicsnumerical methodscomputational sciencecomputational fluid dynamicsdifferential equationsFalkner–Skan systemScienceQAstrophysicsQB460-466PhysicsQC1-999ENEntropy, Vol 23, Iss 1448, p 1448 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	fluid dynamics numerical methods computational science computational fluid dynamics differential equations Falkner–Skan system Science Q Astrophysics QB460-466 Physics QC1-999
spellingShingle	fluid dynamics numerical methods computational science computational fluid dynamics differential equations Falkner–Skan system Science Q Astrophysics QB460-466 Physics QC1-999 Muhammad Fawad Khan Muhammad Sulaiman Carlos Andrés Tavera Romero Ali Alkhathlan Falkner–Skan Flow with Stream-Wise Pressure Gradient and Transfer of Mass over a Dynamic Wall
description	In this work, an important model in fluid dynamics is analyzed by a new hybrid neurocomputing algorithm. We have considered the Falkner–Skan (FS) with the stream-wise pressure gradient transfer of mass over a dynamic wall. To analyze the boundary flow of the FS model, we have utilized the global search characteristic of a recently developed heuristic, the Sine Cosine Algorithm (SCA), and the local search characteristic of Sequential Quadratic Programming (SQP). Artificial neural network (ANN) architecture is utilized to construct a series solution of the mathematical model. We have called our technique the ANN-SCA-SQP algorithm. The dynamic of the FS system is observed by varying stream-wise pressure gradient mass transfer and dynamic wall. To validate the effectiveness of ANN-SCA-SQP algorithm, our solutions are compared with state-of-the-art reference solutions. We have repeated a hundred experiments to establish the robustness of our approach. Our experimental outcome validates the superiority of the ANN-SCA-SQP algorithm.
format	article
author	Muhammad Fawad Khan Muhammad Sulaiman Carlos Andrés Tavera Romero Ali Alkhathlan
author_facet	Muhammad Fawad Khan Muhammad Sulaiman Carlos Andrés Tavera Romero Ali Alkhathlan
author_sort	Muhammad Fawad Khan
title	Falkner–Skan Flow with Stream-Wise Pressure Gradient and Transfer of Mass over a Dynamic Wall
title_short	Falkner–Skan Flow with Stream-Wise Pressure Gradient and Transfer of Mass over a Dynamic Wall
title_full	Falkner–Skan Flow with Stream-Wise Pressure Gradient and Transfer of Mass over a Dynamic Wall
title_fullStr	Falkner–Skan Flow with Stream-Wise Pressure Gradient and Transfer of Mass over a Dynamic Wall
title_full_unstemmed	Falkner–Skan Flow with Stream-Wise Pressure Gradient and Transfer of Mass over a Dynamic Wall
title_sort	falkner–skan flow with stream-wise pressure gradient and transfer of mass over a dynamic wall
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/c74f938f10f748f484d02cc6873d6803
work_keys_str_mv	AT muhammadfawadkhan falknerskanflowwithstreamwisepressuregradientandtransferofmassoveradynamicwall AT muhammadsulaiman falknerskanflowwithstreamwisepressuregradientandtransferofmassoveradynamicwall AT carlosandrestaveraromero falknerskanflowwithstreamwisepressuregradientandtransferofmassoveradynamicwall AT alialkhathlan falknerskanflowwithstreamwisepressuregradientandtransferofmassoveradynamicwall
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Falkner–Skan Flow with Stream-Wise Pressure Gradient and Transfer of Mass over a Dynamic Wall

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