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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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/23/11/1448 |
| _version_ | 1827676689773101056 |
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| 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 |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T05:31:49Z |
| format | Article |
| id | doaj.art-c74f938f10f748f484d02cc6873d6803 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T05:31:49Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-c74f938f10f748f484d02cc6873d68032023-11-22T23:15:07ZengMDPI AGEntropy1099-43002021-10-012311144810.3390/e23111448Falkner–Skan Flow with Stream-Wise Pressure Gradient and Transfer of Mass over a Dynamic WallMuhammad Fawad Khan0Muhammad Sulaiman1Carlos Andrés Tavera Romero2Ali Alkhathlan3Department of Mathematics, Abdul Wali Khan University, Mardan 23200, PakistanDepartment of Mathematics, Abdul Wali Khan University, Mardan 23200, PakistanCOMBA R&D Laboratory, Faculty of Engineering, Universidad Santiago de Cali, Cali 76001, ColombiaComputer Science Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi ArabiaIn 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.https://www.mdpi.com/1099-4300/23/11/1448fluid dynamicsnumerical methodscomputational sciencecomputational fluid dynamicsdifferential equationsFalkner–Skan system |
| spellingShingle | 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 Entropy fluid dynamics numerical methods computational science computational fluid dynamics differential equations Falkner–Skan system |
| title | 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_short | 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 |
| topic | fluid dynamics numerical methods computational science computational fluid dynamics differential equations Falkner–Skan system |
| url | https://www.mdpi.com/1099-4300/23/11/1448 |
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