Neural networking-based approach for examining heat transfer and bioconvection in Non-Newtonian fluid with chemical reaction over a stretching sheet
This research investigates the impact of bioconvection and magnetohydrodynamics on Casson-Williamson fluid flow over a stretching surface while considering the effect of heat sources, thermal radiation, and chemical reactions. They are significant components in industrial processes and biomedical sy...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-05-01
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| Series: | Case Studies in Thermal Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X25003077 |
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| author | Sohaib Abdal Talal Taha Liaqat Ali Rana Muhammad Zulqarnain Se-Jin Yook |
| author_facet | Sohaib Abdal Talal Taha Liaqat Ali Rana Muhammad Zulqarnain Se-Jin Yook |
| author_sort | Sohaib Abdal |
| collection | DOAJ |
| description | This research investigates the impact of bioconvection and magnetohydrodynamics on Casson-Williamson fluid flow over a stretching surface while considering the effect of heat sources, thermal radiation, and chemical reactions. They are significant components in industrial processes and biomedical systems, such as targeted drug release and cancer therapies. The nonlinear governing partial differential equations (PDEs) are converted into ordinary differential equations (ODEs) employing similarity transformations and are numerically solved through a fourth-order procedure. Afterward, an Artificial Neural Network (ANN) with Levenberg-Marquardt training evaluates the flow pattern. The dataset is split into 70 % train, 15 % test, and 15 % validate to maximize model precision and generalizability. Mean Squared Error (MSE) is utilized to measure precision, whereas regression analysis (R ≈ 1) verifies strong prediction accuracy. Findings indicate that the momentum boundary layer reduces with increasing magnetic field and buoyancy ratio, whereas the Nusselt number increases with increased radiation parameters but decreases for growing heat source, Brownian motion, thermophoresis, and Eckert numbers. Skin friction also augments with greater magnetic, porosity, Rayleigh, and buoyancy parameters. These results contribute to the optimization of fluid flow in nanobiotechnology, chemical engineering, and heat transfer processes, underlining the potential of bioconvection and AI-based modeling for future development. |
| format | Article |
| id | doaj-art-56170d9d8dfd4375b3bf81b77919efc7 |
| institution | DOAJ |
| issn | 2214-157X |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Case Studies in Thermal Engineering |
| spelling | doaj-art-56170d9d8dfd4375b3bf81b77919efc72025-08-20T03:18:20ZengElsevierCase Studies in Thermal Engineering2214-157X2025-05-016910604710.1016/j.csite.2025.106047Neural networking-based approach for examining heat transfer and bioconvection in Non-Newtonian fluid with chemical reaction over a stretching sheetSohaib Abdal0Talal Taha1Liaqat Ali2Rana Muhammad Zulqarnain3Se-Jin Yook4School of Mechanical Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul, 04763, Republic of KoreaDepartment of Mathematics and Statistics, Faculty of Sciences, International Islamic University, Islamabad, 04436, PakistanSchool of Sciences, Xi'an Technological University, Xi'an, 710021, ChinaDepartment of Mathematics, Saveetha School of Engineering, SlMATS, Chennai, IndiaSchool of Mechanical Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul, 04763, Republic of Korea; Corresponding author.This research investigates the impact of bioconvection and magnetohydrodynamics on Casson-Williamson fluid flow over a stretching surface while considering the effect of heat sources, thermal radiation, and chemical reactions. They are significant components in industrial processes and biomedical systems, such as targeted drug release and cancer therapies. The nonlinear governing partial differential equations (PDEs) are converted into ordinary differential equations (ODEs) employing similarity transformations and are numerically solved through a fourth-order procedure. Afterward, an Artificial Neural Network (ANN) with Levenberg-Marquardt training evaluates the flow pattern. The dataset is split into 70 % train, 15 % test, and 15 % validate to maximize model precision and generalizability. Mean Squared Error (MSE) is utilized to measure precision, whereas regression analysis (R ≈ 1) verifies strong prediction accuracy. Findings indicate that the momentum boundary layer reduces with increasing magnetic field and buoyancy ratio, whereas the Nusselt number increases with increased radiation parameters but decreases for growing heat source, Brownian motion, thermophoresis, and Eckert numbers. Skin friction also augments with greater magnetic, porosity, Rayleigh, and buoyancy parameters. These results contribute to the optimization of fluid flow in nanobiotechnology, chemical engineering, and heat transfer processes, underlining the potential of bioconvection and AI-based modeling for future development.http://www.sciencedirect.com/science/article/pii/S2214157X25003077BioconvectionCasson fluidWilliamson fluidMagnetohydrodynamicsArtificial neural networkingHeat source |
| spellingShingle | Sohaib Abdal Talal Taha Liaqat Ali Rana Muhammad Zulqarnain Se-Jin Yook Neural networking-based approach for examining heat transfer and bioconvection in Non-Newtonian fluid with chemical reaction over a stretching sheet Case Studies in Thermal Engineering Bioconvection Casson fluid Williamson fluid Magnetohydrodynamics Artificial neural networking Heat source |
| title | Neural networking-based approach for examining heat transfer and bioconvection in Non-Newtonian fluid with chemical reaction over a stretching sheet |
| title_full | Neural networking-based approach for examining heat transfer and bioconvection in Non-Newtonian fluid with chemical reaction over a stretching sheet |
| title_fullStr | Neural networking-based approach for examining heat transfer and bioconvection in Non-Newtonian fluid with chemical reaction over a stretching sheet |
| title_full_unstemmed | Neural networking-based approach for examining heat transfer and bioconvection in Non-Newtonian fluid with chemical reaction over a stretching sheet |
| title_short | Neural networking-based approach for examining heat transfer and bioconvection in Non-Newtonian fluid with chemical reaction over a stretching sheet |
| title_sort | neural networking based approach for examining heat transfer and bioconvection in non newtonian fluid with chemical reaction over a stretching sheet |
| topic | Bioconvection Casson fluid Williamson fluid Magnetohydrodynamics Artificial neural networking Heat source |
| url | http://www.sciencedirect.com/science/article/pii/S2214157X25003077 |
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