Artificial intelligence based evaluation of the tri-hybridized (WS₂+Fe₃O₄+CuS) flow subjected to the thermal performance in porous systems
The thermal and flow dynamics of a ternary nanofluid composed of tungsten disulfide (WS₂), magnetite (Fe₃O₄), and copper sulfide (CuS) nanoparticles suspended in thermal oil is comparatively interpreted in the present work. The system operates within a porous medium emphasizing the effects of the te...
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Elsevier
2025-06-01
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| Series: | Results in Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025007947 |
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| author | Sohail Ahmad Hessa A. Alsalmah |
| author_facet | Sohail Ahmad Hessa A. Alsalmah |
| author_sort | Sohail Ahmad |
| collection | DOAJ |
| description | The thermal and flow dynamics of a ternary nanofluid composed of tungsten disulfide (WS₂), magnetite (Fe₃O₄), and copper sulfide (CuS) nanoparticles suspended in thermal oil is comparatively interpreted in the present work. The system operates within a porous medium emphasizing the effects of the ternary nano-composition under induced magnetic field environment. The model Navier-Stokes system represents the fluid flow in porous systems under varying flow regimes incorporating both Darcy (linear flow resistance) and Forchheimer (nonlinear inertial effects) terms. Porous materials enhance heat transfer by increasing the surface area for conduction and convection. Advanced computational and neural network techniques, including a radial basis function (RBF) neural network and successive over-relaxation (SOR) methods, are employed to model and simulate the system's thermal and hydrodynamic performance. Results reveal that the ternary nano-composition WS₂+Fe₃O₄+CuS outperforms traditional binary and single-component nanofluids in terms of thermal performance within porous systems. The rate of heat transfer is noticed to be low when volume fractions of magnetite and copper sulfide particles are taken large. Normal and streamwise velocities are decreasing functions of the Forchheimer as well as porosity parameter. The nano-structured fluid flows through Darcy-Forchheimer porous media are eminent for enhancing heat transfer in applications like heat exchangers, solar collectors, geothermal systems, and enhanced oil recovery. |
| format | Article |
| id | doaj-art-cf50008b32c841d2a89b73eb2c1811d4 |
| institution | DOAJ |
| issn | 2590-1230 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-cf50008b32c841d2a89b73eb2c1811d42025-08-20T03:09:27ZengElsevierResults in Engineering2590-12302025-06-012610471710.1016/j.rineng.2025.104717Artificial intelligence based evaluation of the tri-hybridized (WS₂+Fe₃O₄+CuS) flow subjected to the thermal performance in porous systemsSohail Ahmad0Hessa A. Alsalmah1Department of Basic Sciences and Humanities, Muhammad Nawaz Sharif University of Engineering and Technology, Multan, 60000, PakistanDepartment of Physics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11623, Saudi Arabia; Corresponding author.The thermal and flow dynamics of a ternary nanofluid composed of tungsten disulfide (WS₂), magnetite (Fe₃O₄), and copper sulfide (CuS) nanoparticles suspended in thermal oil is comparatively interpreted in the present work. The system operates within a porous medium emphasizing the effects of the ternary nano-composition under induced magnetic field environment. The model Navier-Stokes system represents the fluid flow in porous systems under varying flow regimes incorporating both Darcy (linear flow resistance) and Forchheimer (nonlinear inertial effects) terms. Porous materials enhance heat transfer by increasing the surface area for conduction and convection. Advanced computational and neural network techniques, including a radial basis function (RBF) neural network and successive over-relaxation (SOR) methods, are employed to model and simulate the system's thermal and hydrodynamic performance. Results reveal that the ternary nano-composition WS₂+Fe₃O₄+CuS outperforms traditional binary and single-component nanofluids in terms of thermal performance within porous systems. The rate of heat transfer is noticed to be low when volume fractions of magnetite and copper sulfide particles are taken large. Normal and streamwise velocities are decreasing functions of the Forchheimer as well as porosity parameter. The nano-structured fluid flows through Darcy-Forchheimer porous media are eminent for enhancing heat transfer in applications like heat exchangers, solar collectors, geothermal systems, and enhanced oil recovery.http://www.sciencedirect.com/science/article/pii/S2590123025007947RBF Neural NetworkTungsten DisulfideSOR MethodDarcy Forchheimer MediumInduced Magnetic Field |
| spellingShingle | Sohail Ahmad Hessa A. Alsalmah Artificial intelligence based evaluation of the tri-hybridized (WS₂+Fe₃O₄+CuS) flow subjected to the thermal performance in porous systems Results in Engineering RBF Neural Network Tungsten Disulfide SOR Method Darcy Forchheimer Medium Induced Magnetic Field |
| title | Artificial intelligence based evaluation of the tri-hybridized (WS₂+Fe₃O₄+CuS) flow subjected to the thermal performance in porous systems |
| title_full | Artificial intelligence based evaluation of the tri-hybridized (WS₂+Fe₃O₄+CuS) flow subjected to the thermal performance in porous systems |
| title_fullStr | Artificial intelligence based evaluation of the tri-hybridized (WS₂+Fe₃O₄+CuS) flow subjected to the thermal performance in porous systems |
| title_full_unstemmed | Artificial intelligence based evaluation of the tri-hybridized (WS₂+Fe₃O₄+CuS) flow subjected to the thermal performance in porous systems |
| title_short | Artificial intelligence based evaluation of the tri-hybridized (WS₂+Fe₃O₄+CuS) flow subjected to the thermal performance in porous systems |
| title_sort | artificial intelligence based evaluation of the tri hybridized ws₂ fe₃o₄ cus flow subjected to the thermal performance in porous systems |
| topic | RBF Neural Network Tungsten Disulfide SOR Method Darcy Forchheimer Medium Induced Magnetic Field |
| url | http://www.sciencedirect.com/science/article/pii/S2590123025007947 |
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