Application of fractional derivatives in a Darcy medium natural convection flow of MHD nanofluid
Nanofluid thermophysical characteristics are critical for predicting heat transfer behavior. This attempt provides a computational assessment of boundary layer flow and heat transfer behavior of fractional Maxwell viscoelastic nanofluid and their hybrids over a permeable vertical surface. The effect...
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| Published in: | Ain Shams Engineering Journal Vol. 14; no. 9; p. 102093 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier B.V
01.09.2023
Elsevier |
| Subjects: | |
| ISSN: | 2090-4479 |
| Online Access: | Get full text |
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| Summary: | Nanofluid thermophysical characteristics are critical for predicting heat transfer behavior. This attempt provides a computational assessment of boundary layer flow and heat transfer behavior of fractional Maxwell viscoelastic nanofluid and their hybrids over a permeable vertical surface. The effects of Lorents and buoyancy forces are also considered in the flow region. The flow problem is modeled with novel distributed order time fractional derivatives to achieve control of the flow and heat transfer. Mid-point quadrature approach is used to process the distributed order integrals, whereas nonlinear coupled time fractional derivatives are discretized through the finite difference method along withL1- algorithm. The results shows that heat transfer rate enhanced 56.51% by enhancing the thermal Grashof number. Further, increase in nanoparticles volume fraction causes enhancement in thermal conductivity. More effects of the flow characteristic on velocity and temperature fields are shown graphically and analyzed in detail. The involvement of novel distributed fractional order derivatives, and nanoparticles enhanced the importance of the simulated results, which can be helpful to effectively control related thermal engineering issues, like temperature management in internal combustion engines, cooling devices, and heat exchangers. |
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| ISSN: | 2090-4479 |
| DOI: | 10.1016/j.asej.2022.102093 |