Thermal analysis and optimization approach for ternary nanofluid flow in a novel porous cavity by considering nanoparticle shape factor.

This study focuses on the numerical investigation and optimization of the heat-fluid transfer process within a novel cavity containing a ternary nanofluid (Cu-MgO-ZnO/water) influenced by a magnetic field. The research is conducted within a circular cavity featuring a cold wall and a complex internal heat source. The governing equations, converted into dimensionless form, are solved using a computational code based on the finite volume approach. The analysis encompasses the effects of a wide range of physical parameters, including the Rayleigh number (Ra), Hartmann number (Ha), magnetic field angle (α), radiation (Ra), nanoparticle shape factor (Sf), and porosity (ԑ). The results revealed that increasing the nanoparticle shape factor leads to a significant 61 % enhancement in the outer Nusselt number. This finding underscores the substantial influence of the nanoparticle shape factor (Sf) on heat transfer compared to other controlled variables. Furthermore, the response surface method is employed to determine the optimal conditions that yield the highest Nusselt number, resulting in optimal values for Ra, Ha, ԑ, Rd, α, and Sf of 2876, 44.26, 0.75, 0.073, 54.21, and 16.15, respectively. Consequently, the highest average Nusselt number attained is 20.01. As a result, this optimization approach establishes valuable correlations among various control parameters to enhance thermal energy, offering valuable insights for designers in the development of thermal devices.

Optimization of wavy trapezoidal porous cavity containing mixture hybrid nanofluid (water/ethylene glycol Go-Al2O3) by response surface method.

Increasing thermal performance and preventing heat loss are very important in energy conversion systems, especially for new and complex products that exacerbate this need. Therefore, to solve this challenge, a trapezoidal cavity with a wavy top wall containing water/ethylene glycol GO-Al2O3 nanofluid is simulated using Galerkin finite element method. The effects of physical parameters affecting thermal performance and fluid flow, including porosity (ℇ), thermal radiation (Rd), magnetic field angle (α), Rayleigh number (Ra) and Hartmann number (Ha), are investigated in the determined ratios. The results of applied boundary conditions showed that the optimal values for Ra, Ha, ℇ, Rd and α are 1214.46, 2.86, 0.63, 0.24 and 59.35, respectively. Considering that changes in radiation have little effect on streamlines and isothermal lines. Optimization by RSM and Taguchi integration resulted in optimal Nu detection. It provided a correlation for the average Nu based on the investigated determinants due to the conflicting influence of the study factors, which finally calculated the highest average Nusselt number of 3.07. Therefore, the ideal design, which is the primary goal of this research, increases the thermal performance.