Numerical study of mixed convection flow of two-phase nanofluid in a two-dimensional cavity with the presence of a magnetic field by changing the height of obstacles with artificial intelligence: Investigation of entropy production changes and Bejan number

Abstract

Investigating the entropy production (ETP) and inertial number can help to improve the efficiency of heat transfer devices, for this reason, in this paper, the study of the ETP of nanofluid (NNF) flow in a two-dimensional cavity was studied. The NNF flow is affected by the horizontal magnetic field (MGD). Also, the Bejan number (Be) of the flow was also studied for different states of the mentioned parameters. The cavity had two hot and cold walls and two insulated walls, the cold wall above which was also movable. On the lower warm wall, there are 3 blades in the shape of a triangle, the height of each of which was changed individually from 0.1 to 0.7 and its effect on entropy changes and Be was investigated. Finally, using artificial intelligence, the best conditions for having the lowest Be and ETP for the range of variables were checked. The NNF was simulated in two phases and the simulation was done in FORTRAN software using SIMPLE algorithm. The results of this study showed that the largest amount of Be was present in the longest length of the triangular obstacles, but the lowest value of the Be was in the low values of the height of theobstacles and did not necessarily occur in the lowest values of the heights. The highest amount of entropy was produced at the lowest height of the left obstacle and the highest height of the middle obstacle. Also, the amount of ETP at higher altitudes on the right side of the obstacle was greater than its lower altitudes.