Study of mixed convection in a caterpillar wavy lid-driven triangular cavity filled with nanofluid using artificial neural network

Abstract

The present numerical study is carried out for mixed convection in a nanofluid-filled lid-driven triangular cavity. The base wall of the cavity is in a caterpillar shape, which is assumed as a hot wall while the side and inclined walls are considered as cold walls. The finite volume method along with the SIMPLE algorithm is used to discretize the governing equations. The study is evaluated for constrained parameters, such as volume fraction of the nanoparticles, sliding direction of the side wall, Richardson number, and Grashof number. Fluid flow and heat transfer are presented in terms of streamlines and isotherms and rate of enhancement has been shown by local and average Nusselt number. It is observed from the study that the heat transfer rate is enhanced for each volume fraction of nanoparticles, for both directions of sliding wall, Richardson number, and Grashof number. The obtained numerical results are validated with the predicted results of artificial neural network (ANN). Good agreement is reported between the numerical results and the predicted results.