Adaptive network-based fuzzy inference system analysis of mixed convection in a two-sided lid-driven cavity filled with a nanofluid

摘要

A numerical study of laminar mixed convection in a two-sided lid-driven cavity filled with a water-Al_2O_3 nanofluid is presented. The top and bottom walls of the cavity are kept at different temperatures and can slide in the same or opposite direction. The vertical walls are thermally insulated. An Adaptive Network-based Fuzzy Inference System (ANFIS) approach is developed, trained and validated using the results of a Computational Fluid Dynamics (CFD) analysis. The results show that ANFIS can successfully be used to predict the fluid velocity and temperature as well as the heat transfer rate of the cavity, with reduced computation time and without compromising the accuracy.