Application of FCM-ANFIS approach to model heat transfer and pressure drop of Titania-water nanofluids in the turbulent flow regime

Abstract

The revolution of the industrial and manufacturing sector is witnessing a rapid tendency toward miniaturization. Production of high capacity, compact size, portable and lightweight devices such as microelectronics devices is posing a critical challenge of thermal management. In order to maintain the compactness of these devices, the conventional method of thermal management is often ruled out. Recently, research on the option of using nanofluids as alternative thermal fluids has received significant attention as a possible solution to thermal management problems associated with microelectronics devices. In this paper, convection heat transfer and pressure drop of Titania-water nanofluids were modeled by using the application of Fuzzy C-means Adaptive Neuro-Fuzzy Inference System (FCM-ANFIS) approach. Two models were developed for prediction of the Nusselt number and pressure drop of Titania-water nanofluids considering the effective parameters of Reynolds number, Prandtl numbers, nanofluid volume concentration and average nanoparticle diameter. The validity of the proposed models was compared with experimental data available in the literature.