Eur. Phys. J. Plus (2020) 135: 796
https://doi.org/10.1140/epjp/s13360-020-00809-7

Regular Article

Experimental and modeling study of heat transfer enhancement of TiO₂/SiO₂ hybrid nanofluids on modified surfaces in pool boiling process

Department of Chemical Engineering, Babol Noshirvani University of Technology, Shariati Ave, 47148-71167, Babol, Iran

^b shabanian@nit.ac.ir, r_shabanian@yahoo.com

Received: 13 June 2020
Accepted: 25 September 2020
Published online: 8 October 2020

Abstract

The thermal conductivity of working fluids has been dramatically improved by the implementation of nanoparticles. In this experimental study, the influence of TiO₂ and SiO₂ nanoparticles on the pool boiling heat transfer coefficient (HTC) of the nanofluid is thoroughly investigated. The results indicate that HTC of hybrid nanofluid of TiO₂–SiO₂–water is considerably higher than that of single nanofluids TiO₂–water and SiO₂–water systems. The effects of the nanofluid concentration and surface modification on HTC were investigated for two main working fluids of water and a mixture of ethylene glycol (EG)-water. Experimental evidence shows that the highest values of heat flux and HTC are obtained at 0.05% concentration of the hybrid nanofluid. Furthermore, the results show that changing the plain surface to the surface with circular channels and intersection lines (CC-IL) leads to considerable enhancement in HTC for all nanofluids. Two intelligent methods of artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) have also been developed for the prediction of the experimental HTCs. The results indicate the prediction precision of the ANN model is higher than that of ANFIS. The RMSE and AARD of the ANN model are 1.05  and 3.02%, respectively.