A novel hybrid nanofluid including MWCNT and ZrO₂ nanoparticles: implementation of response surface methodology and artificial neural network

In this study, the thermal behavior of a hybrid nanofluid including nanoparticles of multi-walled carbon nanotube (MWCNT) and ZrO ₂ was discussed. The nanoparticles of MWCNT and ZrO ₂ at the mass fraction 40:60 were added to pure water with CMC surfactant to prepare samples at 0.009, 0.018, 0.036, 0.072 and 0.14 vol%. The thermal conductivity of MWCNT - ZrO ₂/ water (kZrO2-MWCNT/water) was measured at temperature range of 20–50 °C and compared with k _water to investigate the effectiveness of adding MWCNT - ZrO ₂ nanoparticles to the base fluid by evaluating the parameter of thermal conductivity ratio (TCR =kZrO2-MWCNT/waterkwater) . The results showed that an increase in temperature results in a higher TCR . The use of MWCNT - ZrO ₂ led to an increase in thermal conductivity up to 15.4%. To boost the amount of improvement, the sonication time increased from 30 to 60 min. The best sonication time was 50 min so that MWCNT and ZrO ₂ nanoparticles could enhance k _water by 59.6%. To estimate TCR, the response surface methodology was used, which based on linear regression, provides a function consisting of independent variables, and it was found for the best function with an error of less than 1.52% and by providing R ² = 0.998, can estimate TCR very well. Then artificial intelligence was used, and it was determined that the neural network consisting of eight neurons with a maximum error of less than 0.4% could predict TCR.