Applying Artificial Neural Networks (ANNs) for prediction of the thermal characteristics of engine oil –based nanofluids containing tungsten oxide -MWCNTs

• DOI: 10.1016/j.csite.2021.101122
• Publication Date: 2021-06-04T18:39:19Z
• Authors: Farid Soltani; Mehdi Hajian; Davood Toghraie; Ali Gheisari; Nima Sina; As'ad Alizadeh
• Keywords: Suspension; Volume fraction; Mass fraction

This paper aims to determine the thermal conductivity (knf) of oxide tungsten (WO3)-MWCNTs/hybrid engine oil, through an Artificial Neural Network (ANN). Nanofluid were prepared by suspension nanoparticles in oil. The experiments conducted at a volume fraction ϕ = 0.05 0.6%, as well temperature range T 20°C–60 °C. ANN was then used estimate knf, and optimum neuron number 7. Results showed that absolute error values method many points are zero. Also, had smaller compared correlation method. acceptable performance coefficient. predict knf.