Abstract
The Support Vector Machine method is employed to predict the thermo-physical properties of hybrid nanofluid composed of TiO2 and ZnO nanoparticles and ethylene glycol as the base fluid at different temperatures, shear rates, and nanoparticle volume fractions. The present work novelty is to use a new sensitivity analysis based on this method which has been widely utilized in the regression and function approximation fields. In addition, the SVM method advantages are its unique solutions, high accurate outcomes at the training data points, and appropriate generalization. Regarding the obtained results, effects of different mentioned working conditions on apparent viscosity and shear stress have examined besides the highest values of sensitivities and pertinent independent parameters are reported. The new statistical/ math proposed model can predict the apparent viscosity, shear stress and shear rate of TiO2/ZnO/EG non-Newtonian hybrid nanofluid which implies its suitable performance for multi-phase non-Newtonian fluids.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Physica A: Statistical Mechanics and its Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
