Heat transfer enhancement in engine oil based hybrid nanofluid through combustive engines: An entropy optimization approach

Abstract

Engine oil based hybrid nanofluid flow past a non-linearly stretching surface is important in solar energy applications, combustive engines, heat exchangers and many other industrial sector machinery. In this study, engine oil based hybrid nanofluid is modeled with multi-walled carbon nanotubes and copper oxide nanoparticles to enhance the heat transfer phenomena, minimize the entropy generation and to obtain a theoretical model more aligned with experimental findings. Engine oil hybrid nanofluid is modeled with non-linear thermal slip case so that a comparative study for no slip, linear slip and non-linear thermal slip is presented in a broader scenario. A variable magnetic field is applied in perpendicular direction with heat source/sink effects. Similarity analysis is conducted to obtain a non-dimensional system of ordinary differential equations. In order to solve the obtained system, a modified homotopy analysis approach is proposed with least square and Galerkin optimizers. Results are validated through mean squared residual errors and comparison with existing experimental data in literature. Analysis on results is presented through 2D plots, bar plots and pie charts. Highest percentage rate of increase in heat transfer of engine oil is obtained to be 23.75% with increase in heat source when volume fraction of both copper oxide and multi-walled carbon nanotubes is 4%. Moreover, entropy in engine oil flow is optimized till zero at 1% volume fraction of copper oxide and 3% volume fraction of multi-walled carbon nanotube in first order thermal slip case. These results are useful in enhancing various physical and engineering properties of engine oil 10W40C by adding multi-walled carbon nanotubes and copper oxide nanoparticles.