Numerical study of flow and heat transfer of minimum quantity lubrication based nanofluid in a turning process using Inconel alloy

Finite element analysis in conjunction with discrete phase model was utilized in this investigation to study the effect of using MQL nanofluid on the average temperature of the cutting tool. The numerical results were validated experimentally, and the relative error was 9.7% in the absence of nanoparticles and 2.7 % for nanoparticles with a volume fraction of 2%. The numerical results illustrated that the addition of Al₂O₃ nanoparticles to MQL reduced the average temperature of the cutting tool from 443 K (0% volume fraction) to 420 K for a volume fraction of 2%. This is evidently demonstrating the significance of decreasing the cutting tool temperature when using nanoparticles with MQL. The results presented in this study also revealed that the temperature variation was considerably greater in the first 0.5 mm from the cutting tool tip over both the rake and flank faces compared with locations far away from the tip. The present study paves the road for the researchers to utilize CFD along with discrete phase model in turning operation to understand the effect of MQL nanofluid on the average temperature of the cutting tool and select the optimum parameters for maximizing heat transfer from the cutting zone.