Computational fluid dynamics analysis of MQL spray parameters and its influence on superalloy grinding

Abstract

ABSTRACTThe application of emulsion for combined heat extraction and lubrication requires continuous monitoring of the quality of emulsion to sustain a desired grinding environment; this is applicable to other grinding fluids as well. To sustain a controlled grinding environment, it is necessary to adopt an effectively lubricated wheel–work interface. The present work aims to develop a numerical model to replicate the mist formation in minimum quantity lubrication (MQL) grinding using a fluent-based computational fluid dynamics (CFD) flow solver. The MQL parameters considered for this study are air pressure and the mass flow rate. Simulation of the atomization under turbulent conditions was done in a discrete phase model (DPM) owing to the fact that oil mass flow rates are very low and oil acts as a discrete medium in air. Jet velocity and droplet diameters were also obtained under different input conditions to find the optimum value of air pressure and mass flow rate of oil to achieve the desired results (lower cutting force and surface roughness) in MQL grinding of superalloy (Inconel 751). It is seen that medium size (around 16.3 µm) of droplet plays a significant role in improved performance by the way of reduction in cutting force and surface roughness.