A 3D analytical thermal model in grinding considering a periodic heat source under dry and wet conditions

Official URL: http://dx.doi.org/10.1016/j.jmatprotec.2021.117158

Predicting the temperature distribution in the workpiece is of high importance to control and prevent thermally induced damages in grinding. Grinding force has an oscillating nature because of the discrete grit-workpiece interaction. The force fluctuation is more pronounced in macro level when the wheel vibrates due to run out or when segmented, grooved or pattern wheels are utilized. These fluctuations cause a discontinuous or a time-dependent heat source. In this study, the dynamic part of the heat source is included in an analytical thermal model as a new approach to understand detailed workpiece temperature behavior in grinding. Furthermore, heat convection from side surfaces of the workpiece was not included in previous analytical models and is formulated and discussed in this study for the first time. By considering proper boundary conditions an analytical solution for the workpiece temperature distribution by using the periodic heat source concept is proposed. The influential parameters are discussed theoretically, and it is shown that the heat source fluctuations cause an increase in maximum temperature compared to the case with a constant heat source. Furthermore, it is shown that the 2D solution is quite reliable and precise enough to predict the maximum temperature of the slab workpiece having a long width in both wet and dry conditions. Grinding experiments have been carried out to validate the model accuracy by embedding foil thermocouples in a split workpiece setup while using CBN electroplated and aluminum oxide wheels. Validation of discontinuous heat source model was investigated while the wheels have some run out. The effects of grinding conditions on the maximum temperature have been obtained experimentally and compared with the proposed model. The results show that considering a time-dependent heat source not only explains and predicts the cyclic nature of temperature but also improves the prediction of workpiece temperature accuracy.