A Finite Element Model for the Prediction of Chip Formation and Surface Morphology in Friction Stir Welding Process
Abstract Friction stir welding (FSW) is widely recognized green manufacturing process capable of producing good quality welded joints at temperature lower than the melting point. However, most of the works is focused on to the establishment of the process parameters for a defect-free joint. There is a lack to understand the formation of defects from physical basis and visualization of the same, which is otherwise difficult to predict by means of simple experiments. The conventional models do not predict chip formation and surface morphology by accounting the material loss during the process. Hence, a 3D finite element based thermo-mechanical model is developed following Coupled Eulerian-Lagrangian (CEL) approach to understand surface morphology by triggering material flow associated with tool-material interaction. In the present quasi-static analysis, the mass scaling factor is explored to make the model computationally feasible by varying the FSW parameter of plunge depth. The simulated results are validated with experimentally measured temperature and surface morphology. In CEL approach, the material flow out of the workpiece enables the visualization of the chip formation, whereas small deformation predict the surface quality of the joint.