A Finite Element Model for the Prediction of Chip Formation and Surface Morphology in Friction Stir Welding Process

Author:

Das Debtanay1,Bag Swarup1,Pal Sukhomay1,Amin M Ruhul2

Affiliation:

1. Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Assam 781039, India

2. Department of Mechanical and Industrial Engineering, Montana State University, Bozeman, MT 59717

Abstract

Abstract Friction stir welding (FSW) is widely recognized green manufacturing process capable of producing good quality welded joints at a temperature lower than the melting point. However, most of the works are focused on the establishment of the process parameters for a defect-free joint. There is a lack to understand the formation of defects from a 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 for the material loss during the process. Hence, a three-dimensional (3D) finite element-based thermomechanical 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 the CEL approach, the material flow out of the workpiece enables the visualization of the chip formation, whereas small deformation predicts the surface quality of the joint.

Publisher

ASME International

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Control and Systems Engineering

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2. A Physics-Informed Machine Learning Model of Dissimilar Friction Stir Welding to Tailor Residual Stress Using Coupled Eulerian and Lagrangian Approach;Journal of Materials Engineering and Performance;2024-04-26

3. Numerical simulation of thermomechanical behavior and mechanical property in HRFSW of Aluminum Alloy;The International Journal of Advanced Manufacturing Technology;2024-04-01

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