Novel Correlations Between Process Forces and Void Morphology for Effective Detection and Minimization of Voids During Friction Stir Welding

Abstract

Sub-surface voids and material heterogeneities resulting from the friction stir welding (FSW) process often necessitate post-weld inspection to ensure the quality of weld obtained from this solid-state welding process. In this context, in-process void detection techniques can potentially help in optimizing the process conditions and thereby reduce expensive and time-consuming post-process inspection of welds. Current in-process void detection techniques rely on approaches that try to directly correlate the part-scale welding quality to void formation, without a fundamental understanding of the underlying mechanics and materials physics that modulate void evolution. In this work, we demonstrate an effective in-process numerical technique that uses process force signals to detect volumetric void formation and connect the variations in the force signals to interactions between the tool probe and the underlying material voids. Our approach relies on a high-fidelity finite element analysis simulation of the FSW process and on correlation of numerically obtained process force signals with the corresponding void structures. This correlation is obtained in the phase-space relating in-plane reaction forces on the tool to the tool rotation angle. We focus on the interactions of the tool geometry and tool motion with the surrounding material undergoing plastic deformation and deduce novel insights into various correlations of tool motion and void formation. Through this approach, we can identify tool-related process conditions that can be optimized to minimize void formation and demonstrate a potential in situ force-based void monitoring method that links to the underlying plastic flow and void structures during the FSW process.