CFD-MODELLING AND THERMAL CHARACTERIZATION OF FRICTION STIR WELDING USING TOOL WITH POLYGONAL PINS
Keywords:
KEYWORDS: Friction Stir Welding (FSW); Polygonal Pin; Analytical Approaches; Computational Fluid Dynamics (CFD); Dynamic Mesh; Liquid Fraction.Abstract
ABSTRACT
In the last two decades, Friction Stir Welding (FSW) has shown a capability to produce high strength joints particularly for the materials that cannot be welded by the conventional welding processes. Hence, optimizing the FSW process parameters to improve the quality of welded joint is still a subject of active research. In view of that, the efficient control of the welding thermal cycle through the geometrical and operational parameters may lead to produce sound weldments where defects can be avoided. Various studies have been carried out considering different tool pin profiles to improve the mechanical strength of welded joint, but the influences of the polygonal pin profiles on the thermal characterizations have been rarely reported in details. Besides, the experimental work has often showed that it is cost and time consuming particularly when the effect of geometrical variables is investigated. The present work focuses on the integral employment of analytical approaches and Computational Fluid Dynamics (CFD) tool to simulate the heat generation and the thermal field associated to the FSW when using tool with polygonal pins. A three-dimensional CFD model considering both dynamic mesh and sliding mesh techniques has been used to investigate the effect of a wide range of geometrical and operational parameters on the temperature distribution and peak temperature within thick FS welded workpieces. A set of novel analytical formulas have been developed to calculate the amount of heat generation corresponding to the pin shape. The improved numerical model has captured the temporal and spatial temperature distribution throughout the weldments and succeeded to monitor the liquid fraction when the material temperature exceeding the solidus temperature. Moreover, the acquired numerical results have then been used to develop a novel semi-empirical prediction model for the peak temperature. https://jer.ly/PDF/Vol-32-2021/JER-04-32-Abstract.php?f=a
