Experimental and finite element simulation for thermal distribution in TIG, MIG and TIG-MIG hybrid welds

• Published in: International journal on interactive design and manufacturing 2024-04, Vol.18 (3), p.1171-1181
• Main Authors: Abima, Cynthia Samuel, Madushele, Nkosinathi, Mwema, Fredrick Madaraka, Akinlabi, Stephen Akinwale
• Format: Article
• Language: English
• Subjects: CAE) and Design; Computer-Aided Engineering (CAD; Electronics and Microelectronics; Engineering; Engineering Design; Evolution; Finite element method; Friction stir welding; Gas metal arc welding; Gas tungsten arc welding; Industrial Design; Instrumentation; Investigations; Lasers; Mechanical Engineering; Mechanical properties; Optimization; Original Paper; Process parameters; Rare gases; Residual stress; Seam welds; Simulation; Taguchi methods; Temperature; Temperature profiles; Tensile strength; Thermal simulation; Thermodynamic properties; Yield stress
• ISSN: 1955-2513; 1955-2505
• DOI: 10.1007/s12008-022-01173-9

The Tungsten Inert Gas-Metal Inert Gas (TIG-MIG) hybrid process has the combined advantages of standalone TIG and MIG welding processes. This study investigates the thermal distribution of the TIG-MIG hybrid welding process compared to the standalone TIG and MIG welding processes. The welds' mechanical properties, microstructural evolution, and phase formation are also discussed. The process parameters for the TIG-MIG, TIG and MIG welding processes used in this study were obtained from prior parametric optimisation for each welding process performed by the Taguchi method with an L-9 orthogonal matrix. The thermal behaviour of TIG, MIG and TIG-MIG welds were investigated by adopting the Gaussian heat source model on the ANSYS workbench. The simulated temperature distributions of the three weld types were validated by the mechanical, microstructural, and phase formation characteristics as obtained experimentally. Similar temperature profiles were observed for all weld types having peak temperatures at the weld seams. The simulated temperature distributions were in good correlation with the experimentally obtained the hardness results, microstructural evolution and phase formation, as revealed from the X-ray diffraction analysis. Hence, the Gaussian heat source model can accurately simulate the properties of a complex heat source interaction, allowing for process optimisation and forecasting.