The Automotive industry extensively uses cast iron for its exceptional mechanical performance and cost-effectiveness. However, repair welding or assembly of cast iron components remain highly challenging due to the material’s high carbon content, inherent brittleness, rapid thermal conductivity, and complex microstructural transformations. Multi-pass welding exacerbates these challenges by subjecting materials to repeated thermal cycling, accumulating residual stress, and inducing distortion – all of which potentially degrade the integrity of welded joints. A comprehensive understanding of welded joint behavior is essential to effectively mitigate these effects. Finite element analysis (FEA) serves as a powerful tool, enabling accurate prediction of thermal profiles, phase transformations, residual stress development, and resulting deformations. These valuable insights are critical for optimizing welding processes and enhancing overall joint quality.
This study investigates and validates the use of FEA-based simulation tools for multi-pass MIG welding of ductile cast iron plates, highlighting the effectiveness of virtual modeling in complex welding scenarios. A numerical simulation of 20 mm thick cast iron plates welded with Ni-Fe filler wire was conducted using SYSWELD software. The distortion, temperature distribution, microstructure, hardness, and residual stresses of the weld coupon were predicted using a thermo-metallurgical-mechanical model. The simulation incorporated a double-elliptical heat source for welding and an imposed thermal cycle model for pre- and post-weld heat treatments. Metallurgical analysis was performed utilizing a phase transformation model and Continuous Cooling Transformation diagram to estimate microstructural phase fractions and hardness. The mechanical analysis, based on the thermo-metallurgical profile and boundary conditions, evaluated weld distortion and residual stresses on weld coupon. Predicted results, including thermal cycles, fusion zone, distortion, hardness, and residual stresses, were validated against experimental data showed strong coherence.
This study demonstrates the efficacy of FEA tools in accurately predicting dissimilar weld properties, reinforcing their reliability for welding and repair of cast iron components in industrial applications.