Modeling and Simulation of advanced manufacturing processes
Modeling of Dissimilar FSW: To understand the friction stir welding of dissimilar materials Al 6061 and AZ31 alloy, a heat transfer numerical model is developed. Thermophysical properties were experimentally determined for the stir zone and compared with the base alloys. These are not strictly the average values of base alloys but indeed exhibit a complex relationship with the microstructural features and also on the intermixing of Al and Mg in the weld region. The numerical model is employed to predict the temperature distribution on advancing as well as retreating side. A good agreement between computed and experimentally measured results were obtained at 24-mm, 20-mm, and 16-mmtool shoulder diameter. The proposed model, thus can be used to predict the thermal cycle, peak temperature, and thermo-mechanically affected zone for welding of dissimilar materials on friction stir welding.
Modeling of Tool Wear during FSW: Understanding tool wear during friction stir welding (FSW) is important for the joining of high melting point metallic (HMPM) materials. Heat transfer and material flow based models developed in the past have improved our understanding of the friction-stir process. However, numerical models to predict tool wear and pin profile during FSW of HMPM materials are not available. Our research has focused on extending our previously developed and validated heat transfer and material flow model to predict tool wear and worn-out tool pin profile of H13 steel during FSW of Cu-0.8Cr-0.1Zr (CuCrZr) alloy. Temperature evolution and material flow are computed by solving conservation equations of mass, momentum and energy. This module is validated for thermal cycles and tool pin profile for various process parameters. Tool wear is predicted based on forces and stresses acting on the tool. Modified Archard’s wear theory is applied to compute tool wear and worn-out tool pin profile. The wear model successfully predicts the worn-out tool pin profile and self-optimized phenomena for various process parameters. The model has also been applied to understand the changes in worn-out pin profile during FSW process.