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The interactions among thermal history, plastic deformation and residual stresses in the friction stir welding (FSW) process under different welding parameters have been widely considered a crucial issue and still not fully understood. In the present study, a novel three-dimensional fully coupled thermo-mechanical finite element (FE) model based on Coupled Eulerian-Lagrangian approach (CEL) has been developed to simulate the FSW process of aluminium alloy AA 6082-T6 and to analyse the thermo-mechanical interaction mechanisms under different welding conditions. The numerical model successfully simulates the plunge, dwell, and welding steps in FSW and captures the evolution of temperature, plastic deformation, and residual stresses in the welded joint. The obtained results were validated by experimental testing with observed cross-weld thermal history, optical macrography and residual stress measurement using the neutron diffraction technique. The results reveal that the tool rotation speed governs the temperature evolution; the peak temperature increased from 740 to 850 °K when the tool rotation speed rose from 800 to 1100 rpm. The rotational speed also affected the plastic deformation, material flow, and the volume of material being stirred during the welding process. Higher plastic deformation is formed in the stirring zone by increasing the tool angular velocity. This behaviour led to an increase in the stirring effect of the welding tool, reduction of the tunnel defect size and enhancing the quality of weldments. The distribution of residual stresses in different zones of the FSW joints has been found to have an M-shaped profile. A significant tensile residual stress is characterised in the edge of the nugget zone in both longitudinal and transverse directions, balanced by compressive stresses in the thermo-mechanically affected zone, heat-affected zone and base metal. The presented FE modelling provides a reliable insight into the effects of the welding parameters on the weld quality of FSW joints and process optimisation with minimised experimental trials.
Salih et al. (Fri,) studied this question.