Prediction of microstructural features and forming of friction stir welded sheets using cellular automata finite element (CAFE) approach

Abstract

The main aim of the present work is to predict the microstructural features like grain size and dislocation density in the weld zone during friction stir welding (FSW) of similar (Al6061T6/Al6061T6) and dissimilar (Al6061T6/Al5086O) Aluminium grades using Cellular Automata Finite Element (CAFE) approach. The FSW process is not modelled with the stirring action, instead heat flux, strain-rate and strain are incorporated by analytical models. The grain size is controlled through cellular automata (CA) cells and dislocation density is related to this by two different (analytical and empirical) models. After FSW, four different methods are proposed for predicting the tensile behaviour of weld zone and the efficiency of these methods is evaluated through validations. The results indicate that the thermal, strain-rate, and strain models are accurate enough in their predictions when compared with existing results. The grain size predictions from CAFE model, which include the transition rule, are also consistent with the literature results, both for similar and dissimilar material combinations. The analytical model shows better dislocation density prediction than empirical model when compared with the experimental data. Of all the methods proposed for tensile behaviour prediction, the CAFE model that includes dislocation density evolution using the second model is efficient and accurate. The stress–strain data predicted from an averaged flow stress of many CA cells is also encouraging. Through these results, it has been demonstrated that the CAFE approach along with few validated analytical models can be used to predict the micro-features and forming aspects during FSW consistently.