A novel approach to determine residual stress field during FSW of AZ91 Mg alloy using combined smoothed particle hydrodynamics/neuro-fuzzy computations and ultrasonic testing

The faults in welding design and process every so often yield defective parts during friction stir welding (FSW). The development of numerical approaches including the finite element method (FEM) provides a way to draw a process paradigm before any physical implementation. It is not practical to simulate all possible designs to identify the optimal FSW practice due to the inefficiency associated with concurrent modeling of material flow and heat dissipation throughout the FSW. This study intends to develop a computational workflow based on the mesh-free FEM framework named smoothed particle hydrodynamics (SPH) which was integrated with adaptive neuro-fuzzy inference system (ANFIS) to evaluate the residual stress in the FSW process. An integrated SPH and ANFIS methodology was established and the well-trained ANIS was then used to predict how the FSW process depends on its parameters. To verify the SPH calculation, an itemized FSW case was performed on AZ91 Mg alloy and the induced residual stress was measured by ultrasonic testing. The suggested methodology can efficiently predict the residual stress distribution throughout friction stir welding of AZ91 alloy. (C) 2021 Chongqing University. Publishing services provided by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.

Automated summary

This study developed a computational workflow based on smoothed particle hydrodynamics (SPH) and adaptive neuro-fuzzy inference system (ANFIS) to evaluate residual stress in the friction stir welding process. The integrated SPH and ANFIS methodology efficiently predicted the residual stress distribution throughout the friction stir welding of AZ91 alloy.