Entire-Process Simulation of Friction Stir Welding — Part 2: Implementation of Neural Networks

Abstract

To further understand the structure-parameter-property relationships of friction stir welded aluminum alloy joints, a nested neural network was proposed to map the macro- and microstructural response. The uncoupled effect of each primitive parameter on the joint performance was depicted. Reducing heat input and keeping an adequate load-bearing area of the welding nugget zone were proven to be the sufficient and necessary conditions to obtain high load-bearing performance. The entire-process simulation strategy showed great potential for prediction and optimization of the macro- and microstructural response of complex and large components.