Abstract
In order to obtain the joint with a high tensile shear load, the small penetration of tool pin into the lower sheet was applied during friction stir lap welding. The tensile shear loads of the Al–Mg–Si aluminum alloy joint under different process parameter combinations were optimized by combining back propagation neural network and genetic algorithm. The result showed that the hook bent down and the height of cold lap was small. Under the external tension load, the crack propagated along the lap interface or extended downward after reaching the highest point along the cold lap. With the increase of heat input, the tensile fracture mode of joint was more easily obtained. The highest tensile shear load of the joint reached 12.45kN, which was increased by 6.9% than the maximum value before optimization.
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