1. Chengdu Aircraft Industry(Group) Co., Ltd., Chengdu 610092, China
2. School of Materials Science and Engineering, Southwest Jiaotong University, Chengdu 610031, China
In this paper, an improved efficient global optimization algorithm based on the Kriging model was proposed and applied to optimize the semi-solid isothermal treatment parameters of Mg-Zn-Y-Zr alloys containing quasicrystals. Firstly, the Mg-1.2Zn-0.2Y-0.15Zr alloy containing quasicrystalline phases was designed and prepared by casting and primary hot extrusion. Then the sample data set and Kriging surrogate model between the semi-solid isothermal treatment parameters of the alloy and its mechanical properties were established. Finally, by combining machine learning and the semi-solid isothermal treatment + hot extrusion composite processing technology, a significant optimization of the comprehensive mechanical properties of the alloy was achieved. Through a total of four iterative optimizations, the maximum tensile strength of （427.4±1.6） MPa was obtained, and its semi-solid process parameters were 574 ℃/60 min. Compared with its primary extrusion state alloy (（285±1.5） MPa), the tensile strength of the optimized alloy increased by nearly 50%. It is proved that the machine learning method is feasible and efficient for optimizing the semi-solid isothermal treatment parameters and enhancing the strength of Mg-Zn-Y-Zr alloys.