Al-enabled properties distribution prediction for high-pressure die casting Al-Si alloy  

作　　者：Yu-Tong Yang Zhong-Yuan Qiu Zhen Zheng Liang-Xi Pu Ding-Ding Chen Jiang Zheng Rui-Jie Zhang Bo Zhang Shi-Yao Huang 

机构地区：[1]Key Laboratory for Light-Weight Materials,Nanjing Tech University,Nanjing,211816,People’s Republic of China [2]Xi’an Jiaotong-Liverpool University,Suzhou,215000,Jiangsu,People’s Republic of China [3]Materials Academy JITRI,Suzhou,215100,Jiangsu,People’s Republic of China [4]Key Laboratory for Light-weight Materials,Nanjing University of Science and Technology,Nanjing,210009,People’s Republic of China [5]College of Materials Science and Engineering,Chongqing University,Chongqing,400044,People’s Republic of China [6]Collaborate Innovation Center of Steel Technology,University of Science and Technology Beijing,Beijing,100083,People’s Republic of China [7]Chongqing Millison Technologies Inc.,Chongqing,401321,People’s Republic of China

出　　处：《Advances in Manufacturing》2024年第3期591-602,共12页先进制造进展（英文版）

基　　金：support from the National Natural Science Foundation of China(Grant Nos.51575068,51501023,and 52271019).

摘　　要：High-pressure die casting(HPDC)is one of the most popular mass production processes in the automotive industry owing to its capability for part consolidation.However,the nonuniform distribution of mechanical properties in large-sized HPDC products adds complexity to part property evaluation.Therefore,a methodology for property prediction must be developed.Material characterization,simulation technologies,and artificial intelligence(AI)algorithms were employed.Firstly,an image recognition technique was employed to construct a temperature-microstructure characteristic model for a typical HPDC Al7Si0.2Mg alloy.Moreover,a porosity/microstructure-mechanical property model was established using a machine learning method based on the finite element method and representative volume element model results.Additionally,the computational results of the casting simulation software were mapped with the porosity/microstructure-mechanical property model,allowing accurate prediction of the property distribution of the HPDC Al-Si alloy.The AI-enabled property distribution model developed in this study is expected to serve as a foundation for intelligent HPDC part design platforms in the automotive industry.

关 键 词：Artificial intelligence(AI) Properties prediction High-pressure die-casting(HPDC) Image recognition Machine learning 

分 类 号：TG146[一般工业技术—材料科学与工程]