Predicting temperature of semi-solid 7075 aluminum alloy slurry prepared by a novel rheocasting route via neural network

Li, Gan; Cheng, Le; Yue, Qiang; Hu, Xiaogang; Lu, Hongxing; Zhu, Qiang

2023-10-15

10.1016/j.matlet.2023.134753

MATERIALS LETTERS   影响因子和分区

0167-577X

1873-4979

The rapid preparation of desired semi-solid slurry with a specific average temperature and a high temperature uniformity is of essential importance for the rheocasting of high-strength aluminum (Al) alloys. In this study, a novel semi-solid slurry preparation process, namely Enthalpy Control Process (ECP), has been proposed for rapid preparation of 7075 Al alloy slurry. The machine learning approach from the aspect of neural network was utilized to predict the average temperature and maximum temperature difference of the Al slurry prepared by ECP. The results indicated that the temperature values predicted by Back Propagation Neural Network optimized by Genetic Algorithm (GA-BPNN) models exhibit an excellent fit with the experimental results. The average relative error and the coefficient of determination for average temperature of were 0.9988 and 0.027%, while the values for the maximum temperature difference were 0.9910 and 3.4%, respectively. The GA-BPNN has a great latent capacity in predicting the temperature of the semi-solid slurry.

Temperature distribution Artificial neural network Semi-solid slurry Metals and alloys Enthalpy control process Metal forming and shaping

SCI ; EI

英语

第一 ; 通讯

GuangDong Basic and Applied Basic Research Foundation[2023A1515012407] ; Shenzhen Science and Technology Innovation Commission["JCYJ20220818100613028","JCYJ20210324104610029","ZDSYS201703031748354"]

Materials Science ; Physics

Materials Science, Multidisciplinary ; Physics, Applied

WOS:001022177600001

ELSEVIER

20232514260992

Aluminum alloys ; Enthalpy ; Forecasting ; Genetic algorithms ; High strength alloys ; Magnesium alloys ; Metal forming ; Process control

Metallurgy:531.1 ; Metal Forming:535.2 ; Aluminum Alloys:541.2 ; Magnesium and Alloys:542.2 ; Alkaline Earth Metals:549.2 ; Thermodynamics:641.1

MATERIALS SCIENCE

Web of Science

Southern Univ Sci & Technol, Dept Mech & Energy Engn, Shenzhen 518055, Peoples R China

Li, Gan,Cheng, Le,Yue, Qiang,et al. Predicting temperature of semi-solid 7075 aluminum alloy slurry prepared by a novel rheocasting route via neural network[J]. MATERIALS LETTERS,2023,349.

Li, Gan,Cheng, Le,Yue, Qiang,Hu, Xiaogang,Lu, Hongxing,&Zhu, Qiang.(2023).Predicting temperature of semi-solid 7075 aluminum alloy slurry prepared by a novel rheocasting route via neural network.MATERIALS LETTERS,349.

Li, Gan,et al."Predicting temperature of semi-solid 7075 aluminum alloy slurry prepared by a novel rheocasting route via neural network".MATERIALS LETTERS 349(2023).