Transactions of Materials and Heat Treatment

Title：Multi-objective optimization on forging mechanical property for 7050 aluminum alloy based on NSGA-II

Authors： Dong Hongsong1 Li Hui2

Unit： 1.Department of Computer Science and Technology Lyuliang College 2.Department of Mining Engineering Lyuliang College

KeyWords： 7050 aluminum alloy mechanical property NSGA-II algorithm multi-objective optimization Pareto optimal solution set

ClassificationCode：TG376

year,vol(issue):pagenumber：2023,48(8):41-47

Abstract：

In order to explore the influence of forging process parameters on mechanical properties of 7050 aluminum alloy forgings, based on the isothermal forging process of 7050 aluminum alloy, the Box-Behnken response surface test was designed to establish a regression model between mechanical properties (tensile strength and elongation) and forging process parameters (forging temperature, deformation rate and forging speed) of 7050 aluminum alloy forgings, and through the variance analysis of regression model, the influence order of each process parameter on the mechanical properties and their interaction were obtained. Then, based on MATLAB software, the non-dominated sorting genetic algorithm NSGA-II was used to find the Pareto optimal solution set for the regression model of 7050 aluminum alloy mechanical properties, and the optimal process parameter combination was obtained. The results show that the influence order of 7050 aluminum alloy forging process parameters on the tensile strength of forgings is forging temperature >forging speed> deformation rate > (forging temperature × forging speed) > (deformation rate × forging speed). The influence order on the elongation is forging temperature > deformation rate > (forging temperature × forging speed ) > (forging temperature × deformation rate) > forging speed. Pareto optimal process parameter combination is the forging temperature of 399.8 ℃, the deformation rate of 59.84% and the forging speed of 15.03 mm·s-1. Then the tensile strength is 605.30 MPa, the elongation is 14.78%, and the mechanical properties of 7050 aluminum alloy forgings are better.

Funds：

山西省高等学校科技创新项目资助（2022L574）;吕梁市科技局项目（2022RC21,2022GXYF16）

作者简介：董红松（1989-），男，博士，讲师 ,E-mail：dong_hs@126.com

Reference：

[1]郭宇娟. 7050高强铝合金模锻工艺基础及应用研究[D].武汉：华中科技大学,2014.

Guo Y J. Study on Die-forging Technology and Application of 7050 High-strength Aluminum Alloy[D]. Wuhan：Huazhong University of Science & Technology,2014.

[2]马志民,刘佳,贾文太.车辆用7050铝合金多向锻造对其组织与性能的影响[J].兵器材料科学与工程,2018,41(5):70-73.

Ma Z M，Liu J，Jia W T. Effect of multidirectional forging on microstructure and properties of 7050 aluminum alloy for vehicles[J]. Ordnance Material Science and Engineering,2018,41(5):70-73.

[3]张含茹. 7050铝合金热态流变行为及其微观组织演变研究[D].济南：山东大学,2022.

Zhang H R. Study on Thermal Rheological Behavior and Microstructure Evolution of 7050 Aluminum Alloy[D]. Jinan: Shandong University,2022.

[4]吴秀江. 7050铝合金模锻件组织均匀性调控及其组织演变研究[D].秦皇岛：燕山大学,2021.

Wu X J. Study on the Microstructure Homogeneity Regulation and it′s Microstructure Evolution of 7050 Aluminum Die Forgings[D]. Qinhuangdao: Yanshan University,2021.

[5]刘伟,李忠文,李春明，等.7050铝合金热锻速度对再结晶及其性能的影响[J].热加工工艺,2018,47(5):34-37.

Liu W, Li Z W, Li C M, et al. Effects of hot forging speed on recrystallization and properties of 7050 aluminum alloy[J]. Hot Working Technology, 2018,47(5):34-37.

[6]徐显强,董显娟,徐勇，等.7050铝合金的蠕变行为研究[J].锻特种铸造及有色合金,2023,43(6):825-830.

Xu X Q, Dong X J, Xu Y, et al. Creep behavior of 7050 aluminum alloy[J]. Special Casting & Nonferrous Alloys, 2023,43(6):825-830.

[7]鲁法云,赵凤,赵业青，等.锻造变形量对7050合金组织和性能的影响[J].材料导报,2015,29(8):105-109，113.

Lu F Y, Zhao F, Zhao Y Q, et al. Effect of forging reduction on the microstructure and properties of 7050 aluminum alloy[J]. Materials Review,2015,29(8):105-109，113.

[8]吴道祥,周杰,张建生，等.7050铝合金航空锻件热锻成形穿流缺陷分析[J].华中科技大学学报：自然科学版,2015,43(4):69-73.

Wu D X, Zhou J, Zhang J S,et al. Analyzing partial draining of 7050 aluminum alloy aircraft forging after hot die forming[J]. Journal of Huazhong University of Science & Technology: Natural Science Edition ,2015,43(4):69-73.

[9]GB/T 228.1—2021，金属材料拉伸试验第1部分：室温试验方法[S].

GB/T 228.1—2021，Metallic materials—Tensile testing—Part 1: Method of test at room temperature [S].

[10]王梦寒,黄龙,王瑞，等.基于响应面法的铝合金筋板锻件工艺参数多目标优化[J].材料科学与工艺,2014,22(1):123-128.

Wang M H, Huang L, Wang R, et al. Multi-objective optimization of process parameters by RSM for aluminium-alloy rib-web forgings[J]. Materials Science and Technology, 2014,22(1):123-128.

[11]李辉,杨锋,袁博. 基于响应曲面法的消失模铸造ZL102合金的力学性能[J]. 特种铸造及有色合金, 2019, 39(3):286-289.

Li H, Yang F, Yuan B. Mechanical properties of lost foam casting Al-Si alloy parts based on response surface method[J]. Special Casting and Nonferrous Alloys, 2019, 39(3): 286-289.

[12]黄俊, 陈子博, 刘其蒙, 等. 基于NSGA-II的离体皮肤组织激光融合工艺参数的多目标优化[J]. 中国激光, 2019, 46(2)：199-205.

Huang J, Chen Z B, Liu Q M, et al. Multi-objective optimization for laser closure process parameters in vitro skin tissue based on NSGA-II[J]. Chinese Journal of Lasers, 2019, 46(2)：199-205.

[13]付涛, 刘伟军, 赵吉宾. 基于NSGA-II算法的高强度模具钢切削参数优化方法[J]. 机械工程材料, 2013, 37(12): 85-91.

Fu T, Liu W J, Zhao J B. Parameters optimization in cutting of high-strength mould steel based on NSGA-II[J]. Materials for Mechanical Engineering, 2013, 37(12): 85-91.

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