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ClassificationCode:TG142.21
year,vol(issue):pagenumber:2024,49(2):255-264
Abstract:

  In order to investigate the high-temperature rheological behavior and thermal working process window of 7050 aluminum alloy, the isothermal compression experiments were conducted under the conditions of the deformation temperature of 573-723 K and the strain rate of 0.01-10 s-1, and sixteen sets of rheological data were obtained. Then, based on these rheological data, a new constitutive model was proposed and compared with classical models in terms of prediction accuracy, material parameters and solution algorithms. The results indicate that the new model has the highest prediction accuracy, while HS model has the lowest prediction accuracy. Material parameter acquisition obtaining of the new model and HS model only requires multiple linear regression, and AH model requires multiple nonlinear regression. The new model has therty parameters, AH model has twenty-four parameters, and HS model has nine parameters. It can be seen that the new model reduces the difficulty of parameter acquisition and significantly improves the prediction accuracy without significantly increasing the number of material parameters. In addition, based on the new model, the analytical equation of hot processing map for 7050 aluminum alloy was deduced, and its hot processing map was drawn. The microstructure analysis results verify the effectiveness of the hot processing map. The results show the risk of instability is small at the deformation temperature of 623-723 K and the strain rate of 0.01-10 s-1. The energy dissipation rate is approximately in the range of 20%-40%, and the material can fully undergo the dynamic recrystallization.

Funds:
基金项目:重庆市教委科学技术研究项目(KJQN202103209)
AuthorIntro:
作者简介:金明(1981-), 男,硕士,教授
Reference:

 
[1]董红松,李辉.基于NSGA-Ⅱ的7050铝合金锻造力学性能多目标优化
[J].锻压技术,2023,48(8):41-47.


 

Dong H S, Li H. Multiobjective optimization on forging mechanical property for 7050 aluminum alloy based on NSGA-Ⅱ
[J]. Forging & Stamping Technology, 2023, 48(8): 41-47.

 


[2]Quan G Z, Wang T, Li Y L, et al. Artificial neural network modeling to evaluate the dynamic flow stress of 7050 aluminum alloy
[J]. Journal of Materials Engineering & Performance, 2016, 25(2):1-12.

 


[3]郝爱国,吉卫,郝花蕾.7050铝合金的热变形行为及热加工图研究
[J].热加工工艺,2018,47(17):141-144.

 

Hao A G, Ji W, Hao H L. Study on hot deformation behavior and hot processing map of 7050 aluminum alloy
[J]. Hot Working Technology, 2018, 47(17):141-144.

 


[4]夏洪均,唐全波,王敬,等.7050铝合金修正本构模型及ZenerHollomon参数演化
[J].塑性工程学报,2022,29(6):149-156.

 

Xia H J, Tang Q B, Wang J, et al. Modified constitutive model and ZenerHollomon parameter evolution of 7050 aluminum alloy
[J]. Journal of Plasticity Engineering, 2022, 29(6):149-156.

 


[5]王运,张昌明,张昱.航空Al7050合金的静动态力学特性研究及JC本构模型构建
[J].材料导报,2021,35(10):10096-10102.

 

Wang Y, Zhang C M, Zhang Y. Study on static and dynamic mechanical properties of aviation Al7050 alloy and construction of JC constitutive model
[J]. Materials Reports,2021,35(10):10096-10102.


[6]杨成曦,王姝俨,吴道祥.锻态7050铝合金修正JC本构模型建立与模拟应用
[J].铝加工,2022,(4):47-51.

 

Yang C X, Wang S Y, Wu D X. Construction and simulation application of modified JohnsonCookconstitutive model for forged 7050 aluminum alloy
[J]. Aluminium Fabrication, 2022,(4):47-51.

 


[7]苏燕,梁武.基于RBF神经网络的铸轧7050铝合金的力学性能预测
[J].热加工工艺,2018,47(21):145-147,151.

 

Su Y, Liang W. Prediction of mechanical properties of casting rolling 7050 aluminum alloy based on RBF neural network
[J]. Hot Working Technology, 2018, 47(21):145-147,151.

 


[8]马斌,梁强,贾艳艳,等.基于BPNN、SVR和RF模型的7050合金高温流动应力预测
[J].材料热处理学报,2023,44(3):196-204.

 

Ma B, Liang Q, Jia Y Y, et al. Prediction of high temperature flow stress of 7050 aluminum alloy based on BPNN, SVR and RF models
[J]. Transactions of Materials and Heat Treatment, 2023, 44(3):196-204.

 


[9]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.

 


[10]Liu S H, Pan Q L, Li H, et al. Characterization of hot deformation behavior and constitutive modeling of AlMgSiMnCr alloy
[J].Journal of Materials Science, 2019, 54:4366-4383.

 


[11]Rudra A, Das S, Dasgupta R. Constitutive modeling for hot deformation behavior of Al-5083+SiC composite
[J]. Journal of Materials Engineering and Performance, 2019, 28: 87-99.

 


[12]陈学文, 杨喜晴, 王纳纳. GCr15SiMn钢的温变形行为及HanselSpittel流变应力模型
[J]. 金属热处理, 2018, 43(5):34-38.

 

Chen X W, Yang X Q, Wang N N. Warm deformation behavior and HanselSpittel of constitutive model of GCr15SiMn steel
[J]. Heat Treatment of Metals, 2018, 43(5):34-38.

 


[13]Richardson G J, Sellars C M, Tegart W. Recrystallization during creep of nickel
[J]. Acta Metallurgica, 1966, 14(10):1225-1236.

 


[14]Zhang J S, Xiao G Q,Deng G Y, The quadratic constitutive model based on partial derivative and taylor series of Ti6242s alloy and predictability analysis
[J].Materials,2023,16(7):2928.

 


[15]Prasad Y V R K, Gegel H L, Doraivelu S M, et al. Modeling of dynamic material behavior in hot deformation: Forging of Ti-6242
[J]. Metallurgical Transactions A, 1984, 15(10):1883-1892.

 


[16]赵天生. 7050铝合金T形截面高筋薄壁锻件成形工艺优化及多级时效研究
[D].重庆:重庆大学,2017.

 

Zhao T S. Study on Optimization of Forming Process and Multi Stage Aging for 7050 Alloy Tshape Section with High Reinforcement and Thin Wall Forgings
[D]. Chongqing:Chongqing University, 2017.

 
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