Study on the inhomogeneity of Al–Zn–Cu–Mg aluminum alloy plates with different thickness

Li, Chen; Che, Guiyue; Xiao, Wenlong; Zang, Chenyang; Zhang, Xinquan; Fu, Yu; Ma, Chaoli

doi:10.1007/s10853-022-07928-9

Cited by 3 publications

(1 citation statement)

References 54 publications

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“…Even though the initial grain size is considered in the Sellars-Anelli model, the deformation of the surface layer of the plate cannot be identical to that of the central layer during the rolling process. The grain recrystallization near the surface layer will be higher than that of the central layer [36]. Therefore, the fitting results of the Anelli model are better.…”

Section: Grain Growth Model Comparisonmentioning

confidence: 99%

Effect of Solution Heat Treatment on the Microstructure and Microhardness of 7050 Aluminum Alloy

Qi,

Li,

Duan

et al. 2023

Metals

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Today, 7xxx aluminum alloys are widely used in aerospace and other fields due to their excellent properties such as low density, high specific strength, and good processing performance. The heat treatment process of 7xxx aluminum alloy is crucial in controlling the strengthening phases and grain size, which is a significant way to enhance the alloy’s performance. In this study, solution heat treatment tests of 7050 aluminum alloys were carried out at different temperatures, ranging from 440 °C to 470 °C, with a holding time ranging from 0.5 h to 8 h, using a DIL 805A thermomechanical test machine. The microstructural evolution during the solution heat treatment was characterized using an optical microscope (OM), a scanning electron microscope (SEM), and a transmission electron microscope (TEM). The effects of the solution parameters on the alloy’s microhardness were analyzed using a digital Vickers microhardness tester. According to the ASTM E112-13 standard, The Anelli grain growth models were established to illustrate the grain size evolution during solution heat treatment, and a modified Anelli grain growth model was established. The results indicated that the grain size significantly increases with the increase in the solution heat treatment time and temperature. The Anelli grain growth model can illustrate the phenomenon of grain growth more accurately in the solution heat treatment process of 7050 aluminum alloy. It was found that prolonging the time and elevating the temperature of the solution heat treatment reduced the microhardness of the aluminum alloy because of the dissolution of the precipitates.

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Section: Grain Growth Model Comparisonmentioning

confidence: 99%

Effect of Solution Heat Treatment on the Microstructure and Microhardness of 7050 Aluminum Alloy

Qi,

Li,

Duan

et al. 2023

Metals

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Machine Learning‐Based Strength Prediction for Two‐Stage Aged 7050 Aluminum Alloy Forgings in Aircraft Main Support Joints

Liu,

Qian,

Huang

et al. 2024

Adv Eng Mater

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Aluminum alloys, widely regarded as lightweight structural materials, are extensively used in the aerospace industry. The aging process is essential for reducing residual stresses and ensuring alloys quality. Traditional methods for optimizing aging are often time‐consuming and expensive. In contrast, machine learning (ML) accelerates material design and performance prediction, significantly minimizing the need for extensive experimentation. In this study, the 7050 aluminum alloy forgings in aircraft main support joints are selected as the research object. A forward prediction model is developed using common ML algorithms, incorporating two‐stage aging process parameters and microstructural features as inputs, with yield strength (YS) and ultimate tensile strength (UTS) as outputs. The results demonstrate that the extreme gradient boosting regression model is the most effective for predicting the strength of aluminum alloys, with R2 values exceeding 0.7. By the Shapley additive explanation (SHAP) method and microscopic morphology analysis, the second‐stage aging time (t2) significantly influences YS and UTS. Hence, t2 was selected as the output for constructing the reverse classification model. The support vector machine classification model exhibits optimal performance, attaining macro‐accuracy and macro‐recall rates of 0.91 and 0.90, respectively.

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Effect of non-isothermal aging treatments on the microstructure and properties of TiC-TiB2 ceramic particles-reinforced spray-formed 7055 aluminum alloy TIG weld metal

Cheng,

Xu,

et al. 2023

J Mater Sci

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Study on the inhomogeneity of Al–Zn–Cu–Mg aluminum alloy plates with different thickness

Cited by 3 publications

References 54 publications

Effect of Solution Heat Treatment on the Microstructure and Microhardness of 7050 Aluminum Alloy

Effect of Solution Heat Treatment on the Microstructure and Microhardness of 7050 Aluminum Alloy

Machine Learning‐Based Strength Prediction for Two‐Stage Aged 7050 Aluminum Alloy Forgings in Aircraft Main Support Joints

Effect of non-isothermal aging treatments on the microstructure and properties of TiC-TiB2 ceramic particles-reinforced spray-formed 7055 aluminum alloy TIG weld metal

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