Static Globularization Behavior and Artificial Neural Network Modeling during Post-Annealing of Wedge-Shaped Hot-Rolled Ti-55511 Alloy

The globularization of the lamellar α phase by thermomechanical processing and subsequent annealing contributes to achieving the well-balanced strength and plasticity of titanium alloys. A high-throughput experimental method, wedge-shaped hot-rolling, was designed to obtain samples with gradient tru...

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Main Authors: Liguo Xu, Shuangxi Shi, Bin Kong, Deng Luo, Xiaoyong Zhang, Kechao Zhou
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Materials
Subjects:
Online Access:https://www.mdpi.com/1996-1944/16/3/1031
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author Liguo Xu
Shuangxi Shi
Bin Kong
Deng Luo
Xiaoyong Zhang
Kechao Zhou
author_facet Liguo Xu
Shuangxi Shi
Bin Kong
Deng Luo
Xiaoyong Zhang
Kechao Zhou
author_sort Liguo Xu
collection DOAJ
description The globularization of the lamellar α phase by thermomechanical processing and subsequent annealing contributes to achieving the well-balanced strength and plasticity of titanium alloys. A high-throughput experimental method, wedge-shaped hot-rolling, was designed to obtain samples with gradient true strain distribution of 0~1.10. The samples with gradient strain distribution were annealed to obtain the gradient distribution of globularized α phase, which could rapidly assess the globularization fraction of α phase under different conditions. The static globularization behavior under various parameters was systematically studied. The applied prestrain provided the necessary driving force for static globularization during annealing. The substructure evolution and the boundary splitting occurred mainly at the early stage of annealing. The termination migration and the Ostwald ripening were dominant in the prolonged annealing. A backpropagation artificial neural network (BP-ANN) model for static globularization was developed, which coupled the factors of prestrain, annealing temperature, and annealing time. The average absolute relative errors (AARE) for the training and validation set are 3.17% and 3.22%, respectively. Further sensitivity analysis of the factors shows that the order of relative importance for static globularization is annealing temperature, prestrain and annealing time. The developed BP-ANN can precisely predict the static globularization kinetic curves without overfitting.
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spelling doaj.art-d3f48e45f0434c418d2c95f0c7dd13582023-11-16T17:16:09ZengMDPI AGMaterials1996-19442023-01-01163103110.3390/ma16031031Static Globularization Behavior and Artificial Neural Network Modeling during Post-Annealing of Wedge-Shaped Hot-Rolled Ti-55511 AlloyLiguo Xu0Shuangxi Shi1Bin Kong2Deng Luo3Xiaoyong Zhang4Kechao Zhou5State Key Laboratory of Powder Metallurgy, Central South University, Changsha 410083, ChinaState Key Laboratory of Powder Metallurgy, Central South University, Changsha 410083, ChinaHunan Xuangtou Goldsky Titanium Metal Co., Ltd., Changsha 410221, ChinaXiangtan Iron & Steel Group Co., Ltd., Xiangtan 411104, ChinaState Key Laboratory of Powder Metallurgy, Central South University, Changsha 410083, ChinaState Key Laboratory of Powder Metallurgy, Central South University, Changsha 410083, ChinaThe globularization of the lamellar α phase by thermomechanical processing and subsequent annealing contributes to achieving the well-balanced strength and plasticity of titanium alloys. A high-throughput experimental method, wedge-shaped hot-rolling, was designed to obtain samples with gradient true strain distribution of 0~1.10. The samples with gradient strain distribution were annealed to obtain the gradient distribution of globularized α phase, which could rapidly assess the globularization fraction of α phase under different conditions. The static globularization behavior under various parameters was systematically studied. The applied prestrain provided the necessary driving force for static globularization during annealing. The substructure evolution and the boundary splitting occurred mainly at the early stage of annealing. The termination migration and the Ostwald ripening were dominant in the prolonged annealing. A backpropagation artificial neural network (BP-ANN) model for static globularization was developed, which coupled the factors of prestrain, annealing temperature, and annealing time. The average absolute relative errors (AARE) for the training and validation set are 3.17% and 3.22%, respectively. Further sensitivity analysis of the factors shows that the order of relative importance for static globularization is annealing temperature, prestrain and annealing time. The developed BP-ANN can precisely predict the static globularization kinetic curves without overfitting.https://www.mdpi.com/1996-1944/16/3/1031Ti-55511 alloywedge-shaped hot-rollingannealingstatic globularizationartificial neural network (ANN) –
spellingShingle Liguo Xu
Shuangxi Shi
Bin Kong
Deng Luo
Xiaoyong Zhang
Kechao Zhou
Static Globularization Behavior and Artificial Neural Network Modeling during Post-Annealing of Wedge-Shaped Hot-Rolled Ti-55511 Alloy
Materials
Ti-55511 alloy
wedge-shaped hot-rolling
annealing
static globularization
artificial neural network (ANN) –
title Static Globularization Behavior and Artificial Neural Network Modeling during Post-Annealing of Wedge-Shaped Hot-Rolled Ti-55511 Alloy
title_full Static Globularization Behavior and Artificial Neural Network Modeling during Post-Annealing of Wedge-Shaped Hot-Rolled Ti-55511 Alloy
title_fullStr Static Globularization Behavior and Artificial Neural Network Modeling during Post-Annealing of Wedge-Shaped Hot-Rolled Ti-55511 Alloy
title_full_unstemmed Static Globularization Behavior and Artificial Neural Network Modeling during Post-Annealing of Wedge-Shaped Hot-Rolled Ti-55511 Alloy
title_short Static Globularization Behavior and Artificial Neural Network Modeling during Post-Annealing of Wedge-Shaped Hot-Rolled Ti-55511 Alloy
title_sort static globularization behavior and artificial neural network modeling during post annealing of wedge shaped hot rolled ti 55511 alloy
topic Ti-55511 alloy
wedge-shaped hot-rolling
annealing
static globularization
artificial neural network (ANN) –
url https://www.mdpi.com/1996-1944/16/3/1031
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