4.6 Article

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

期刊

MATERIALS
卷 16, 期 3, 页码 -

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MDPI
DOI: 10.3390/ma16031031

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Ti-55511 alloy; wedge-shaped hot-rolling; annealing; static globularization; artificial neural network (ANN) -

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The globularization of the lamellar alpha phase is achieved through thermomechanical processing and subsequent annealing, resulting in a well-balanced strength and plasticity of titanium alloys. A high-throughput experimental method called wedge-shaped hot-rolling is developed to obtain samples with gradient true strain distribution. The samples are annealed to obtain the gradient distribution of globularized alpha phase, and the static globularization behavior under various parameters is systematically studied.
The globularization of the lamellar alpha 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 similar to 1.10. The samples with gradient strain distribution were annealed to obtain the gradient distribution of globularized alpha phase, which could rapidly assess the globularization fraction of alpha 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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