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This study uses the Anand constitutive model to predict how commercially pure Grade 2 titanium behaves during thermoplastic deformation, with the goal of making it more suitable for load-bearing medical implants. Although titanium alloys like Ti6Al4V are commonly used in implants, there are concerns about the release of toxic ions, which encourages the search for safer options like pure titanium. To strengthen pure titanium, this research focuses on thermo-mechanical processing (TMP). The study combines experimental compression tests (conducted at 400–600°C and strain rates of 0.01–1.0 s-1) with computer simulations based on the Anand model. The model can describe important material behaviours such as strain hardening, dynamic recovery, and sensitivity to temperature and strain rate. Originally developed for soft metals, the Anand model was successfully adapted to pure titanium and showed high accuracy in predicting material behaviour at elevated temperatures and moderate strain rates. Some prediction errors at 400°C were likely due to incomplete dynamic recrystallisation. The best fit of our model to the experimental results was achieved for the temperature 600°C and strain rate 0.01 s-1 with adjusted R-square equal 0.988 and root mean square error equal 3.941. The model was further tested under specific conditions (450°C, 550°C, strain rate of 0.5 s-1) and achieved flow stress prediction errors below 8%. In summary, this work provides a reliable and efficient tool for optimizing TMP processes, reducing the need for costly trial-and-error methods, and supporting the production of patient-specific implants made from pure titanium.
Słowa kluczowe
Wydawca
Rocznik
Tom
Strony
504--515
Opis fizyczny
Bibliogr. 45 poz., fig., tab.
Twórcy
autor
- Faculty of Mechanical and Industrial Engineering, Warsaw University of Technology, Narbutta 85, 02-524 Warsaw, Poland
autor
- Faculty of Mechanical and Industrial Engineering, Warsaw University of Technology, Narbutta 85, 02-524 Warsaw, Poland
Bibliografia
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-eeed8cd7-09c9-4f42-bd82-bf654c7cc7a8
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