@Article{cmes.2026.080866,
AUTHOR = {Teng Long, Leyu Wang, James D. Lee, Cing-Dao Kan},
TITLE = {Computer Modeling and Characterization of Plastic Strain Hardening in Ti-6Al-4V under Tension and Compression},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {},
YEAR = {},
NUMBER = {},
PAGES = {{pages}},
URL = {http://www.techscience.com/CMES/online/detail/27282},
ISSN = {1526-1506},
ABSTRACT = {Titanium alloy Ti-6Al-4V has been widely applied in many industries, for example, aerospace, marine, automotive, and biomedical engineering systems, where accurate characterization of plastic deformation is important for evaluating material performance and potential failure under severe loading conditions. This material shows nonlinear plasticity and tension–compression asymmetry, which makes the strain hardening characterization important for computational failure analysis and crashworthiness-related simulations. However, conventional strain hardening models and parameter identification methods often rely on linear or extrapolation-based assumptions and are sensitive to initial guesses due to the non-convex nature of the optimization problem. In this study, a flexible rational-polynomial-based strain-hardening model was employed to characterize the stress–strain responses of Ti-6Al-4V under both tensile and compressive loading. To identify the polynomial parameters, an online hyperparameter tuning Bayesian optimization framework was adopted. The finite element predictions closely reproduce the experimental force–displacement responses under both tensile and compressive loading. This consistency demonstrates the capability of the proposed data-driven computational framework to identify strain-hardening parameters and characterize the plastic deformation behavior of Ti-6Al-4V alloy.},
DOI = {10.32604/cmes.2026.080866}
}