Visco-hyperelastic constitutive modeling of soft tissues based on short and long-term internal variables
BioMedical Engineering OnLine
Background Differential-type and integral-type formulations are two common approaches in modeling viscoelastic materials. A differential-type theory is often derived from a Helmholtz free energy function and is usually more suitable for the prediction of strain-rate dependent mechanical behavior during rapid loading, while an integral-type theory usually captures stress relaxation more efficiently than a differential-type theory. A modeling approach is needed to predict the viscoelastic responses during both rapid loading and relaxation phases. Methods A constitutive modeling methodology based on the short and long-term internal variables was proposed in the present study in order to fully use the better features of the two types of theories. The short-term variables described the loading rate, while the long-term variables involving time constants characterized loading history and stress relaxation. Results The application of the methodology was demonstrated with particular formulations for ligament and articular cartilage. Model parameters were calibrated for both tissues with experimental data from the literature. It was found that the proposed model could well predict a wide range of strain-rate dependent load responses during both loading and relaxation phases. Conclusion Introducing different internal variables in terms of their time scales reduced the difficulties in the material characterization process and enabled the model to predict the experimental data more accurately, in particular at high strain-rates.
Publisher version of article deposited according to publisher policy posted on BioMed Central, May 13, 2015. http://www.biomedcentral.com/authors/license
Articular cartilage, Constitutive modeling, Ligament, Strain-rate sensitivity, Viscoelasticity
Ahsanizadeh, S., & Li, L. (2015). Visco-hyperelastic constitutive modeling of soft tissues based on short and long-term internal variables. Biomedical Engineering Online, 14(1), 29. http://doi.org/10.1186/s12938-015-0023-7