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  • Title: Time and depth dependent Poisson's ratio of cartilage explained by an inhomogeneous orthotropic fiber embedded biphasic model.
    Author: Chegini S, Ferguson SJ.
    Journal: J Biomech; 2010 Jun 18; 43(9):1660-6. PubMed ID: 20392445.
    Abstract:
    A time- and depth-dependent Poisson's ratio has been observed during unconfined compression experiments on articular cartilage, but existing cartilage models have not fully addressed these phenomena. The goal of this study was to develop a model which is able to predict and explain these phenomena, while also being able to fit other experimental scenarios on full depth cartilage specimens such as confined and unconfined compressions. A biphasic (poroelastic), fiber-embedded cartilage model was developed. The heterogeneous material properties of the cartilage (aggregate modulus, void ratio tensile modulus) were extracted from reported experiments on individual layers of bovine articular cartilage. The nonlinear permeability material constants were found by fitting the overall response to published experimental data from confined compression. The matrix of the cartilage was modelled as an inhomogeneous isotropic biphasic material with nonlinear strain dependent permeability. Orthotropic layers were added as embedded elements to represent collagen fibers. Material parameters for these layers were derived from tensile tests of different layers of cartilage. With these predefined tensile parameters, the model showed a good fit with multi-step confined and unconfined compression experiments (R(2)=0.984 and 0.977, respectively) and could also predict the depth-dependent Poisson's ratio (R(2)=0.981). The highlight of the model is the ability to explain the time-depth dependent Poisson's ratio and, by association, the strong effect of material inhomogeneity on local stress and strain patterns within the cartilage layer. This material model's response may provide valuable new insight into potential initiation of cartilage fibrillation or delamination in whole-joint simulations.
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