Date of Award
2016
Document Type
Open Access Dissertation
Department
Mechanical Engineering
Sub-Department
College of Engineering and Computing
First Advisor
Xiaomin Deng
Abstract
Arterial tissue failure leads to a number of potentially life-threatening clinical conditions, such as atherosclerotic plaque rupture and aortic dissection which develop unpredictably and rapidly in vivo. Thus, a full understanding of the two conditions will provide a solid basis for medical advances in the intervention and prevention of the occurrence of this life-threatening event. The present work aims to develop a cohesive zone model (CZM) approach for analysis and simulation of arterial tissue failure, such as plaque and fibrous cap delamination and tearing, and to validate simulation predictions with experimental results.
To characterize the hysteresis phenomenon of diseased aortic tissue, a viscoelastic anisotropic (VA) model for the bulk arterial material behavior is proposed based on a hyperelastic anisotropic model and a general viscoelastic formulation in the literature. The viscoelastic effects of the material are taken into account by using a generalized Maxwell model. In order to capture the failure process of the interface between arterial layers, three types of cohesive zone models were considered, which include the exponential, triangular and trapezoidal CZMs.
Atherosclerotic plaque delamination experiments performed on ApoE-KO mouse aorta specimens were simulated using the CZM approach. A three-dimensional (3D) finite element model for the experiments was developed, in which the Holzapfel-Gasser-Ogden(HGO) model for the bulk arterial material behavior and a CZM for the plaque-media interface behavior are adopted. A set of HGO and CZM parameter values were obtained through a material parameter identification procedure in which a subset of experimental loading-delamination-unloading cycle data was used. Simulation predictions for additional loading-delamination-unloading cycles were obtained, which show good agreement with experimental measurements.
Two types of delamination experiments (a “mixed-mode” type and a “mode I” type) were conducted on porcine aorta specimens. These experiments were analyzed and compared using finite element simulations. Simulation results revealed that the intuitive classification of these two types of experiments is not necessarily accurate for soft tissue materials. In particular, the “mixed-mode” experiment was found to have a dominant mode II component in the cohesive zone ahead of the growing delamination front.
Human fibrous cap delamination experiments were conducted and simulated using the finite element method by employing the VA bulk material model and three types of CZMs. A set of VA and CZM parameter values was determined using the same material parameter identification procedure as in the simulations of mouse plaque delamination experiments. Using this set of parameter values, simulation predictions for two sequential loading-delamination-unloading cycles were performed, which show good agreement with experimental measurements, including the hysteresis behavior during unloading. Furthermore, a mode I tearing test was conducted on human fibrous cap in order to investigate the failure process of plaque rupture. The CZM parameter values were obtained through an inverse analysis. These parameter values will provide input for further numerical simulation of plaque rupture events.
The CZM based approach was applied to develop a micromechanical model for arterial delamination along the interface between the fibrous cap and the underlying plaque tissue in order to understand delamination mechanisms, including fiber bridging. A 3D unit cell containing an individual fiber between two arterial tissue layers was considered. With the unit cell model, micromechanical factors affecting the resulting traction-separation relation were investigated through a parametric study.
Rights
© 2016, Xiaochang Leng
Recommended Citation
Leng, X.(2016). Numerical Studies Of Arterial Tissue Failure. (Doctoral dissertation). Retrieved from https://scholarcommons.sc.edu/etd/3752