COMPUTATIONAL MECHANICS FOR SOFT BIOLOGICAL TISSUES

2023-1-17
Altun, Cem
Computational biomechanics is an active research area, not only to understand the mechanisms behind the behaviours of biological tissues but also to develop medical techniques for surgeries, rehabilitations, and diseases. The thesis mainly composed of two parts namely, growth-induced instabilities and dispersion-type anisotropic viscoelasticity for soft biological tissues. In the first part of the thesis, planar growth-induced instabilities for a three-dimensional bilayer-type confined tissue is examined. Firstly, a five-field Hu-Washizu type mixed variational formulation for incompressible and inextensible limits is extended for finite growth theory that captures the primary and secondary growth-induced instabilities for anisotropic soft biological tissues. A numerical example is solved by implementing T2P0F0 element on the automated differential equation solver, FEniCS. The influence of fiber stiffness on the critical growth parameter, primary and secondary buckling is investigated. The numerical outcomes of this study will help to understand the fiber stiffness effect on the buckling and post-buckling behavior of bilayer-typed anisotropic soft biological tissues. In the second part of thesis, we proposed five novel formulations for angular-integration based dispersion-type anisotropic viscoelastic constitutive models at finite strains where the formulations use bivariate and planar von Mises density distribution functions. Then, a numerical model validation is conducted for the human myocardium. The proposed models use the generalized structure tensor for the baseline hyperelastic mechanical response to reflect the dispersion characteristics along the fiber and sheet directions of the myocardium. A quadratic free-energy function is defined for the viscous response that is mainly composed of logarithmic elastic and microviscous strains. The density distribution function is introduced in the constitutive equations by defining two types of formulations, namely, local-based and global-based. In the local-based formulations, we use the density distribution as a part of the micro-viscous free-energy functions. In the global-based formulations, the density distribution function enters the equations during the continuous averaging of the stress and tangent moduli expressions. For the five of proposed models, the overstress response has been identified through either nonlinear or linear evolution laws in each orientation direction by using numerical integration, either over the unit micro-sphere or over the unit planar circle. Then, the fitting performances of the proposed models are examined and compared with the cyclic triaxial shear and triaxial shear relaxation experiments of human passive myocardium from the literature. All models are compared, and their pros and cons are discussed. While local-based formulations suffer from the violation of the normalization condition during the averaging integral stage when the nonlinear evolution is used, the global-based formulations are stable and provide high accuracy for both linear and nonlinear evolutions with a sufficient number of integration points. The proposed formulations provide a histological-based flexible calibration capability for any type of anisotropic soft biological tissue that exhibits either elastic or viscous response.

Suggestions

Computational modeling of coupled cardiac electromechanics incorporating cardiac dysfunctions
Berberoglu, Ezgi; Solmaz, H. Onur; Göktepe, Serdar (Elsevier BV, 2014-11-01)
Computational models have huge potential to improve our understanding of the coupled biological, electrical, and mechanical underpinning mechanisms of cardiac function and diseases. This contribution is concerned with the computational modeling of different cardiac dysfunctions related to the excitation-contraction coupling in the heart. To this end, the coupled problem of cardiac electromechanics is formulated through the conservation of linear momentum equation and the excitation equation formulated in th...
Computational modeling of cardiac tissue with strongly coupled electromechanics and orthotropic viscoelastic effects
Cansiz, Baris; Dal, Hüsnü; Kaliske, Michael (2014-03-14)
Modeling of complex mechanisms leading to the functioning of the heart has been an active field of research since decades. Difficulties associated with in vivo experiments motivate the utilization of computational models in order to gain a better appreciation of heart electromechanics. Although rate dependent behaviour of the orthotropic passive heart tissue has been comprehensively studied in the literature [1], effects of this phenomenon on fully coupled cardiac electromechanics are unrevealed yet. Theref...
Computational modeling of growth: systemic and pulmonary hypertension in the heart
Rausch, M. K.; Dam, A.; Göktepe, Serdar; Abilez, O. J.; Kuhl, E. (2011-12-01)
We introduce a novel constitutive model for growing soft biological tissue and study its performance in two characteristic cases of mechanically induced wall thickening of the heart. We adopt the concept of an incompatible growth configuration introducing the multiplicative decomposition of the deformation gradient into an elastic and a growth part. The key feature of the model is the definition of the evolution equation for the growth tensor which we motivate by pressure-overload-induced sarcomerogenesis. ...
Computational approaches leveraging integrated connections of multi-omic data toward clinical applications
Demirel, Habibe Cansu; Tunçbağ, Nurcan (2021-10-01)
In line with the advances in high-throughput technologies, multiple omic datasets have accumulated to study biological systems and diseases coherently. No single omics data type is capable of fully representing cellular activity. The complexity of the biological processes arises from the interactions between omic entities such as genes, proteins, and metabolites. Therefore, multi-omic data integration is crucial but challenging. The impact of the molecular alterations in multi-omic data is not local in the ...
Numerical aspects of anisotropic failure in soft biological tissues favor energy-based criteria: A rate-dependent anisotropic crack phase-field model
Gueltekin, Osman; Dal, Hüsnü; Holzapfel, Gerhard A. (2018-04-01)
A deeper understanding to predict fracture in soft biological tissues is of crucial importance to better guide and improve medical monitoring, planning of surgical interventions and risk assessment of diseases such as aortic dissection, aneurysms, atherosclerosis and tears in tendons and ligaments. In our previous contribution (Gultekin et al., 2016) we have addressed the rupture of aortic tissue by applying a holistic geometrical approach to fracture, namely the crack phase-field approach emanating from va...
Citation Formats
C. Altun, “COMPUTATIONAL MECHANICS FOR SOFT BIOLOGICAL TISSUES,” Ph.D. - Doctoral Program, Middle East Technical University, 2023.