%0 Generic %A Brinkmann, Felix %C Heidelberg %D 2020 %F heidok:28136 %K embryonic pattern formation; hydra aggregates; colonial hydroids; predictive numerical experiments; mechanochemical pattern formation; biophysical simulations; deformation gradient decomposition; gascoigne; %R 10.11588/heidok.00028136 %T Mathematical models and numerical simulation of mechanochemical pattern formation in biological tissues %U https://archiv.ub.uni-heidelberg.de/volltextserver/28136/ %X Mechanical and chemical pattern formation in the development of biological tissue is a fundamental and fascinating process of self-complexation and self-organization. Yet, the understanding of the underlying mechanisms and their mathematical description still lacks in many interesting cases such as embryogenesis. In this thesis, we combine recent experimental and theoretical insights and numerically investigate the capacity of mechano-chemical processes to spontaneously generate patterns in biological tissue. Firstly, we develop and numerically analyze a prototypical system of partial differential equations (PDEs) leading to mechanochemical pattern formation in evolving tissues. Based on recent experimental data, we propose a novel coupling by tensor invariants describing stretch, stress or strain of tissue mechanics on the production of signaling molecules (morphogens). In turn, morphogen leads to piecewise-defined active deformations of individual biological cells. The presented approach is flexible and applied to two prominent examples of evolving tissue: We show how these simple interaction rules (“feedback loops”) lead to spontaneous, robust mechanochemical patterns in the applications to embryogenesis and to symmetry breaking in the sweet water polyp Hydra. Our results reveal that the full 3D model geometry is essential to obtain realistic results such as gastrulation events. Also, we highlight predictive numerical experiments that assess the sensitivity of biological tissue with regard to mechanical stimuli, namely to micropipette aspiration. These numerical experiments allow for a cross-validation with experimental observations. Besides, we apply our modeling approach to growing tips in colonial hydroids and investigate the role of rotational and shearing active deformations by comparison to experimental data. Secondly, we develop an efficient, numerical method to reliably solve these strongly coupled, prototypical systems of PDEs that model mechanochemical long-term problems. We employ state-of-the-art finite element methods, parallel geometric multigrid solvers and present a simple, local mesh refinement strategy to obtain an efficient solution approach. Parallel solvers are essential to deal with the huge problem size in 3D and were modified to keep track of biological cells. Further, we propose a stabilization of the structural equation to deal with the strongly coupled system of equations and the challenges of the different timescales of growth (days) and nonlinear elasticity (seconds). Also, this addresses the instabilities which result form the description of homogeneous Neumann values on the entire boundary that is necessary since the locations of patterns is a priori unknown.