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Computational modeling of growth

机译:增长的计算模型

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The present contribution is dedicated to the computational modeling of growth phenomena typically encountered in modern biomechanical applications. We set the basis by critically reviewing the relevant literature and classifying the existing models. Next, we introduce a geometrically exact continuum model of growth which is not a priori restricted to applications in hard tissue biomechanics. The initial boundary value problem of biomechanics is primarily governed by the density and the deformation problem which render a nonlinear coupled system of equations in terms of the balance of mass and momentum. To ensure unconditional stability of the required time integration procedure, we apply the classical implicit Euler backward method. For the spatial discretization, we suggest two alternative strategies, a node-based and an integration point–based approach. While for the former, the discrete balance of mass and momentum are solved simultaneously on the global level, the latter is typically related to a staggered solution with the density treated as internal variable. The resulting algorithms of the alternative solution techniques are compared in terms of stability, uniqueness, efficiency and robustness. To illustrate their basic features, we elaborate two academic model problems and a typical benchmark example from the field of biomechanics.
机译:本贡献致力于现代生物力学应用中通常遇到的生长现象的计算模型。我们通过严格审查相关文献并对现有模型进行分类来奠定基础。接下来,我们介绍一个几何精确的连续增长模型,该模型并不先验地限于硬组织生物力学中的应用。生物力学的初始边界值问题主要受密度和变形问题支配,这些问题使质量和动量平衡成为方程式的非线性耦合系统。为了确保所需时间积分过程的无条件稳定性,我们应用了经典的隐式Euler向后方法。对于空间离散化,我们建议两种替代策略,一种基于节点的方法和一种基于积分点的方法。对于前者,质量和动量的离散平衡是在全局水平上同时解决的,而后者通常与将密度视为内部变量的交错解有关。比较了替代解决方案技术的结果算法在稳定性,唯一性,效率和鲁棒性方面。为了说明它们的基本特征,我们从生物力学领域阐述了两个学术模型问题和一个典型的基准示例。

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