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Stretching skin: The physiological limit and beyond

机译:伸展皮肤:生理极限和超越极限

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The goal of this paper is to establish a novel computational model for skin to characterize its constitutive behavior when stretched within and beyond its physiological limits. Within the physiological regime, skin displays a reversible, highly non-linear, stretch locking, and anisotropic behavior. We model these characteristics using a transversely isotropic chain network model composed of eight wormlike chains. Beyond the physiological limit, skin undergoes an irreversible area growth triggered through mechanical stretch. We model skin growth as a transversely isotropic process characterized through a single internal variable, the scalar-valued growth multiplier. To discretize the evolution of growth in time, we apply an unconditionally stable, implicit Euler backward scheme. To discretize it in space, we utilize the finite element method. For maximum algorithmic efficiency and optimal convergence, we suggest an inner Newton iteration to locally update the growth multiplier at each integration point. This iteration is embedded within an outer Newton iteration to globally update the deformation at each finite element node. To illustrate the characteristic features of skin growth, we first compare the two simple model problems of displacement- and force-driven growth. Then, we model the process of stretch-induced skin growth during tissue expansion. In particular, we compare the spatio-temporal evolution of stress, strain, and area gain for four commonly available tissue expander geometries. We believe that the proposed model has the potential to open new avenues in reconstructive surgery and rationalize critical process parameters in tissue expansion, such as expander geometry, expander size, expander placement, and inflation timing.
机译:本文的目的是建立一种新颖的皮肤计算模型,以描述其在生理极限范围之内和之外伸展时的本构行为。在生理范围内,皮肤表现出可逆的,高度非线性的,拉伸锁定和各向异性行为。我们使用由八个蠕虫状链组成的横向各向同性链网络模型对这些特征进行建模。超出生理极限,皮肤会经历由机械拉伸触发的不可逆的区域生长。我们将皮肤生长建模为一个横向各向同性的过程,该过程以单个内部变量(标量值增长乘数)为特征。为了离散化时间增长的演化,我们应用了无条件稳定的隐式Euler向后方案。为了使它在空间离散,我们利用有限元方法。为了获得最大的算法效率和最佳收敛性,我们建议进行内部牛顿迭代以在每个集成点局部更新增长乘数。该迭代被嵌入外部的Newton迭代中,以全局更新每个有限元节点处的变形。为了说明皮肤生长的特征,我们首先比较位移驱动和力驱动生长的两个简单模型问题。然后,我们对组织扩展过程中拉伸诱导的皮肤生长过程进行建模。特别是,我们比较了四种常见组织扩张器几何结构的应力,应变和面积增益的时空演变。我们认为,提出的模型有可能在重建手术中开辟新的途径,并使组织扩张中的关键过程参数合理化,例如扩张器的几何形状,扩张器的尺寸,扩张器的位置和充气时机。

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