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基于非匹配浸入方法的血管组织多尺度建模。

Multiscale modeling of vascularized tissues via nonmatching immersed methods.

机构信息

Mathematical Modeling and Scientific Computing Lab, International School for Advanced Studies, Trieste, Italy.

Numerical Mathematics and Scientific Computing Group, Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany.

出版信息

Int J Numer Method Biomed Eng. 2019 Dec;35(12):e3264. doi: 10.1002/cnm.3264. Epub 2019 Dec 1.

Abstract

We consider a multiscale approach based on immersed methods for the efficient computational modeling of tissues composed of an elastic matrix (in two or three dimensions) and a thin vascular structure (treated as a co-dimension two manifold) at a given pressure. We derive different variational formulations of the coupled problem, in which the effect of the vasculature can be surrogated in the elasticity equations via singular or hypersingular forcing terms. These terms only depend on information defined on co-dimension two manifolds (such as vessel center line, cross-sectional area, and mean pressure over cross section), thus drastically reducing the complexity of the computational model. We perform several numerical tests, ranging from simple cases with known exact solutions to the modeling of materials with random distributions of vessels. In the latter case, we use our immersed method to perform an in silico characterization of the mechanical properties of the effective biphasic material tissue via statistical simulations.

摘要

我们考虑了一种基于浸入方法的多尺度方法,用于高效地计算建模由弹性基质(二维或三维)和给定压力下的薄血管结构(视为二维协维流形)组成的组织。我们推导出耦合问题的不同变分公式,其中血管的影响可以通过奇异或超奇异强迫项在弹性方程中替代。这些项仅依赖于协维二面流形上定义的信息(例如血管中心线、横截面积和横截面上的平均压力),从而大大降低了计算模型的复杂性。我们进行了几次数值测试,范围从具有已知精确解的简单情况到具有随机血管分布的材料建模。在后一种情况下,我们使用浸入方法通过统计模拟对有效两相材料组织的机械性能进行计算机表征。

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