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A generalized optimization principle for asymmetric branching in fluidic networks

机译:流体网络非对称分支的广义优化原理

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摘要

When applied to a branching network, Murray’s law states that the optimal branching of vascular networks is achieved when the cube of the parent channel radius is equal to the sum of the cubes of the daughter channel radii. It is considered integral to understanding biological networks and for the biomimetic design of artificial fluidic systems. However, despite its ubiquity, we demonstrate that Murray’s law is only optimal (i.e. maximizes flow conductance per unit volume) for symmetric branching, where the local optimization of each individual channel corresponds to the global optimum of the network as a whole. In this paper, we present a generalized law that is valid for asymmetric branching, for any cross-sectional shape, and for a range of fluidic models. We verify our analytical solutions with the numerical optimization of a bifurcating fluidic network for the examples of laminar, turbulent and non-Newtonian fluid flows.
机译:当应用于分支网络时,穆雷定律指出,当父通道半径的立方等于子通道半径的立方之和时,可以实现最佳的血管网络分支。它被认为是理解生物学网络和人工流体系统的仿生设计必不可少的。但是,尽管它无处不在,但我们证明,对于对称分支,穆雷定律仅是最优的(即,使每单位体积的流导最大化),其中每个单个通道的局部优化对应于整个网络的全局最优。在本文中,我们提出了适用于非对称分支,任何横截面形状以及一系列流体模型的通用定律。我们以分叉流体网络的数值优化为层流,湍流和非牛顿流体流动的实例来验证我们的分析解决方案。

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