Stokes flows in a two-dimensional bifurcation

被引:0
|
作者
Xue, Yidan [1 ,2 ,3 ]
Payne, Stephen J. [4 ]
Waters, Sarah L. [1 ]
机构
[1] Univ Oxford, Math Inst, Oxford, England
[2] Cardiff Univ, Sch Math, Cardiff, Wales
[3] Univ Manchester, Sch Hlth Sci, Manchester, England
[4] Natl Taiwan Univ, Inst Appl Mech, Taipei, Taiwan
来源
ROYAL SOCIETY OPEN SCIENCE | 2025年 / 12卷 / 01期
基金
英国工程与自然科学研究理事会;
关键词
Stokes flow; flow network; bifurcation; lightning solver; biharmonic equation; TISSUE; PHYSICS; MODEL;
D O I
10.1098/rsos.241392
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The flow network model is an established approach to approximate pressure-flow relationships in a bifurcating network, and has been widely used in many contexts. Existing models typically assume unidirectional flow and exploit Poiseuille's law, and thus neglect the impact of bifurcation geometry and finite-sized objects on the flow. We determine the impact of bifurcation geometry and objects by computing Stokes flows in a two-dimensional (2D) bifurcation using the Lightning-AAA Rational Stokes algorithm, a novel mesh-free algorithm for solving 2D Stokes flow problems utilizing an applied complex analysis approach based on rational approximation of the Goursat functions. We compute the flow conductances of bifurcations with different channel widths, bifurcation angles, curved boundary geometries and fixed circular objects. We quantify the difference between the computed conductances and their Poiseuille law approximations to demonstrate the importance of incorporating detailed bifurcation geometry into existing flow network models. We parametrize the flow conductances of 2D bifurcation as functions of the dimensionless parameters of bifurcation geometry and a fixed object using a machine learning approach, which is simple to use and provides more accurate approximations than Poiseuille's law. Finally, the details of the 2D Stokes flows in bifurcations are presented.
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页数:18
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