基于多组分非牛顿流体混合模型的血流模拟

Simulation of blood flow based on a multicomponent non-Newtonian fluid mixing model

  • 摘要: 可视化人体内血液流动特性对精准诊断心血管疾病、解析病理机制及优化治疗方案至关重要。然而,传统医疗手段难以直接观测血液流动状态,且对血液成分耦合效应的量化评估不足。为此,本文提出一种基于多组分非牛顿流体混合模型的血流模拟方法。首先,基于Walburn-Schneck模型描述非牛顿流体表观粘度;其次,通过引入体积分数,将Walburn-Schneck粘度模型拓展至多组分应用场景,准确模拟了不同组分间的交互作用机制,实现了多组分非牛顿流体延展和流动效果的准确模拟;最后,构建血管壁处固-液作用力模型,采用改进的光滑粒子流体动力学方法对壁面剪应力和粘附力进行建模,修正了壁面附近粒子截断对流固边界附近流体模拟的计算误差。实验结果表明,本文方法可有效捕捉非牛顿流体的剪切速率依赖性及多组分混合扩散行为,较传统模型能更真实地还原复杂血管结构中的血液流动状态。研究成果为数智化诊疗提供了新的技术路径,有望辅助深化理解血流动力学异常相关病理机制。

     

    Abstract: Visualization the characteristics of blood flow in the human body is essential for accurate diagnosis of cardiovascular diseases, analysis of pathological mechanisms and optimization of treatment options. However, traditional medical methods struggle to directly observe blood flow states and the quantitative assessment of the coupling effect of blood components is insufficient. In this paper, we propose a blood flow simulation method based on a multi-component non-Newtonian fluid mixing model. Firstly, the Walburn-Schneck model is employed to describe the viscosity of non-Newtonian fluids; secondly, by introducing volume fractions, the Walburn-Schneck model is extended to multi-component application scenarios, which accurately simulates the interaction mechanism between different components and achieves the accurate extension and flow effects simulation of multi-component non-Newtonian fluids; finally, a solid-liquid interaction force model at the blood vessel wall is constructed, and the improved solid-liquid interaction force model is used. Finally, the solid-liquid force model is constructed at the vessel wall, and an improved smoothed particle hydrodynamics (SPH) method is used to model wall shear stress and adhesive forces, correcting calculation errors in fluid simulation near the fluid-solid boundary caused by particle truncation. The experimental results show that the method can effectively capture the shear rate dependence of non-Newtonian fluids and the mixing-diffusion behavior of multi-components, restoring blood flow states in complex vascular structures better than traditional models. The research results provide a new technical pathway for digital and intelligent medical diagnosis, holding promise to assist in deepening the understanding of pathological mechanisms related to hemodynamic abnormalities.

     

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