如何洞察生命“内流场”？ 陕西一高校团队精准量化血液流变

Core Viewpoint - The research conducted by the team at Northwestern Polytechnical University aims to establish a unified computational physics evaluation system for blood rheology, addressing the complexities of non-Newtonian fluid behavior in blood flow simulations, which is crucial for cardiovascular disease diagnosis and thrombus risk prediction [3][6]. Group 1: Non-Newtonian Fluid Characteristics - Non-Newtonian fluids exhibit different behaviors under varying forces; for instance, they can behave like solids under high shear rates and like liquids under low shear rates, a phenomenon known as "shear thickening" [1]. - Blood, as a non-Newtonian fluid, demonstrates "shear thinning" behavior, where its viscosity decreases with increased flow rate, facilitating smooth circulation in blood vessels [1]. Group 2: Research Contributions - The study systematically reviews 140 core research findings since 1919 to create a comprehensive evaluation system that includes characteristics such as shear thinning, viscoelasticity, and yield stress, providing a reference for researchers in selecting computational models [3][6]. - The research identifies a scientific boundary for the non-Newtonian characteristics of blood, indicating that above a certain threshold, blood behaves like a Newtonian fluid, while below it, particularly in areas like aneurysms or narrowed vessels, it exhibits significant non-Newtonian properties [6]. Group 3: Computational Methods - The research evaluates different computational approaches for simulating blood flow, including the bidirectional fluid-structure interaction (FSI) methods and the arbitrary Lagrangian-Eulerian (ALE) method, highlighting the challenges of mesh reconfiguration in large deformation scenarios [7]. - To overcome computational limitations, the study introduces the Smoothed Particle Hydrodynamics (SPH) method, which avoids mesh distortion and enhances flexibility in handling large deformations, thus improving the accuracy of multi-phase physical interface tracking [7]. Group 4: Implications for Medical Applications - The findings provide a theoretical foundation for constructing high-precision patient-specific models, which can significantly advance precision medicine by enabling more accurate simulations of blood flow and vessel behavior in clinical settings [7].