As living standards rise, more and more people are paying attention to their own health, especially issues such as cerebral thrombosis, cerebral infarction, and other cerebral blood flow problems. An accurate simulation of blood flow within cerebral vessels has emerged as a crucial area of research. In this study, we focus on microcirculatory blood flow in ischemic brain tissue and employ a 0D-1D geometric multi-scale coupled model to characterize this process. Given the intricate nature of human cerebral vessels, we apply a numerical method combining the finite element method and the third-order Runge-Kutta method to resolve the coupled model. To enhance computational efficiency, we introduce a fast method based on the reduced-order extrapolation algorithm. Our numerical example underscores the stability of the method and convergence accuracy to , while significantly improving the accuracy and efficiency of blood flow simulation, making the mechanism analysis more accurate. Additionally, we present examples detailing variations and distribution of intracranial pressure and blood flow in ischemic brain tissue throughout a cardiac cycle. Both reduced vascular compliance and vascular stenosis can have adverse effects on intracranial cerebral pressure and blood flow, leading to insufficient local oxygen supply and negative effects on brain function. Meanwhile, there will also be corresponding changes in volume flow and pulsatile blood pressure.
Keywords: Runge–Kutta method; fast method; finite element method; geometric multi‐scale coupled model; ischemic cerebral tissue blood flow.
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