دانلود مقاله ISI انگلیسی شماره 79003
ترجمه فارسی عنوان مقاله

یک الگوریتم سریع برای تحریک امواج پالس شریانی.

عنوان انگلیسی
A fast algorithm for the simulation of arterial pulse waves
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
79003 2016 15 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Computational Physics, Volume 314, 1 June 2016, Pages 450–464

ترجمه کلمات کلیدی
موج نبض خون؛ متغیرهای ریمان؛ روش Wendroff لکس؛ سرعت موج بزرگ؛ الگوریتم سریع
کلمات کلیدی انگلیسی
Blood pulse wave; Riemann variables; Lax–Wendroff method; Large wave speed; Fast algorithm
پیش نمایش مقاله
پیش نمایش مقاله  یک الگوریتم سریع برای تحریک امواج پالس شریانی.

چکیده انگلیسی

One-dimensional models have been widely used in studies of the propagation of blood pulse waves in large arterial trees. Under a periodic driving of the heartbeat, traditional numerical methods, such as the Lax–Wendroff method, are employed to obtain asymptotic periodic solutions at large times. However, these methods are severely constrained by the CFL condition due to large pulse wave speed. In this work, we develop a new numerical algorithm to overcome this constraint. First, we reformulate the model system of pulse wave propagation using a set of Riemann variables and derive a new form of boundary conditions at the inlet, the outlets, and the bifurcation points of the arterial tree. The new form of the boundary conditions enables us to design a convergent iterative method to enforce the boundary conditions. Then, after exchanging the spatial and temporal coordinates of the model system, we apply the Lax–Wendroff method in the exchanged coordinate system, which turns the large pulse wave speed from a liability to a benefit, to solve the wave equation in each artery of the model arterial system. Our numerical studies show that our new algorithm is stable and can perform ∼15 times faster than the traditional implementation of the Lax–Wendroff method under the requirement that the relative numerical error of blood pressure be smaller than one percent, which is much smaller than the modeling error.