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arXiv 2402.04766physics.flu-dynmath.OC
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利用数据同化确定Navier滑移参数

Determination of Navier's slip parameter using data assimilation

Alena Jarolímová, Jaroslav Hron

AI总结:

针对患者特异性血流模拟中Navier滑移参数确定困难的问题,提出并测试了一种基于最优控制的方法,利用人工数据估计滑移参数和入口速度剖面,结果表明即使数据含噪声也能通过精确离散化恢复参数和流动模式。

摘要:

患者特异性血流模拟的关键方面之一是指定材料参数和边界条件。边界条件的选择会对流动特性产生重大影响。虽然无滑移是最常用的壁面边界条件,但一定程度的滑移(决定了允许多少流体沿壁面流动)可能有助于更好地与医学图像中的流动模式达成一致。然而,即使假设壁面采用简单的Navier边界条件(其中法向牵引力的切向分量与速度之间呈线性关系),滑移参数具体值的确定通常也很困难。在这项工作中,我们提出并测试了一种最优控制方法,利用人工生成的流动域和流动数据来估计壁面的Navier滑移参数和入口处的速度剖面。结果表明,即使从包含大量噪声的数据中,通过足够精确的离散化,也可以恢复流动模式和Navier滑移参数。

英文摘要:

One of the crucial aspects of patient-specific blood flow simulations is to specify material parameters and boundary conditions. The choice of boundary conditions can have a substantial impact on the character of the flow. While no-slip is the most popular wall boundary condition, some amount of slip, which determines how much fluid is allowed to flow along the wall, might be beneficial for better agreement with flow patterns in medical images. However, even if one assumes the simple Navier's boundary conditions on the wall, in which the relationship between tangential components of the normal traction and the velocity is linear, the determination of the specific value of the slip parameter is often difficult. In this work, we present and test an optimal control method to estimate Navier's slip parameter on the wall and the velocity profile at the inlet using artificially generated flow domain and flow data. The results show that it is possible to recover the flow patterns and Navier's slip parameter by using sufficiently accurate discretization even from data containing a substantial amount of noise.

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