标题： 用于冠状动脉旁路移植物参数化最优流动控制的降阶方法，面向患者特定的数据同化 显示英文标题

标题： Reduced order methods for parametric optimal flow control in coronary bypass grafts, towards patient-specific data assimilation

摘要： 冠状动脉旁路移植术（CABG）是一种侵入性手术，用于绕过冠状动脉疾病（CAD）中部分或完全的血流阻塞。 在本工作中，我们将数值最优流动控制模型应用于从真实手术案例的临床图像中重建的患者特定几何结构，在参数化设置中进行研究。 这些应用的目的是将已知的生理数据与对应于不同场景的数值血液动力学结果相匹配，这些场景是通过调整某些参数产生的。 此类应用是尽可能在患者特定的血管几何结构中匹配患者特定生理数据的第一步。 据报道，在此类问题中出现的两个关键挑战是，$\left( i \right)$。 缺乏对有意义边界条件的稳健量化，以尽可能匹配已知数据和$\left( ii \right)$。 高计算成本。 在本工作中，我们利用最优流动控制问题中的未知控制变量来解决第一个挑战。 此外，为了解决第二个挑战，我们通过使用适当正交分解（POD）-伽辽金方法将它们投影到低维解流形上，提出了一种时间高效且可靠的计算环境用于此类参数化问题。 显示英文摘要

摘要： Coronary artery bypass grafts (CABG) surgery is an invasive procedure performed to circumvent partial or complete blood flow blockage in coronary artery disease (CAD). In this work, we apply a numerical optimal flow control model to patient-specific geometries of CABG, reconstructed from clinical images of real-life surgical cases, in parameterized settings. The aim of these applications is to match known physiological data with numerical hemodynamics corresponding to different scenarios, arisen by tuning some parameters. Such applications are an initial step towards matching patient-specific physiological data in patient-specific vascular geometries as best as possible. Two critical challenges that reportedly arise in such problems are, $\left( i \right)$. lack of robust quantification of meaningful boundary conditions required to match known data as best as possible and $\left( ii \right)$. high computational cost. In this work, we utilize unknown control variables in the optimal flow control problems to take care of the first challenge. Moreover, to address the second challenge, we propose a time-efficient and reliable computational environment for such parameterized problems by projecting them onto a low-dimensional solution manifold through proper orthogonal decomposition (POD)--Galerkin.