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计算模型如何帮助在设计过程早期预测人工肺中的气体传递。

How Computational Modeling can Help to Predict Gas Transfer in Artificial Lungs Early in the Design Process.

机构信息

From the Department of Cardiovascular Engineering, Institute of Applied Medical Engineering, Helmholtz Institute, Medical Faculty, RWTH Aachen University, Germany.

出版信息

ASAIO J. 2020 Jun;66(6):683-690. doi: 10.1097/MAT.0000000000001098.

Abstract

Wearable extracorporeal membrane oxygenation (ECMO) circuits may soon become a viable alternative to conventional ECMO treatment. Common device-induced complications, however, such as blood trauma and oxygenator thrombosis, must first be addressed to improve long-term reliability, since ambulatory patients cannot be monitored as closely as intensive care patients. Additionally, an efficient use of the membrane surface can reduce the size of the devices, priming volume, and weight to achieve portability. Both challenges are linked to the hemodynamics in the fiber bundle. While experimental test methods can often only provide global and time-averaged information, computational fluid dynamics (CFD) can give insight into local flow dynamics and gas transfer before building the first laboratory prototype. In this study, we applied our previously introduced micro-scale CFD model to the full fiber bundle of a small oxygenator for gas transfer prediction. Three randomized geometries as well as a staggered and in-line configuration were modeled and simulated with Ansys CFX. Three small laboratory oxygenator prototypes were built by stacking fiber segments unidirectionally with spacers between consecutive segments. The devices were tested in vitro for gas transfer with porcine blood in accordance with ISO 7199. The error of the predicted averaged CFD oxygen saturations of the random 1, 2, and 3 configurations relative to the averaged in-vitro data (over all samples and devices) was 2.4%, 4.6%, 3.1%, and 3.0% for blood flow rates of 100, 200, 300, and 400 ml/min, respectively. While our micro-scale CFD model was successfully applied to a small oxygenator with unidirectional fibers, the application to clinically relevant oxygenators will remain challenging due to the complex flow distribution in the fiber bundle and high computational costs. However, we will outline our future research priorities and discuss how an extended mass transfer correlation model implemented into CFD might enable an a priori prediction of gas transfer in full size oxygenators.

摘要

可穿戴式体外膜肺氧合(ECMO)回路可能很快成为传统 ECMO 治疗的可行替代方案。然而,必须首先解决常见的设备引起的并发症,如血液创伤和氧合器血栓形成,以提高长期可靠性,因为不能像对重症监护患者那样密切监测门诊患者。此外,有效利用膜表面可以减小设备的尺寸、预充体积和重量,从而实现便携性。这两个挑战都与纤维束中的血液动力学有关。虽然实验测试方法通常只能提供全局和时间平均信息,但计算流体动力学(CFD)可以在构建第一个实验室原型之前深入了解局部流动动力学和气体传递。在这项研究中,我们将之前介绍的微尺度 CFD 模型应用于小型氧合器的整个纤维束,以预测气体传递。对三种随机几何形状以及交错和直线配置进行了建模和模拟,并使用 Ansys CFX 进行了模拟。通过在相邻段之间使用间隔件将纤维段单向堆叠,制造了三个小型实验室氧合器原型。根据 ISO 7199,用猪血对设备进行了体外气体传递测试。与体外数据(所有样本和设备的平均值)相比,预测的随机 1、2 和 3 配置的平均 CFD 氧饱和度的误差分别为 2.4%、4.6%、3.1%和 3.0%,血流速度分别为 100、200、300 和 400 ml/min。虽然我们的微尺度 CFD 模型成功地应用于具有单向纤维的小型氧合器,但由于纤维束中的复杂流动分布和高计算成本,将其应用于临床相关的氧合器仍具有挑战性。然而,我们将概述我们未来的研究重点,并讨论如何将扩展的传质相关模型应用于 CFD 可能实现对全尺寸氧合器中气体传递的预先预测。

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