A CFD-based Kriging surrogate modeling approach for predicting device-specific hemolysis power law coefficients in blood-contacting medical devices
A CFD-based Kriging surrogate modeling approach for predicting device-specific hemolysis power law coefficients in blood-contacting medical devices
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DOI：
10.1007/s10237-019-01126-4
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发表时间：
2019-08-01
影响因子：
3.5
通讯作者：
Malinauskas, Richard A.
中科院分区：
文献类型：
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作者：
Craven, Brent A.;Aycock, Kenneth I.;Malinauskas, Richard A.
计算流体动力学 (CFD) 中使用的大多数基于应力的溶血模型都是基于溶血产生与流动引起的应力和暴露时间之间的经验幂律相关性。经验模型系数通常是通过在均匀剪切条件和明确定义的暴露时间下在简化的血液剪切装置中拟合全局溶血测量来确定的。然后使用这些理想化的全局经验系数进行 CFD 模拟，以预测具有复杂血流动力学的医疗设备中的溶血情况。然而，这种对具有不同曝光时间和不均匀剪切的真实设备使用理想化系数的传统方法的适用性目前尚不清楚。在本研究中，我们提出了一种确定设备和物种特异性溶血幂律系数（C、a 和 b）的新方法。该方法包括使用不同的系数组计算多个溶血解，以在三维（C、a、b）参数空间中映射溶血响应场。然后将所得响应场与同一设备中的实验数据进行比较，以确定系数，当将其合并到局部定义的幂律模型中时，会产生正确的全局溶血预测。我们首先通过推导简单均匀和非均匀剪切流（分别为平面库埃特流和圆形泊肃叶流）的解析解来开发广义方法，这使我们能够在（C，a，b）参数空间中连续绘制溶血解。然后，我们将我们的方法扩展到与血液接触医疗设备相关的更多实际案例，用 CFD 和克里金代理模型替换我们的通用方法中对分析解决方案的要求。最后，我们应用经过验证的基于 CFD 的克里金代理建模方法来预测设备和物种特定的幂律系数，以在小毛细管中形成层流。我们表明，所得系数与从简化的均匀剪切实验获得的传统理想化系数有很大不同，并且使用这种理想化系数会产生高度不准确的溶血预测，与实验相比，误差超过 2000%。我们的方法和替代建模框架可以应用于更复杂的医疗设备，并易于扩展以确定其他基于连续体的溶血模型和其他形式的流动引起的血液损伤（例如血小板活化和血栓形成）的经验系数。
Most stress-based hemolysis models used in computational fluid dynamics (CFD) are based on an empirical power law correlation between hemolysis generation and the flow-induced stress and exposure time. Empirical model coefficients are typically determined by fitting global hemolysis measurements in simplified blood shearing devices under uniform shear conditions and with well-defined exposure times. CFD simulations using these idealized global empirical coefficients are then performed to predict hemolysis in a medical device with complex hemodynamics. The applicability, however, of this traditional approach of using idealized coefficients for a real device with varying exposure times and non-uniform shear is currently unknown. In this study, we propose a new approach for determining device- and species-specific hemolysis power law coefficients (C, a, and b). The approach consists of calculating multiple hemolysis solutions using different sets of coefficients to map the hemolysis response field in three-dimensional (C, a, b) parameter space. The resultant response field is then compared with experimental data in the same device to determine the coefficients that when incorporated into the locally defined power law model yield correct global hemolysis predictions. We first develop the generalized approach by deriving analytical solutions for simple uniform and non-uniform shear flows (planar Couette flow and circular Poiseuille flow, respectively) that allow us to continuously map the hemolysis solution in (C, a, b) parameter space. We then extend our approach to more practical cases relevant to blood-contacting medical devices by replacing the requirement for an analytical solution in our generalized approach with CFD and Kriging surrogate modeling. Finally, we apply our verified CFD-based Kriging surrogate modeling approach to predict the device- and species-specific power law coefficients for developing laminar flow in a small capillary tube. We show that the resultant coefficients are much different than traditional idealized coefficients obtained from simplified uniform shear experiments and that using such idealized coefficients yields a highly inaccurate prediction of hemolysis that is in error by more than 2000% compared to experiments. Our approach and surrogate modeling framework may be applied to more complex medical devices and readily extended to determine empirical coefficients for other continuum-based models of hemolysis and other forms of flow-induced blood damage (e.g., platelet activation and thrombosis).