Bozzi Silvia, Dominissini Davide, Redaelli Alberto, Passoni Giuseppe
Politecnico di Milano, Department of Electronics Information and Bioengineering, Milano, Italy.
Politecnico di Milano, Department of Electronics Information and Bioengineering, Milano, Italy.
J Biomech. 2021 Nov 9;128:110704. doi: 10.1016/j.jbiomech.2021.110704. Epub 2021 Aug 20.
Pathological platelet activation by abnormal shear stresses is regarded as a main clinical complication in recipients of cardiovascular mechanical devices. In order to improve their performance computational fluid dynamics (CFD) are used to evaluate flow fields and related shear stresses. CFD models are coupled with mathematical models that describe the relation between fluid dynamics variables, and in particular shear stresses, and the platelet activation state (PAS). These models typically use a Lagrangian approach to compute the shear stresses along possible platelet trajectories. However, in the case of turbulent flow, the choice of the proper turbulence closure is still debated for both concerning its effect on shear stress calculation and Lagrangian statistics. In this study different numerical simulations of the flow through a mechanical heart valve were performed and then compared in terms of Eulerian and Lagrangian quantities: a direct numerical simulation (DNS), a large eddy simulation (LES), two Reynolds-averaged Navier-Stokes (RANS) simulations (SST k-ω and RSM) and a "laminar" (no turbulence modelling) simulation. Results exhibit a large variability in the PAS assessment depending on the turbulence model adopted. "Laminar" and RSM estimates of platelet activation are about 60% below DNS, while LES is 16% less. Surprisingly, PAS estimated from the SST k- ω velocity field is only 8% less than from DNS data. This appears more artificial than physical as can be inferred after comparing frequency distributions of PAS and of the different Lagrangian variables of the mechano-biological model of platelet activation. Our study indicates how much turbulence closures may affect platelet activation estimates, in comparison to an accurate DNS, when assessing blood damage in blood contacting devices.
异常剪切应力导致的病理性血小板激活被视为心血管机械装置接受者的主要临床并发症。为了改善其性能,计算流体动力学(CFD)被用于评估流场和相关剪切应力。CFD模型与描述流体动力学变量之间关系的数学模型相结合,特别是剪切应力与血小板激活状态(PAS)之间的关系。这些模型通常采用拉格朗日方法来计算沿可能的血小板轨迹的剪切应力。然而,在湍流情况下,对于合适的湍流闭合模型的选择,在其对剪切应力计算和拉格朗日统计的影响方面仍存在争议。在本研究中,对通过机械心脏瓣膜的流动进行了不同的数值模拟,然后根据欧拉量和拉格朗日量进行了比较:直接数值模拟(DNS)、大涡模拟(LES)、两种雷诺平均纳维 - 斯托克斯(RANS)模拟(SST k - ω和RSM)以及一种“层流”(无湍流建模)模拟。结果表明,根据所采用的湍流模型,PAS评估存在很大差异。“层流”和RSM对血小板激活的估计比DNS低约60%,而LES低16%。令人惊讶的是,从SST k - ω速度场估计的PAS仅比DNS数据低8%。在比较PAS的频率分布和血小板激活的机械生物学模型的不同拉格朗日变量后可以推断,这看起来更像是人为的而非物理现象。我们的研究表明,在评估血液接触装置中的血液损伤时,与精确的DNS相比,湍流闭合模型对血小板激活估计的影响程度有多大。