The results show the potential of the large eddy simulation as a high-quality comparative case to check the suitability of a chosen Reynolds-averaged Navier-Stokes setup and turbulence model. Furthermore, the results lead to suggest that large eddy simulations are superior to unsteady Reynolds-averaged Navier-Stokes simulations when instantaneous stresses are applied for the blood damage prediction.

The blood damage prediction in rotary blood pumps is an important procedure to evaluate the hemocompatibility of such systems. Blood damage is caused by shear stresses to the blood cells and their exposure times. The total impact of an equivalent shear stress can only be taken into account when turbulent stresses are included in the blood damage prediction. The aim of this article was to analyze the influence of the turbulent stresses on the damage prediction in a rotary blood pump’s flow. Therefore, the flow in a research blood pump was computed using large eddy simulations. A highly turbulence-resolving setup was used in order to directly resolve most of the computed stresses. The simulations were performed at the design point and an operation point with lower flow rate. Blood damage was predicted using three damage models (volumetric analysis of exceeded stress thresholds, hemolysis transport equation, and hemolysis approximation via volume integral) and two shear stress definitions (with and without turbulent stresses). For both simulations, turbulent stresses are the dominant stresses away from the walls. Here, they act in a range between 9 and 50 Pa. Nonetheless, the mean stresses in the proximity of the walls reach levels, which are one order of magnitude higher. Due to this, the turbulent stresses have a small impact on the results of the hemolysis prediction. Yet, turbulent stresses should be included in the damage prediction, since they belong to the total equivalent stress definition and could impact the damage on proteins or platelets.

Adverse events due to flow-induced blood damage remain a serious problem for blood pumps as cardiac support systems. The numerical prediction of blood damage via computational fluid dynamics (CFD) is a helpful tool for the design and optimization of reliable pumps. Blood damage prediction models primarily are based on the acting shear stresses, which are calculated by solving the Navier–Stokes equations on computational grids. The purpose of this paper is to analyze the influence of the spatial discretization and the associated discretization error on the shear stress calculation in a blood pump in comparison to other important flow quantities like the pressure head of the pump. Therefore, CFD analysis using seven unsteady Reynolds-averaged Navier–Stokes (URANS) simulations was performed. Two simple stress calculation indicators were applied to estimate the influence of the discretization on the results using an approach to calculate numerical uncertainties, which indicates discretization errors. For the finest grid with 19 × 106 elements, numerical uncertainties up to 20% for shear stresses were determined, while the pressure heads show smaller uncertainties with a maximum of 4.8%. No grid-independent solution for velocity gradient-dependent variables could be obtained on a grid size that is comparable to mesh sizes in state-of-the-art blood pump studies. It can be concluded that the grid size has a major influence on the shear stress calculation, and therefore, the potential blood damage prediction, and that the quantification of this error should always be taken into account.

Numerical flow simulations that analyze the turbulent flow characteristics within a turbopump are important for optimizing the efficiency of such machines. In the case of ventricular assist devices (VADs), turbulent flow characteristics must be also examined in order to improve hemocompatibility. Turbulence increases the shear stresses in the VAD flow, which can lead to an increased damage to the transported blood components. Therefore, an understanding of the turbulent flow patterns and their significance for the numerical blood damage prediction is particularly important for flow optimizations in VADs in order to identify and thus minimize flow regions where blood could be damaged due to high turbulent stresses. Nevertheless, the turbulence occurring in VADs and the local turbulent structures that lead to increased turbulent stresses have not yet been analyzed in detail in these machines. Therefore, this study aims to investigate the turbulence in an axial VAD in a comprehensive and double tracked way. First, the flow in an axial VAD was computed using the large‐eddy simulation method, and it was verified that the majority of the turbulence was directly resolved by the simulation. Then, the turbulent flow state of the VAD was quantified globally. For this purpose, a self‐designed evaluation method, the power loss analysis, was used. Subsequently, local flow regions and flow structures were identified where significant turbulent stresses prevail. It will be shown that the identified regions are universal and will also occur in other axial blood pumps as well, for example, in the HeartMate II.

Purpose Cardiovascular engineering includes flows with fluid-dynamical stresses as a parameter of interest. Mechanical stresses are high-risk factors for blood damage and can be assessed by computational fluid dynamics. By now, it is not described how to calculate an adequate scalar stress out of turbulent flow regimes when the whole share of turbulence is not resolved by the simulation method and how this impacts the stress calculation. Methods We conducted direct numerical simulations (DNS) of test cases (a turbulent channel flow and the FDA nozzle) in order to access all scales of flow movement. After validation of both DNS with literature und experimental data using magnetic resonance imaging, the mechanical stress is calculated as a baseline. Afterwards, same flows are calculated using state-of-the-art turbulence models. The stresses are computed for every result using our definition of an equivalent scalar stress, which includes the influence from respective turbulence model, by using the parameter dissipation. Afterwards, the results are compared with the baseline data. Results The results show a good agreement regarding the computed stress. Even when no turbulence is resolved by the simulation method, the results agree well with DNS data. When the influence of non-resolved motion is neglected in the stress calculation, it is underpredicted in all cases. Conclusion With the used scalar stress formulation, it is possible to include information about the turbulence of the flow into the mechanical stress calculation even when the used simulation method does not resolve any turbulence.