Experimental and Numerical Investigation of an Axial Rotary Blood Pump

Abstract

Left ventricular assist devices (LVADs) have become a standard therapy for patients with severe heart failure. As low blood trauma in LVADs is important for a good clinical outcome, the assessment of the fluid loads inside the pump is critical. More specifically, the flow features on the surfaces where the interaction between blood and artificial material happens is of great importance. Therefore, experimental data for the near-wall flows in an axial rotary blood pump were collected and directly compared to computational fluid dynamic results. For this, the flow fields based on unsteady Reynolds-averaged Navier-Stokes simulations-computational fluid dynamics (URANS-CFD) of an axial rotary blood pump were calculated and compared with experimental flow data at one typical state of operation in an enlarged model of the pump. The focus was set on the assessment of wall shear stresses (WSS) at the housing wall and rotor gap region by means of the wall-particle image velocimetry technique, and the visualization of near-wall flow structures on the inner pump surfaces by a paint erosion method. Additionally, maximum WSS and tip leakage volume flows were measured for 13 different states of operation. Good agreement between CFD and experimental data was found, which includes the location, magnitude, and direction of the maximum and minimum WSS and the presence of recirculation zones on the pump stators. The maximum WSS increased linearly with pressure head. They occurred at the upstream third of the impeller blades and exceeded the critical values with respect to hemolysis. Regions of very high shear stresses and recirculation zones could be identified and were in good agreement with simulations. URANS-CFD, which is often used for pump performance and blood damage prediction, seems to be, therefore, a valid tool for the assessment of flow fields in axial rotary blood pumps. The magnitude of maximum WSS could be confirmed and were in the order of several hundred Pascal.

Turbulence Measurements in an Axial Rotary Blood Pump with Laser Doppler Velocimetry

“…The specific speed, flow coefficient, and head coefficient are automatically maintained under the applied Euler and Reynolds scaling. A comparison between the pump performance curves of the up-scaled model and the original model has shown similarity based on pump pressure head, rotational speed and volume flow at the investigated state of operation (30). Therefore, it is concluded that both pumps have similar flow and that the slightly larger tip gap in the up-scaled model did not significantly alter the mean flow characteristics of the pump.…”

Computational characterization of flow and blood damage potential of the new maglev CH-VAD pump versus the HVAD and HeartMate II pumps

“…Specifically, the gap size of the hydrodynamic bearing in the HVAD is generally smaller than 0.05 mm, 16 and the gap size between the blade tips and the housing in the HM II pump is 0.1 mm. 50 Therefore, the inaccuracies in the geometries of the two pumps could potentially cause noticeable changes in the WSS levels in these gaps. The CFD-predicted HI in the areas with small gaps could also be affected.…”

On the Accuracy of Hemolysis Models in Couette‐Type Blood Shearing Devices

“…Computational fluid dynamics (CFD) has been widely used in various engineering fields to solve and analyze problems that involve fluid flows . Empirical hemolysis estimation models, in conjunction with CFD simulations have been used to predict hemolysis during the development phase of VADs . Typical hemolysis models relate hemolysis to shear stresses and exposure time through a power‐law relationship …”

“…Computational fluid dynamics (CFD) has been widely used in various engineering fields to solve and analyze problems that involve fluid flows (6,7). Empirical hemolysis estimation models, in conjunction with CFD simulations have been used to predict hemolysis during the development phase of VADs (8)(9)(10)(11)(12)(13)(14)(15)(16)(17). Typical hemolysis models relate hemolysis to shear stresses and exposure time through a power-law relationship (18)(19)(20)(21)(22) where D (%) is the hemolysis index, Hb is the total hemoglobin concentration, hb represents the increase in plasma free hemoglobin, C, and are empirical constants determined by regression of the experimental data.…”