Grid convergence study for the prediction of hemolysis in blood circulatory devices: sensitivity to the form of equivalent stress and turbulence simulation methods

Abstract

Hemolysis and related complications induced by non-physiological stress are major concerns during the development and clinical applications of blood circulatory devices. Turbulence is one of the primary causes of hemolysis. To consider turbulence effects on hemolysis, various turbulence simulation methods and stress forms were employed or proposed. Nonetheless, the results showed significant divergence for different stress forms and turbulence simulation methods, discrediting hemolysis prediction as an important tool for the design, optimization and evaluation of blood circulatory devices. This study aims at quantitatively investigating the grid convergence for the prediction of hemolysis in blood circulatory devices, with a focus on its sensitivity to the stress forms and turbulence simulation methods. We revealed the integral of equivalent stress has very different characteristics of grid convergence. For Reynolds-averaged Navier-Stokes (RANS) method, grid convergence was less demanding on grid size and insensitive to stress forms. For large eddy simulation (LES), grid convergence was demanding and sensitive to stress forms, with highest uncertainty for the “total scalar stress”, followed by “viscous stress”. The “energy-dissipation stress” showed the best grid convergence for both RANS and LES. We also observed a significant divergence for metrics based on “total scalar stress” under different turbulence simulation methods, while the “energy-dissipation stress” showed a much higher consistency. We show the combination of energy-dissipation stress and LES can better capture the trend of hemolysis and has the best grid convergence. This study provides insights for a better prediction of hemolysis in turbulent flows in blood circulatory devices.