Nasim Gholizadeh

Predicting absolute values of hemolysis using the power law model to guide medical device design is hampered by uncertainties stemming from four sources of model inputs: incoming/upstream velocity profiles, blood viscosity models, power law hemolysis coefficients, and obtaining accurate stress exposure times. Amidst all these uncertainties, enabling rapid assessments and predictions of relative hemolysis would still be valuable for evaluating device design prototypes. Towards achieving this objective, hemolysis data from the Eulerian modeling framework was first generated from computational fluid dynamics simulations encompassing five blood viscosity models, four sets of hemolysis power law coefficients, fully developed as well as developing velocity flow conditions, and a wide range of shear stresses, strain rates, and stress exposure times. Corresponding hemolysis predictions were also made in a Lagrangian framework via numerical integration of shear stress and residence time spatial variations under the assumption of fully developed Newtonian fluid flow. Absolute hemolysis predictions (from both frameworks) were proportional to each other and independent of the blood viscosity model. Further, relative hemolysis trends were not dependent on the hemolysis power law coefficients. However, accuracy in wall shear stresses in developing flow conditions is necessary for accurate relative hemolysis assessments.

Predicting absolute values of hemolysis using the power-law model to guide medical device design is hampered by uncertainties stemming from four sources of model inputs: incoming/upstream velocity profiles, blood viscosity model, power law hemolysis coefficients, and obtaining accurate stress exposure times. Amidst all these uncertainties, enabling rapid assessments and predictions of relative hemolysis would still be valuable towards evaluating device design prototypes. Towards achieving this objective, hemolysis data from Eulerian modeling framework was first generated from computational fluid dynamic simulations encompassing: five blood viscosity models, four sets of hemolysis power law coefficients, fully developed as well as developing velocity flow conditions, wide range of shear stresses (1 – 600 Pa), strain rates (1 – 10,000 s-1) and stress exposure times (5 – 400 milliseconds). Corresponding hemolysis predictions were also made in a Lagrangian framework via numerical integration of shear stress and residence time spatial variations under the assumption of fully developed Newtonian fluid flow. Absolute hemolysis predictions (from both frameworks) were proportional to each other and independent of the blood viscosity model. Further, relative hemolysis trends were not dependent on the hemolysis power law coefficients. However, accuracy in wall shear stresses in developing flow conditions are necessary for accurate relative hemolysis assessments.

There is a prevailing consensus that most Computational Fluid Dynamics (CFD) frameworks can accurately predict global variables under laminar flow conditions within the Food and Drug Administration (FDA) benchmark nozzle geometry. However, variations in derived variables, such as strain rate and vorticity, may arise due to differences in numerical solvers and gradient evaluation methods, which can subsequently impact predictions related to blood damage and non-Newtonian flow behavior. To examine this, flow symmetry indices, vortex characteristics, and blood damage—were assessed using Newtonian and four non-Newtonian viscosity models with CFD codes Ansys Fluent and OpenFOAM on identical meshes. At Reynolds number (Re) 500, symmetry breakdown and complex vortex shapes were predicted with some non-Newtonian models in both OpenFOAM and Ansys Fluent, whereas these phenomena were not observed with the Newtonian model. This contradicted the expectation that employing a non-Newtonian model would delay the onset of turbulence. Similarly, at Re 2000, symmetry breakdown occurred sooner (following the sudden expansion section) with the non-Newtonian models in both Ansys Fluent and OpenFOAM. Vortex identification based on the Q-criterion resulted in distinctly different vortex shapes in Ansys Fluent and OpenFOAM. Blood damage assessments showed greater prediction variations among the non-Newtonian models at lower Reynolds numbers.