Physiological Stress Modelling and Hemolysis Prediction for High Shear Stress Flows using Computational Hemodynamics

Predicting hemolysis is a mandatory task when designing blood flow related mechanisms. For decades, researchers have tried to estimate trauma in red cell (RBC) for applying assist mechanisms development, but the specificity and absence of more physical details limited models this purpose into ranges applications. This work aims present new method modelling considering stress threshold that RBC could stand and, bellow that, Physiological Stress. Complementing application, simulations Ventricular Assist Device (VAD) was performed using Computational Fluid Dynamics (CFD) hemodynamics. risk analyses, critical regions were established by mean magnitude, also purposed here. The magnitude presented including turbulent parameters, trying reduce error calculating tensor velocity magnitudes Reynolds Average Navier-Stokes flows. Five tested: Standard κ-ε, κ-ε RNG, Realizable, κ-ω, κ-ω SST Spalart-Allmaras models. Results indicate similar results Stress compared traditional model applications, even adapted coefficients, what induces specific coefficients might improve estimations. RNG had better agreement with data expectations best scenarios improved future uses.