This study aims to develop an experimentally validated computational fluid dynamics (CFD) model to estimate hemodynamic characteristics in cerebral aneurysms (CAs) using non-Newtonian blood analogues. Blood viscosities varying with shear rates were measured under four temperatures first, which serves as the reference for the generation of blood analogues. Using the blood analogue, particle image velocimetry (PIV) measurements were conducted to quantify flow characteristics in a CA model. Then, using the identical blood properties in the experiment, CFD simulations were executed to quantify the flow patterns, which were used to compare with the PIV counterpart. Additionally, hemodynamic characteristics in the simplified Newtonian and non-Newtonian models were quantified and compared using the experimentally validated CFD model. Results showed the proposed non-Newtonian viscosity model can predict blood shear-thinning properties accurately under varying temperatures and shear rates. Another developed viscosity model based on the blood analogue can well represent blood rheological properties. The comparisons in flow characteristics show good agreements between PIV and CFD, demonstrating the developed CFD model is qualified to investigate hemodynamic factors within CAs. Furthermore, results show the differences of absolute values were insignificant between Newtonian and non-Newtonian fluids in the distributions of wall shear stress (WSS) and oscillatory shear index (OSI) on arterial walls. However, not only does the simplified Newtonian model underestimate WSS and OSI in most regions of the aneurysmal sac, but it also makes mistakes in identifying the high OSI regions on the sac surface, which may mislead the hemodynamic assessment on the pathophysiology of CAs.

This study provides a quantitative analysis to investigate the effects of cough intensity and initial mucus thickness on the mucus transport and clearance in a mouth-to-trachea airway geometry using an experimentally validated Volume of Fluid (VOF) based multiphase model. In addition, the accuracy of simplifying mucus as Newtonian fluid is also quantified by the comparisons of mucus transport and clearance efficiencies with the simulations using realistic shear-thinning non-Newtonian fluid viscosities as a function of shear rate. It proves that the VOF model developed in this study can capture air–mucus interface evolution and predict the mucus transport behaviors driven by the expiratory cough waveforms. Numerical results show that noticeable differences can be identified between the simulations using simplified Newtonian fluid and the realistic non-Newtonian fluid viscosity models, which indicates that an appropriate non-Newtonian fluid model should be applied when modeling mucus transport to avoid the possible inaccuracy induced by the Newtonian fluid simplification. Furthermore, the results also indicate that an intense cough can enhance the mucus clearance efficiency in chronic obstructive pulmonary disease (COPD) upper airways. Additionally, although higher mucus clearance efficiency is observed for severe COPD conditions with a thicker mucus layer, there is a possibility of mucus accumulation and obstruction in the upper airway for such a COPD condition if the cough is not strong enough, which will possibly cause further breathing difficulty. The VOF model developed in this study can be further refined and integrated with discrete phase models to predict the mucus clearance effect on inhaled particles explicitly.