EXPERIMENTAL AND NUMERICAL STUDY OF ASCENDING AORTA HEMODYNAMICS THROUGH 3D PARTICLE TRACKING VELOCIMETRY AND COMPUTATIONAL FLUID DYNAMICS

摘要

The complex hemodynamics observed in the human aorta make this district a site of election for an in depth investigation of the relationship between fluid structures, transport and pathophysiology. In recent years, the coupling of imaging techniques and computational fluid dynamics (CFD) has been applied to study aortic hemodynamics, because of the possibility to obtain highly resolved blood flow patterns in more and more realistic and fully personalized flow simulations [1]. However, the combination of imaging techniques and computational methods requires some assumptions that might influence the predicted hemodynamic scenario. Thus, computational modeling requires experimental cross-validation. Recently, 4D phase contrast MRI (PCMRI) has been applied in vivo and in vitro to access the velocity field in aorta [2] and to validate numerical results [3]. However, PCMRI usually requires long acquisition times and suffers from low spatial and temporal resolution and a low signal-to-noise ratio. Anemometric techniques have been also applied for in vitro characterization of the fluid dynamics in aortic phantoms. Among them, 3D Particle Tracking Velocimetry (PTV), an optical technique based on imaging of flow tracers successfully used to obtain Lagrangian velocity fields in a wide range of complex and turbulent flows [4], has been very recently applied to characterize fluid structures in the ascending aorta [5]. In this study, the 3D, pulsatile flow in an anatomically realistic rigid phantom of human ascending aorta (AAo) is investigated experimentally and computationally. The feasibility of unsteady velocity measurements by 3D PTV in a realistic AAo geometry is demonstrated, and the in vitro measured data are used as conditions at boundaries in high-resolution CFD simulations. The numerical solution is then cross-validated by PTV experiments. The validation of the numerical results allows to complement the in vitro measured data with reliable information, for instance on the distribution of the blood friction forces at the luminal surface of the vessel, the direct measure of which is still challenging.