Evaluating Uncertainties in CFD Simulations of Patient-Specific Aorta Models using Grid Convergence Index Method
Osman Aycan, Adnan Topuz, Lyes Kadem

TL;DR
This study evaluates how different mesh types and densities affect the accuracy and reliability of CFD simulations of patient-specific aorta models, using the Grid Convergence Index method to identify optimal meshing strategies.
Contribution
It introduces a systematic GCI-based approach to select the best mesh type for CFD aorta simulations, highlighting the advantages of polyhedral meshes.
Findings
Increasing mesh density reduces uncertainty in results.
Polyhedral meshes offer a good balance between accuracy and computational cost.
GCI values confirm the reliability of the simulation results.
Abstract
Cardiovascular diseases are among the most important causes of global mortality. Computational Fluid Dynamics (CFD) is a powerful research tool that analyzes the hemodynamics of artery and blood flow patterns. In this study, CFD simulations are performed to assess the patient-specific healthy aorta, fusiform, and saccular aneurysm with various mesh types, including tetrahedral, polyhedral, and poly-hexacore. The aim of this study is to explore how different mesh types and grid densities impact the hemodynamic properties of physiological flows, with the goal of identifying the most cost-effective meshing approach. A mesh independence study is carried out to ensure the precision of the results, considering the wall shear stress distribution. For this, five different mesh resolutions are generated for each geometry. The uncertainties of the simulations associated with the discretization…
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