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- W3038534988 abstract "Computational modeling methods have been increasingly employed to quantify aortic hemodynamic parameters that are challenging to in vivo measurements but important for the diagnosis/treatment of aortic disease. Although the presence of turbulence-like behaviors of blood flow in normal or diseased aorta has long been confirmed, the majority of existing computational model studies adopted the laminar flow assumption (LFA) in the treatment of sub-grid flow variables. So far, it remains unclear whether LFA would significantly compromise the reliability of hemodynamic simulation. In the present study, we addressed the issue in the context of a specific aortopathy, namely aortic dilation, which is usually accompanied by disturbed flow patterns. Three patient-specific aortas with treated/untreated dilation of the ascending segment were investigated, and their geometrical models were reconstructed from computed tomography angiographic images, with the boundary conditions being prescribed based on flow velocity information measured in vivo with the phase contrast magnetic resonance imaging technique. For the modeling of blood flow, apart from the traditional LFA-based method in which sub-grid flow dynamics is ignored, the large eddy simulation (LES) method capable of incorporating the dissipative energy loss induced by turbulent eddies at the sub-grid level, was adopted and taken as a reference for examining the performance of the LFA-based method. Obtained results showed that the simulated large-scale flow patterns with the two methods had high similarity, both agreeing well with in vivo measurements, although locally large between-method discrepancies in computed hemodynamic quantities existed in regions with high intensity of flow turbulence. Quantitatively, a switch from the LES to the LFAbased modeling method led to mild (" @default.
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- W3038534988 date "2020-01-01" @default.
- W3038534988 modified "2023-09-30" @default.
- W3038534988 title "Numerical Simulation of Blood Flow in Aorta with Dilation: A Comparison between Laminar and LES Modeling Methods" @default.
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- W3038534988 doi "https://doi.org/10.32604/cmes.2020.010719" @default.
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