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Quantifying turbulent wall shear stress in a subject specific human aorta using large eddy simulation

Lantz, Jonas (author)
Linköpings universitet,Mekanisk värmeteori och strömningslära,Tekniska högskolan
Gårdhagen, Roland (author)
Linköpings universitet,Mekanisk värmeteori och strömningslära,Tekniska högskolan
Karlsson, Matts (author)
Linköpings universitet,Mekanisk värmeteori och strömningslära,Tekniska högskolan
 (creator_code:org_t)
Elsevier, 2012
2012
English.
In: Medical Engineering and Physics. - : Elsevier. - 1350-4533 .- 1873-4030. ; 34:8, s. 1139-1148
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • In this study, large-eddy simulation (LES) is employed to calculate the disturbed flow field and the wall shear stress (WSS) in a subject specific human aorta. Velocity and geometry measurements using magnetic resonance imaging (MRI) are taken as input to the model to provide accurate boundary conditions and to assure the physiological relevance. In total, 50 consecutive cardiac cycles were simulated from which a phase average was computed to get a statistically reliable result. A decomposition similar to Reynolds decomposition is introduced, where the WSS signal is divided into a pulsating part (due to the mass flow rate) and a fluctuating part (originating from the disturbed flow). Oscillatory shear index (OSI) is plotted against time-averaged WSS in a novel way, and locations on the aortic wall where elevated values existed could easily be found. In general, high and oscillating WSS values were found in the vicinity of the branches in the aortic arch, while low and oscillating WSS were present in the inner curvature of the descending aorta. The decomposition of WSS into a pulsating and a fluctuating part increases the understanding of how WSS affects the aortic wall, which enables both qualitative and quantitative comparisons.

Keyword

Human aorta
Atherosclerosis
Wall shear stress
Computational fluid dynamics
Scale resolving turbulence model
Reynolds decomposition
TECHNOLOGY
TEKNIKVETENSKAP

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