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

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 condi...

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Published inMedical engineering & physics Vol. 34; no. 8; pp. 1139 - 1148
Main Authors Lantz, Jonas, Gårdhagen, Roland, Karlsson, Matts
Format Journal Article
LanguageEnglish
Published Kidlington Elsevier Ltd 01.10.2012
Elsevier
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Abstract 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.
AbstractList 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.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.
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.
Abstract 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.
Author Lantz, Jonas
Gårdhagen, Roland
Karlsson, Matts
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  surname: Gårdhagen
  fullname: Gårdhagen, Roland
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Issue 8
Keywords Wall shear stress
Scale resolving turbulence model
Reynolds decomposition
Computational fluid dynamics
Human aorta
Atherosclerosis
Human
Turbulence
Cardiovascular disease
Artery
Vascular disease
Large eddy simulation
Mechanical stress
Blood vessel
Shear stress
Aorta
Models
Circulatory system
Biomedical engineering
Language English
License CC BY 4.0
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Snippet 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....
Abstract 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...
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SubjectTerms Aorta
Aorta - physiology
Aortic arch
Atherosclerosis
Atherosclerosis (general aspects, experimental research)
Biological and medical sciences
Blood and lymphatic vessels
Blood Circulation
Boundaries
Cardiology. Vascular system
Computational fluid dynamics
Computer Simulation
Decomposition
Heart
Heart - physiology
Hemorheology
Human aorta
Humans
Hydrodynamics
Magnetic Resonance Imaging
Male
Mechanical stimuli
Medical sciences
Radiology
Reynolds decomposition
Scale resolving turbulence model
Spatio-Temporal Analysis
Stress, Mechanical
TECHNOLOGY
TEKNIKVETENSKAP
Wall shear stress
Title Quantifying turbulent wall shear stress in a subject specific human aorta using large eddy simulation
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https://www.clinicalkey.es/playcontent/1-s2.0-S135045331100316X
https://dx.doi.org/10.1016/j.medengphy.2011.12.002
https://www.ncbi.nlm.nih.gov/pubmed/22209366
https://www.proquest.com/docview/1037656407
https://www.proquest.com/docview/1125241924
https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-84887
Volume 34
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