A Numerical Study of Aortic Flow Stability and Comparison With In Vivo Flow Measurements

Kousera, CA; Wood, Nigel B.; Seed, W. A.; Torii, Ryo; O’Regan, Declan P; Xu, X. Yun

doi:10.1115/1.4023132

Cited by 51 publications

(38 citation statements)

References 32 publications

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“…Salsac et al (2006) also provides a thorough description of the unsteady wall shear stress, but does not consider the instability and laminar-turbulent transition of the vortex ring. Both studies from Peattie et al (2004) and Salsac et al (2006) investigate peak Reynolds numbers based on the undilated vessel diameter of Re = 2300 and Re = 2700 , which is presumed to be too low for the human aorta (Kousera et al 2013). Yip andYu (2001, 2003) provide an overall description of the flow inside an aneurysm, and discuss the stability and decay of the vortex, as well as the spatial and temporal evolution of the WSS.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the wall shear stress in a generic aneurysm under pulsating and transitional flow conditions

et al. 2020

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In this study, the flow through a generic abdominal aneurysm under realistic pulsating flow conditions is examined with magnetic resonance velocimetry (MRV), laser Doppler velocimetry (LDV) and computational fluid dynamics (CFD). The influence of flow phenomena on the wall shear stress (WSS) is examined. It is seen that a strong vortex ring develops during systole at the proximal end of the aneurysm and subsequently travels downstream and decays. The vortex formation plays a major role in the temporal and spatial distribution of the WSS, which is analyzed in detail. A peak of the WSS is observed for a very limited time and in a very localized region where the vortex ring initially develops. The intrinsic temporal averaging during the acquisition of the MRV data is found to significantly decrease this peak. CFD and LDV results, which are averaged in the same manner, show a similar behavior. This indicates that besides the spatial resolution, the temporal resolution is a crucial factor, which needs to be considered especially in flows where vortex rings are observed. Results from LDV and CFD show excellent agreement for the velocity field obtained by MRV. While the flow is found to be laminar in the undilated diameter, results show laminar-turbulent transitional behavior for specific phases of the cycle within the aneurysm bulk. Although MRV is not capable of measuring instantaneous velocity fluctuations, we show that the periodic increase in turbulence intensity can be observed from image artifacts in the MRV data. These artifacts increase the velocity uncertainty, which correlates well with the velocity fluctuations measured with LDV. Although the flow encounters laminar and transitional conditions as well as multiple vortices and stagnation and reattachment points, the improved instabilitysensitive Reynolds stress model, which is used for the numerical simulations of this work, shows very good agreement with the measurements. Significant effort has been expended by numerous research groups in recent years in improving the estimation of WSS from MRV data. However, an assessment of these various post-processing methods is only possible if the true values of the WSS are known. The present study is therefore aimed at providing such ground truth WSS values as well as the corresponding MRV data, allowing also other research groups to validate their WSS estimation methods using the experimental data set presented in this work.

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Section: Introductionmentioning

confidence: 99%

Analysis of the wall shear stress in a generic aneurysm under pulsating and transitional flow conditions

et al. 2020

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“…Failure to consider the turbulent flow behaviour can cause a large numerical error. Kousera et al reported stability of aortic flow [8]. Using the Reynolds-averaged Navier–Stokes-based shear stress transport transitional model to compute various Reynolds numbers ranging from 4000 to 10,000 and Womersley parameters ranging from 17 to 26, they concluded that the model is capable of capturing the correct flow state by comparing the results to experimentally acquired in vivo flow measurements using a catheter-mounted hot-film probe.…”

Section: Introductionmentioning

confidence: 99%

Validation of numerical simulation methods in aortic arch using 4D Flow MRI

Miyazaki

Furusawa²,

Nishino³

et al. 2017

Heart Vessels

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Computational fluid dynamics (CFD) are the gold standard in studying blood flow dynamics. However, CFD results are dependent on the boundary conditions and the computation model. The purpose of this study was to validate CFD methods using comparison with actual measurements of the blood flow vector obtained with four-dimensional (4D) flow magnetic resonance imaging (MRI). 4D Flow MRI was performed on a healthy adult and a child with double-aortic arch. The aortic lumen was segmented to visualize the blood flow. The CFD analyses were performed for the same geometries based on three turbulent models: laminar, large eddy simulation (LES), and the renormalization group k–ε model (RNG k–ε). The flow-velocity vector components, namely the wall shear stress (WSS) and flow energy loss (EL), of the MRI and CFD results were compared. The flow rate of the MRI results was underestimated in small vessels, including the neck vessels. Spiral flow in the ascending aorta caused by the left ventricular twist was observed by MRI. Secondary flow distal to the aortic arch was well realized in both CFD and MRI. The average correlation coefficients of the velocity vector components of MRI and CFD for the child were the highest for the RNG k–ε model (0.530 in ascending aorta, 0.768 in the aortic arch, 0.584 in the descending aorta). The WSS and EL values of MRI were less than half of those of CFD, but the WSS distribution patterns were quite similar. The WSS and EL estimates were higher in RNG k–ε and LES than in the laminar model because of eddy viscosity. The CFD computation realized accurate flow distal to the aortic arch, and the WSS distribution was well simulated compared to actual measurement using 4D Flow MRI. However, the helical flow was not simulated in the ascending aorta. The accuracy was enhanced by using the turbulence model, and the RNG k–ε model showed the highest correlation with 4D Flow MRI.

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“…Altered hemodynamics is associated with aorta pathologies (aneurysms and stenosis) affecting the long-term outcome of patients (1,3,12). The accuracy of CFD results is, however, mainly affected by a choice of the appropriate CFD model, as shown in a set of numerical studies (13)(14)(15)(16)(17). In this proof-of-concept study we compared MRIbased CFD with catheter-derived peak systolic pressure drops in a clinical setting in patients with CoA.…”

mentioning

confidence: 99%

MRI‐based computational fluid dynamics for diagnosis and treatment prediction: Clinical validation study in patients with coarctation of aorta

Goubergrits

Riesenkampff

Yevtushenko

et al. 2014

Magnetic Resonance Imaging

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A Numerical Study of Aortic Flow Stability and Comparison With In Vivo Flow Measurements

Cited by 51 publications

References 32 publications

Analysis of the wall shear stress in a generic aneurysm under pulsating and transitional flow conditions

Analysis of the wall shear stress in a generic aneurysm under pulsating and transitional flow conditions

Validation of numerical simulation methods in aortic arch using 4D Flow MRI

MRI‐based computational fluid dynamics for diagnosis and treatment prediction: Clinical validation study in patients with coarctation of aorta

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