An Experimental Study of Pulsatile Flow in a Compliant Aortic Root Model under Varied Cardiac Outputs

Zhang, Ruihang; Zhang, Yan

doi:10.3390/fluids3040071

Cited by 9 publications

(4 citation statements)

References 47 publications

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“…Additionally, the Computational Fluid Dynamics (CFD) simulations were based on a turbulent flow model. In reality, blood flow through the aortic valve is pulsatile in nature, meaning it may fail to reach a completely turbulent state (Zhang & Zhang, 2018).…”

Section: Discussionmentioning

confidence: 99%

CFD-based Synthetic Data Generation for Machine Learning based Pressure Drop Assessment in Aortic Stenosis

MATEI,

POPESCU,

NITA

et al. 2023

SIC

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Aortic stenosis occurs when the aortic valve does not fully open during the systole, which reduces and partially blocks the blood flow to the systemic circulation. The clinical diagnosis and treatment decision depend on the functional severity of the stenosis, which is assessed based on the trans-valvular peak pressure drop. The pressure drop is routinely estimated analytically, which may lead to sub-optimal results since certain hemodynamic aspects are not fully captured, like pressure recovery or blood flow turbulence. A promising solution lies in the use of machine learning (ML) for estimating the pressure drop based on patient-specific characteristics. Although a ML-based solution could provide the desired results in real time, the training of an accurate neural network would require a large database of invasively measured pressure drops, which is difficult and costly to set up. This study introduces a method for generating synthetic datasets based on a generic aortic valve model. This model is customized in order to create diverse yet physiologically normal valve shapes by modifying three anatomical parameters, namely the aorta diameter, blood velocity and valve area, by reducing it. High-fidelity computational fluid dynamics (CFD) simulations were conducted to compute reference pressure drop values. The efficacy of the generated dataset was assessed by employing it for training an ML model for pressure drop estimation.

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Section: Discussionmentioning

confidence: 99%

CFD-based Synthetic Data Generation for Machine Learning based Pressure Drop Assessment in Aortic Stenosis

MATEI,

POPESCU,

NITA

et al. 2023

SIC

View full text Add to dashboard Cite

show abstract

“…The list of similarity parameters is presented in Table 2 in the Results section. More details regarding the simulator can also be found in [24] A square channel with a rectangular sidewall cavity model with aspect ratio of 1.5 (depth/width) was constructed using acrylic sheets, as shown in Fig. 2b.…”

Section: The Pulsatile Flow Simulator and Cavity Modelmentioning

confidence: 99%

Diversion of Pulsatile Flow Over a Rectangular Sidewall Cavity Using Superhydrophobic Mesh

Eichholz

Zhang

2020

Volume 2: Fluid Mechanics; Multiphase Flows

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Pulsatile flow over open cavity represents one type of physiological phenomenon related to a few common cardiovascular diseases, such as cerebral sidewall aneurysm and arrhythmia-induced thromboembolism in the left atrium appendage (LAA). In recent years, endovascular treatments using mesh-based implants have become increasingly popular. In this paper, we study the characteristics of pulsatile flow over a simplified sidewall cavity under two Reynolds/Womersley number conditions using Particle Image Velocimetry. The impacts of a regular mesh and a superhydrobobically-coated mesh on the cavity flow are investigated. Our results quantify the phase-to-phase changes of the flow fields and reveal the formation and the transport of the primary vortex over the ostium of the rectangular cavity. Results suggest the meshes diverted the main flow away from the cavity and prohibited the development of the primary vortex. A penetrated jet flow was formed near the front side of the cavity due to the presence of the mesh. The superhydrophobic mesh dramatically reduced the kinetic energy of the penetrated jet into the cavity. It indicates the mesh flow diversion is effective because of the destruction of the shear-induced vortex dynamics that causes flow stagnation on the rear cavity wall. Our results also indicate the superhydrophobic coating is potentially beneficial in terms of reducing the hemodynamic loading inside the cavity.

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“…Fluid mechanics face problems with the measurement of volume flow on a micro-scale, which include, among others, biological systems, especially blood flow measurement [1], and on a macro-scale, in industrial flows. Several different flow meters are used for measuring, mainly for the purpose of controlling the technological process where constant measurement of fluid flow is required.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty Assessment for Determining the Discharge Coefficient C for a Multi-Opening Orifice

Mrowiec

2020

Applied Sciences

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This article contains the results of experimental studies of a multi-opening orifice with substitute constriction factor of β = 0.5 (m = 0.25), mounted in a DN50 hydraulic measuring flume. Flow measurements were taken from a progressing turbulent flow within Reynolds numbers (Re = 4700–19,500). Based on conducted experimental data, flow characteristics, and discharge coefficient C characteristics were determined. Relative expanded uncertainty of determining a discharge coefficient C was estimated within the changes of volume flow qv from 0.35 to 0.68 dm3/s, based on rules from the GUM international standard. The value, determined from uncertainty analysis, did not exceed 1.25% within the changes of Reynolds numbers 9800 ≤ Re ≤ 19,500.

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An Experimental Study of Pulsatile Flow in a Compliant Aortic Root Model under Varied Cardiac Outputs

Cited by 9 publications

References 47 publications

CFD-based Synthetic Data Generation for Machine Learning based Pressure Drop Assessment in Aortic Stenosis

CFD-based Synthetic Data Generation for Machine Learning based Pressure Drop Assessment in Aortic Stenosis

Diversion of Pulsatile Flow Over a Rectangular Sidewall Cavity Using Superhydrophobic Mesh

Uncertainty Assessment for Determining the Discharge Coefficient C for a Multi-Opening Orifice

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