The characteristics of mechanical bileaflet valves, the leaflets of which open at the outside first, differ significantly from those of natural valves, whose leaflets open at the center first, and this fact affects the flow field down-stream of the valves. The direction of jet-type flows, which is influenced by this difference in valve features, and the existence of the sinus of Valsalva both affect the flow field inside the aorta in different ways, depending on the valve design. There may also be an influence on the coronary circulation, the entrance to which resides inside the sinus of Valsalva. A dynamic particle image velocimetry (PIV) study was conducted to analyze the influence of the design of prosthetic heart valves on the aortic flow field. Three contemporary bileaflet prostheses, the St. Jude Medical (SJM) valve, the On-X valve (with straight leaflets), and the MIRA valve (with curved leaflets), were tested inside a simulated aorta under pulsatile flow conditions. A dynamic PIV system was employed to analyze the aortic flow field resulting from the different valve designs. The two newer valves, the On-X and the MIRA valves, open more quickly than the SJM valve and provide a wider opening area when the valve is fully open. The SJM valve's outer orifices deflect the flow during the accelerating flow phase, whereas the newer designs deflect the flow less. The flow through the central orifice of the SJM valve has a lower velocity compared to the newer designs; the newer designs tend to have a strong flow through all orifices. The On-X valve generates a simple jet-type flow, whereas the MIRA valve (with circumferentially curved leaflets) generates a strong but three-dimensionally diffuse flow, resulting in a more complex flow field downstream of the aortic valve. The clinically more adapted 180 degrees orientation seems to provide a less diffuse flow than the 90 degrees orientation does. The small differences in leaflet design in the bileaflet valves generate noticeable differences in the aortic flow; the newer valves show strong flows through all orifices.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s10047-008-0410-y | DOI Listing |
Sci Rep
January 2025
Laboratory of Engineering Profile, Satbayev University, Satbayev St. 22a, 050013, Almaty, Kazakhstan.
Several mechanisms were postulated to reduce drilling problems, improve hole cleaning characteristics, and keep the bit in good condition for the second usage. This study was conducted on Majnoon Field in southeastern Iraq to optimize the bit and drilling parameters. The results indicated that the 16" SFD75D bit proved the preferred bit for both vertical and deviated wells due to its directional capabilities.
View Article and Find Full Text PDFSci Rep
January 2025
University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan, 680-749, Republic of Korea.
This study employed large eddy simulation (LES) with the wall-adapting local eddy-viscosity (WALE) model to investigate transitional flow characteristics in an idealized model of a healthy thoracic aorta. The OpenFOAM solver pimpleFoam was used to simulate blood flow as an incompressible Newtonian fluid, with the aortic walls treated as rigid boundaries. Simulations were conducted for 30 cardiac cycles and ensemble averaging was employed to ensure statistically reliable results.
View Article and Find Full Text PDFAnal Chim Acta
February 2025
Department of Physical and Analytical Chemistry & Institute of Biotechnology of Asturias, University of Oviedo, c/Julián Clavería 8, 33006, Oviedo, Spain. Electronic address:
The COVID-19 outbreak was an important turning point in the development of a new generation of biosensing technologies. The synergistic combination of an immunochromatographic test (lateral flow immunoassays, LFIA) and signal transducers provides enhanced sensitivity and the ability to quantify in the rapid tests. This is possible due to the variety of nanoparticles that can be used as reporter labels.
View Article and Find Full Text PDFMagn Reson Imaging
January 2025
Institute of Fluid Mechanics, University of Rostock, Rostock, Germany.
Purpose: To improve the current method for MRI turbulence quantification which is the intravoxel phase dispersion (IVPD) method. Turbulence is commonly characterized by the Reynolds stress tensor (RST) which describes the velocity covariance matrix. A major source for systematic errors in MRI is the sequence's sensitivity to the variance of the derivatives of velocity, such as the acceleration variance, which can lead to a substantial measurement bias.
View Article and Find Full Text PDFNeural Netw
January 2025
Defense Innovation Institute, Chinese Academy of Military Science, Beijing 100071, China; Intelligent Game and Decision Laboratory, China.
The Physics-informed Neural Network (PINN) has been a popular method for solving partial differential equations (PDEs) due to its flexibility. However, PINN still faces challenges in characterizing spatio-temporal correlations when solving parametric PDEs due to network limitations. To address this issue, we propose a Physics-Informed Neural Implicit Flow (PINIF) framework, which enables a meshless low-rank representation of the parametric spatio-temporal field based on the expressiveness of the Neural Implicit Flow (NIF), enabling a meshless low-rank representation.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!