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  5. 3D simulation of pulsatile bubbly flow resembling decompression sickness conditions inside a realistic human artery

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Article
en
2024

3D simulation of pulsatile bubbly flow resembling decompression sickness conditions inside a realistic human artery

0 Datasets

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en
2024
Vol 6 (2)
Vol. 6
DOI: 10.1007/s42757-023-0173-y

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Thodoris Karapantsios
Thodoris Karapantsios

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Sotiris P. Evgenidis
Thodoris Karapantsios

Abstract

Abstract I-VED ( In-Vivo Embolic Detector) is a novel diagnostic tool for non-invasive, real-time detection of bubbles in humans. Bubbles are precursors of decompression sickness (DCS), which can be encountered in astronauts, scuba divers, etc. I-VED exploits an EU patented electrical impedance spectroscopy technology, developed under the umbrella of a European Space Agency project. So far, I-VED has been calibrated and validated in vitro . In view of the forthcoming in-vivo trials, it needs to be configured for sensing bubbles in the bloodstream. For this, 3D computational fluid dynamics simulation is performed to investigate axial and radial variation of void fraction ( α ) and flow velocity ( U ) in a pulsatile bubbly flow inside a realistic human artery (diameter: 5–20 mm, implying vessel dilatation or contraction), where liquid velocity, bubble size, and void fraction resemble DCS conditions. Results show that U and α show a core-peaking profile despite the variation of artery diameter, while 3D sharp turns yield U and α non-uniformities in the angular direction that do not affect mean void fraction across the artery. Obtained knowledge allows deeper insight on the physics and spatial characteristics of bubbly flow in a real artery, which is useful in the design of measuring volume and tuning of I-VED.

How to cite this publication

Sotiris P. Evgenidis, Thodoris Karapantsios (2024). 3D simulation of pulsatile bubbly flow resembling decompression sickness conditions inside a realistic human artery. , 6(2), DOI: https://doi.org/10.1007/s42757-023-0173-y.

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Publication Details

Type

Article

Year

2024

Authors

2

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1007/s42757-023-0173-y

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