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You are here: Home / Seminars / Experimental physics and modelling / Gas transport during high-frequency ventilation

Gas transport during high-frequency ventilation

Chinthaka Jacob (CBP / LPENSL)
When May 14, 2024
from 11:00 to 12:00
Where Salle des thèses
Contact Name Louis Couston
Attendees Chinthaka Jacob
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High-frequency ventilation (HFV) is a medical ventilation technique that uses fast yet shallow inflations, resulting in small peak pressures, thereby protecting lungs from over-distension. While several mechanisms have been proposed for gas transport during HFV, this process is still not well understood and it is likely the treatment as it stands is sub-optimal. Nonlinear mean streaming and turbulent diffusion are two mechanisms with the potential to be further exploited for gas transport, and the work presented in this talk aims to characterize and quantify these mechanisms in geometries, and at parameters, which are relevant to the application of HFV.


  The first outcome of this work is the quantification of these two mechanisms in a 1:2, or single-generation, bifurcating tube. We have shown that the generation of Dean vortices controls the recirculating flux due to nonlinear mean streaming and the onset of conditional turbulence. A second outcome is the quantification of these same mechanisms in a 1:2:4, or multi-generation, bifurcating tube, to systematically study and quantify the impact of coupling the flows between generations.

  For both the single and double bifurcation models, this is achieved by performing direct numerical simulations of the reciprocating flows inside the bifurcating tube. The geometries of the models are constructed to model a portion of the approximately self-similar human airway so that the flow in different portions can be modeled by simply changing model parameters. This allows these findings to quantify the role of these gas transport mechanisms in the entire airway.

  Finally, the overview of a flow-splitting algorithm is presented to highlight its use in combining numerical simulations with clinical measurements.