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Combined Respiratory Circuit-Computa...

McCay, James William.

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Combined Respiratory Circuit-Computational Fluid Dynamics Modeling of Partial Endotracheal Tube Obstruction.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Combined Respiratory Circuit-Computational Fluid Dynamics Modeling of Partial Endotracheal Tube Obstruction./
Author:	McCay, James William.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	78 p.
Notes:	Source: Masters Abstracts International, Volume: 58-01.
Contained By:	Masters Abstracts International58-01(E).
Subject:	Mechanical engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10784550
ISBN:	9780438289727

Combined Respiratory Circuit-Computational Fluid Dynamics Modeling of Partial Endotracheal Tube Obstruction.
McCay, James William.

Combined Respiratory Circuit-Computational Fluid Dynamics Modeling of Partial Endotracheal Tube Obstruction. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 78 p.

Source: Masters Abstracts International, Volume: 58-01.

Thesis (M.S.)--University of California, Davis, 2018.

Partial obstruction of endotracheal tubes due to deposited mucus during clinical mechanical ventilation is an insidious and difficult-to-detect problem that can have severe consequences for patient health. Other studies have developed techniques and algorithms for detecting obstructions, although the relationship between the models and the underlying fluid dynamics is still not well defined. This study develops specialized models to understand that relationship and evaluates their potential for further use in obstruction detection algorithms.

ISBN: 9780438289727Subjects--Topical Terms:

649730
Mechanical engineering.

Combined Respiratory Circuit-Computational Fluid Dynamics Modeling of Partial Endotracheal Tube Obstruction.
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100 1 $a McCay, James William. $3 3426705
245 1 0 $a Combined Respiratory Circuit-Computational Fluid Dynamics Modeling of Partial Endotracheal Tube Obstruction.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2018
300 $a 78 p.
500 $a Source: Masters Abstracts International, Volume: 58-01.
500 $a Adviser: Jean-Pierre Delplanque.
502 $a Thesis (M.S.)--University of California, Davis, 2018.
520 $a Partial obstruction of endotracheal tubes due to deposited mucus during clinical mechanical ventilation is an insidious and difficult-to-detect problem that can have severe consequences for patient health. Other studies have developed techniques and algorithms for detecting obstructions, although the relationship between the models and the underlying fluid dynamics is still not well defined. This study develops specialized models to understand that relationship and evaluates their potential for further use in obstruction detection algorithms.
520 $a Computational fluid dynamics (CFD) and computed tomography (CT) x-ray scans were used to construct models of the flow within clean (the optimal, unobstructed state) and mucus-obstructed endotracheal tubes in an in-vitro experiment. Ventilator flow rate readings were verified and the contribution of an endotracheal tube to total respiratory resistance was calculated.
520 $a A circuit model of the respiratory system was developed for comparison to the CFD model. The model was based on a simple inductance (L), resistance (R), and compliance (C) circuit but incorporated nonlinear coefficients for L, R, and C to compare with the nonlinear relationships expected in the CFD model. It was formulated so that the coefficients developed their own functional forms. The resulting model effectively related flow rate to the ventilator circulation pressure with resistance coefficient trends that compared well with the CFD model's trends. Different tube sizes and levels of obstruction could be clearly distinguished. The compliance coefficient also agreed with expected values.
520 $a In its current form, the circuit model is limited to pressure control breaths as it relies on specific regions in a breath that are not present in volume control. However, data derived from a pressure control breath can be used to reconstruct volume control breaths, and there may be ways to extend the derivation algorithm to other ventilator modes. A next step is application to clinical data and development towards an obstruction detection algorithm.
590 $a School code: 0029.
650 4 $a Mechanical engineering. $3 649730
650 4 $a Fluid mechanics. $3 528155
650 4 $a Biomedical engineering. $3 535387
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710 2 $a University of California, Davis. $b Mechanical and Aerospace Engineering. $3 3190211
773 0 $t Masters Abstracts International $g 58-01(E).
790 $a 0029
791 $a M.S.
792 $a 2018
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10784550