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Record W7046416021

Design and optimization of a microporous hollow fibre blood oxygenator

2023· dissertation· en· W7046416021 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2023
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersMcGill University
KeywordsMicroporous materialOxygenatorFiberExtrusion
DOInot available

Abstract

fetched live from OpenAlex

Extracorporeal blood oxygenators are used to oxygenate the blood during open-heart surgery.The main goal of the project is designing an oxygenator consisting of a hollow fibre membrane.The hollow fibre microporous oxygenator consists of porous fibres conducting an oxygen flow.As blood flows over and inside this hollow fibre bundle, the oxygen diffuses from the gas phase through the gas-filled membrane pores into the blood, and the carbon dioxide goes back into the fibres.Reliable modeling of this phenomenon is essential for the prediction of gas transfer performance, allowing for development of an efficient blood oxygenator.Our focus is on the optimization of this bundle.We want to increase the gas transfers by varying the configuration of the fibres.To achieve our goals, we will first define an initial geometry of the bundle using biomechanical concepts and equations, assessing parameters like the oxygen transfer rate, the blood pressure drop in the bundle, the priming volume, and the effective surface of contact to give a first estimation of the definition of the bundle.We will then conduct Computational Fluid Dynamic (CFD) simulation testing through the use of software such as ANSYS Fluent.A simple model is first studied in ANSYS, consisting of an outer casing and 197 hollow fibres going through it.The casing is filled with blood.All the sections are set as fluid sections, as the hollow fibres are porous itself.The fluid is set as laminar.After basic validation of this simplified model, resulting in efficiency factors in the same order of magnitude as market oxygenators, the efficiency of the model is studied for different input parameters.An increase in blood flow rate from 1 to 5 L/min increases the oxygen transfer rate efficiency by 20%, but decreases the pressure drop efficiency by 82%.Increasing the amount of swirl (up to rotational speeds of 837.75 rad/s) in the bundle increases the oxygen transfer rate efficiency by 142%, with a decrease in the pressure drop efficiency of 23%.Doubling the fibre outer diameter and tripling the total number of fibres does not make the bundle more efficient, only decreasing the pressure drop efficiency over 85%.This feasibility study generates a starting point for future device development.iii ABSTRAIT Les oxygénateurs sanguins extracorporels sont utilisés afin d'oxygéner le sang pendant les opérations à cœur ouvert.L'objectif principal de ce projet est de concevoir un oxygénateur constitué d'une membrane en fibres creuses.L'oxygénateur microporeux à fibres creuses est constitué de fibres poreuses conduisant un flux d'oxygène.Lorsque le sang circule sur et à l'intérieur de ce faisceau de fibres creuses, l'oxygène diffuse de la phase gazeuse à travers les pores de la membrane remplis de gaz vers le sang, et le dioxyde de carbone retourne dans les fibres.Une modélisation fiable de ce phénomène est essentielle pour la prédiction des performances de transfert de gaz, permettant le développement d'un oxygénateur sanguin efficace.Nous nous concentrons sur l'optimisation de ce faisceau.Nous voulons augmenter les transferts de gaz en faisant varier la configuration des fibres.Pour atteindre nos objectifs, nous définirons d'abord une géométrie initiale du faisceau en utilisant des concepts et des équations biomécaniques, en évaluant des paramètres tels que le taux de transfert d'oxygène, la chute de pression sanguine dans le faisceau, le volume sanguin total et l'aire de l'interface d'échange pour donner une première estimation de la définition du faisceau.Nous effectuerons ensuite des tests de simulation de Méchanique des Fluides Numérique (MFN) à l'aide de logiciels tels que ANSYS Fluent.Un modèle simple est d'abord étudié dans ANSYS, composé d'une enveloppe extérieure et de 197 fibres creuses la traversant.L'enveloppe est remplie de sang.Toutes les sections sont définies comme des sections de fluide, car les fibres creuses sont elles-mêmes poreuses.Le fluide est défini comme laminaire.Après la validation de base de ce modèle simplifié, qui donne des facteurs d'efficacité du même ordre de grandeur que les oxygénateurs du marché, l'efficacité du modèle est étudiée pour différents paramètres d'entrée.Une augmentation du débit sanguin de 1 à 5 L/min augmente l'efficacité du taux de transfert d'oxygène de 20 %, mais diminue l'efficacité de la chute de pression de 82 %.L'augmentation de la quantité de tourbillon (jusqu'à des vitesses de rotation de 837,75 rad/s) dans le faisceau augmente l'efficacité du taux de transfert d'oxygène de 142 %, avec une diminution de l'efficacité de la chute de pression de 23 %.Doubler le diamètre extérieur des fibres et tripler le nombre total de fibres ne rend pas le faisceau plus efficace, mais diminue l'efficacité de la chute de pression de plus de 85 %.Cette étude de faisabilité constitue un point de départ pour le développement ultérieur du dispositif.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.242
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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