How Computational Modeling can Help to Predict Gas Transfer in Artificial Lungs Early in the Design Process

Andreas Kaesler* (Corresponding Author), Marius Rosen, Peter C. Schlanstein, Georg Wagner, Sascha Groß-Hardt, Thomas Schmitz-Rode, Ulrich Steinseifer, Jutta Arens

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)

Abstract

Wearable extracorporeal membrane oxygenation (ECMO) circuits may soon become a viable alternative to conventional ECMO treatment. Common device-induced complications, however, such as blood trauma and oxygenator thrombosis, must first be addressed to improve long-term reliability, since ambulatory patients cannot be monitored as closely as intensive care patients. Additionally, an efficient use of the membrane surface can reduce the size of the devices, priming volume, and weight to achieve portability. Both challenges are linked to the hemodynamics in the fiber bundle. While experimental test methods can often only provide global and time-averaged information, computational fluid dynamics (CFD) can give insight into local flow dynamics and gas transfer before building the first laboratory prototype. In this study, we applied our previously introduced micro-scale CFD model to the full fiber bundle of a small oxygenator for gas transfer prediction. Three randomized geometries as well as a staggered and in-line configuration were modeled and simulated with Ansys CFX. Three small laboratory oxygenator prototypes were built by stacking fiber segments unidirectionally with spacers between consecutive segments. The devices were tested in vitro for gas transfer with porcine blood in accordance with ISO 7199. The error of the predicted averaged CFD oxygen saturations of the random 1, 2, and 3 configurations relative to the averaged in-vitro data (over all samples and devices) was 2.4%, 4.6%, 3.1%, and 3.0% for blood flow rates of 100, 200, 300, and 400 ml/min, respectively. While our micro-scale CFD model was successfully applied to a small oxygenator with unidirectional fibers, the application to clinically relevant oxygenators will remain challenging due to the complex flow distribution in the fiber bundle and high computational costs. However, we will outline our future research priorities and discuss how an extended mass transfer correlation model implemented into CFD might enable an a priori prediction of gas transfer in full size oxygenators.
Original languageEnglish
Pages (from-to)683-690
Number of pages8
JournalASAIO Journal
Volume66
Issue number6
Early online dateNov 2019
DOIs
Publication statusPublished - Jun 2020

Keywords

  • artificial lung
  • gas transfer modeling
  • gas transfer prediction
  • micro-scale CFD model
  • oxygenator

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