Improvement of a Mathematical Model to Predict CO<sub>2</sub> Removal in Hollow Fiber Membrane Oxygenators
The use of extracorporeal oxygenation and CO<sub>2</sub> removal has gained clinical validity and popularity in recent years. These systems are composed of a pump to drive blood flow through the circuit and a hollow fiber membrane bundle through which gas exchange is achieved. Mathematic...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Bioengineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2306-5354/9/10/568 |
| Summary: | The use of extracorporeal oxygenation and CO<sub>2</sub> removal has gained clinical validity and popularity in recent years. These systems are composed of a pump to drive blood flow through the circuit and a hollow fiber membrane bundle through which gas exchange is achieved. Mathematical modeling of device design is utilized by researchers to improve device hemocompatibility and efficiency. A previously published mathematical model to predict CO<sub>2</sub> removal in hollow fiber membrane bundles was modified to include an empirical representation of the Haldane effect. The predictive capabilities of both models were compared to experimental data gathered from a fiber bundle of 7.9 cm in length and 4.4 cm in diameter. The CO<sub>2</sub> removal rate predictions of the model including the Haldane effect reduced the percent error between experimental data and mathematical predictions by up to 16%. Improving the predictive capabilities of computational fluid dynamics for the design of hollow fiber membrane bundles reduces the monetary and manpower expenses involved in designing and testing such devices. |
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| ISSN: | 2306-5354 |