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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Bioengineering |
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| Online Access: | https://www.mdpi.com/2306-5354/9/10/568 |
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| author | Katelin S. Omecinski William J. Federspiel |
| author_facet | Katelin S. Omecinski William J. Federspiel |
| author_sort | Katelin S. Omecinski |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T20:40:33Z |
| format | Article |
| id | doaj.art-24e46df367554e059697bb2f3caee25a |
| institution | Directory Open Access Journal |
| issn | 2306-5354 |
| language | English |
| last_indexed | 2024-03-09T20:40:33Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Bioengineering |
| spelling | doaj.art-24e46df367554e059697bb2f3caee25a2023-11-23T22:57:59ZengMDPI AGBioengineering2306-53542022-10-0191056810.3390/bioengineering9100568Improvement of a Mathematical Model to Predict CO<sub>2</sub> Removal in Hollow Fiber Membrane OxygenatorsKatelin S. Omecinski0William J. Federspiel1McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USAMcGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USAThe 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.https://www.mdpi.com/2306-5354/9/10/568hollow fiber membrane bundleoxygenatorextracorporeal oxygenationextracorporeal CO<sub>2</sub> removalHaldane effectartificial lung |
| spellingShingle | Katelin S. Omecinski William J. Federspiel Improvement of a Mathematical Model to Predict CO<sub>2</sub> Removal in Hollow Fiber Membrane Oxygenators Bioengineering hollow fiber membrane bundle oxygenator extracorporeal oxygenation extracorporeal CO<sub>2</sub> removal Haldane effect artificial lung |
| title | Improvement of a Mathematical Model to Predict CO<sub>2</sub> Removal in Hollow Fiber Membrane Oxygenators |
| title_full | Improvement of a Mathematical Model to Predict CO<sub>2</sub> Removal in Hollow Fiber Membrane Oxygenators |
| title_fullStr | Improvement of a Mathematical Model to Predict CO<sub>2</sub> Removal in Hollow Fiber Membrane Oxygenators |
| title_full_unstemmed | Improvement of a Mathematical Model to Predict CO<sub>2</sub> Removal in Hollow Fiber Membrane Oxygenators |
| title_short | Improvement of a Mathematical Model to Predict CO<sub>2</sub> Removal in Hollow Fiber Membrane Oxygenators |
| title_sort | improvement of a mathematical model to predict co sub 2 sub removal in hollow fiber membrane oxygenators |
| topic | hollow fiber membrane bundle oxygenator extracorporeal oxygenation extracorporeal CO<sub>2</sub> removal Haldane effect artificial lung |
| url | https://www.mdpi.com/2306-5354/9/10/568 |
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