Computational fluid dynamics (CFD) provides a flexible tool for investigation of separation processes within membrane hollow fiber modules. By enabling a three-dimensional and time dependent description of the corresponding transport phenomena, very detailed information about mass transfer or geometrical influences can be provided. The high level of detail comes with high computational costs, especially since species transport simulations must discretize and resolve steep gradients in the concentration polarization layer at the membrane. In contrast, flow simulations are not required to resolve these gradients. Hence, there is a large gap in the scale and complexity of computationally feasible geometries when comparing flow and species transport simulations. A method, which tries to cover the mentioned gap, is presented in the present article. It allows upscaling of the findings of species transport simulations, conducted for reduced geometries, on the geometrical scales of flow simulations. Consequently, total transmembrane transport of complete modules can be numerically predicted. The upscaling method does not require any empirical correlation to incorporate geometrical characteristics but solely depends on results acquired by CFD flow simulations. In the scope of this research, the proposed method is explained, conducted, and validated. This is done by the example of CO2 removal in a prototype hollow fiber membrane oxygenator.

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CO2 removal via membrane oxygenators during lung protective ventilation has become a reliable clinical technique. For further optimization of oxygenators, accurate prediction of the CO2 removal rate is necessary. It can either be determined by measuring the CO2 content in the exhaust gas of the oxygenator (sweep flow-based) or using blood gas analyzer data and a CO2 solubility model (blood-based). In this study, we determined the CO2 removal rate of a prototype oxygenator utilizing both methods in in vitro trials with bovine and in vivo trials with porcine blood. While the sweep flow-based method is reliably accurate, the blood-based method depends on the accuracy of the solubility model. In this work, we quantified performances of four different solubility models by calculating the deviation of the CO2 removal rates determined by both methods. Obtained data suggest that the simplest model (Loeppky) performs better than the more complex ones (May, Siggaard-Anderson, and Zierenberg). The models of May, Siggaard-Anderson, and Zierenberg show a significantly better performance for in vitro bovine blood data than for in vivo porcine blood data. Furthermore, the suitability of the Loeppky model parameters for bovine blood (in vitro) and porcine blood (in vivo) is evaluated.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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