Chronic respiratory diseases claim nearly four million lives annually, making them
the third leading cause of death worldwide. Extracorporeal membrane oxygenation (ECMO)
is often the last line of support for patients with severe lung failure. Still, its
performance is limited by an incomplete understanding of gas exchange in hollow fiber
membrane (HFM) oxygenators. Computational fluid dynamics (CFD) has become a robust
oxygenator design and optimization tool. However, most models oversimplify O2 and
CO2 transport by ignoring their physiological coupling, instead relying on fixed saturation
curves or constant-content assumptions. For the first time, this study introduces
a novel physiologically informed CFD model that integrates the Bohr and Haldane effects
to capture the coupled transport of oxygen and carbon dioxide as functions of local
pH, temperature, and gas partial pressures. The model is validated against in vitro
experimental data from the literature and assessed against established CFD models.
The proposed CFD model achieved excellent agreement with experiments across blood
flow rates (100-500 mL/min ), with relative errors below 5% for oxygen and 10-15%
for carbon dioxide transfer. These results surpassed the accuracy of all existing
CFD approaches, demonstrating that a carefully formulated single-phase model combined
with physiologically informed diffusivities can outperform more complex multiphase
simulations. This work provides a computationally efficient and physiologically realistic
framework for oxygenator optimization, potentially accelerating device development,
reducing reliance on costly in vitro testing, and enabling patient-specific simulations.
