Computational Modeling of Oxygen Transfer in Artificial Lungs

Area of Science:

• Biomedical Engineering
• Computational Fluid Dynamics (CFD)
• Respiratory Physiology

Background:

• Hemoglobin-bound oxygen transport is critical for tissue oxygenation.
• Previous CFD models for artificial lungs often overestimate oxygen transfer.
• Accurate modeling of oxygen transfer is essential for artificial lung design.

Purpose of the Study:

• To develop and validate a novel, more accurate CFD model for oxygen transfer in artificial lungs.
• To implement a two-phase blood model (plasma and red blood cells) with a source term for hemoglobin-oxygen reaction.
• To compare the novel model's performance against experimental data and existing models.

Main Methods:

• Developed a two-phase CFD model incorporating hemoglobin-oxygen reaction kinetics as a source term.
• Implemented the model using Ansys CFX 18.1.
• Validated the model against in vitro experimental data from three micro-oxygenators under various blood flow rates.

Main Results:

• The novel model showed improved accuracy in predicting oxygen transfer rates compared to previous methods.
• Model predictions had a relative difference of -23.7% and +6.3% at 20 and 90 mL/h blood flow, respectively.
• The effective diffusivity model significantly overestimated oxygen transfer, with differences up to +121.0%.

Conclusions:

• The novel two-phase CFD model offers a more accurate approach to simulating oxygen transfer in artificial lungs.
• This model has the potential to improve the design and efficiency of artificial oxygenators.
• Further validation with diverse configurations is recommended for comprehensive assessment.