Graphical Abstract

Project Overview

Low blood pressure drop is a critical performance metric for Hollow-Fiber Membrane Oxygenators (HFMOs). Since traditional in vitro testing often substitutes complex blood with simpler fluids, introducing inaccuracies, this project sought a highly accurate, non-experimental solution. We developed a comprehensive in silico (computational) phenomenological model to precisely predict the liquid pressure drop through cylindrical HFMOs. The model uniquely integrates both viscous and inertial resistances within the porous fiber bundle, offering a robust tool for design optimization without relying on complex fluid handling.

Major Outcomes

• Developed a novel in silico phenomenological model for accurately predicting liquid pressure drop in cylindrical HFMOs.
• The model rigorously accounts for both viscous and inertial flow resistances, providing a complete and robust description of fluid dynamics within the fiber bundle.
• Established a reliable, non-blood-based method to benchmark and predict a critical HFMO performance characteristic (pressure drop) during the design phase.
• Validated the model’s high accuracy, confirming that simulated results closely approximate experimental observations.

Paper Source

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