CFD-based bioreactor model with proportional-integral-derivative controller functionality for dissolved oxygen and...

Area of Science:

• Biochemical Engineering
• Process Systems Engineering
• Computational Fluid Dynamics

Background:

• Accurate prediction of fluid dynamics and mass transfer is crucial for optimizing cell culture processes in bioreactors.
• Integrating process and control variables enhances bioreactor performance and stability.

Purpose of the Study:

• To develop and validate a physics-based model for predicting cell culture fluid properties within a stirred tank bioreactor.
• To incorporate Proportional-Integral-Derivative (PID) controller logic for direct coupling of process and control variables.
• To assess the model's accuracy in predicting steady-state conditions and dynamic responses to setpoint changes.

Main Methods:

• Development of a time-accurate computational model for fluid velocity fields and volumetric mass transfer coefficient.
• Inclusion of interfacial mass transfer, species mixing, and aqueous chemical reaction dynamics.
• Embedded PID controller logic for real-time simulation of system control.

Main Results:

• The model successfully predicts fluid velocity, mass transfer, mixing, and reaction kinetics.
• Demonstrated satisfactory agreement between model predictions and experimental bioreactor data.
• Validated steady-state operating conditions and dynamic responses to setpoint adjustments.

Conclusions:

• The presented physics-based model provides a reliable tool for simulating bioreactor performance.
• The integrated controller logic enables accurate prediction of coupled process and control dynamics.
• Simulation efficiency is suitable for industrial research and design applications.