An Automatic Method for Generation of CFD-Based 3D Compartment Models: Towards Real-Time Mixing Simulations

Area of Science:

• Chemical Engineering
• Bioprocess Engineering
• Computational Fluid Dynamics (CFD)

Background:

• Accurate modeling of large-scale reactors is crucial for optimizing bioprocesses.
• Simplifying complex mixing phenomena while retaining key interactions is a significant challenge.
• Computational Fluid Dynamics (CFD) provides detailed but computationally intensive simulations.

Purpose of the Study:

• To develop an automated method for generating compartment models from CFD data.
• To simplify complex mixing and reaction dynamics in large-scale bioreactors.
• To enable real-time prediction capabilities for bioprocesses.

Main Methods:

• Converting CFD simulation results into mass balance equations for compartment models.
• Applying a compartmentalization technique to different bioreactor geometries.
• Coupling the generated compartment models with Monod-type biokinetic models.

Main Results:

• The generated compartment models successfully replicated CFD-simulated tracer mixing profiles.
• Substrate gradients were shown to significantly impact biokinetics, especially at larger scales.
• The coupled model achieved faster-than-real-time simulation speeds for fermentation processes.

Conclusions:

• The automated generation of CFD-based compartment models offers a viable simplification strategy.
• These models accurately capture essential reactor dynamics and are scalable.
• The real-time simulation capability is vital for digital twin and predictive applications in bioprocessing.