Real-Time CFD-based Bioreactor Models with Integrated Process Control [Webinar]

In a recent presentation by M-Star President John Thomas, the transformative potential of digital twins in reactor modeling took center stage. Thomas shed light on the significance of adopting a physics-based modeling approach, setting it apart from traditional correlation lookup tools. The focus was on solving governing equations for transport, ensuring predictions closely mirrored physical outcomes. Notably, the integration of GPU computing emerged as a game-changer, enabling the capture of transport carrier-level physics in simulations related to slurry systems, bioreactors, and diverse reactor configurations. The presentation navigated the intricate relationships between reactor design, controller configuration, and fluid properties, showcasing how digital twins accurately predicted system behavior under varying operating conditions.

Zooming into bioreactors, Thomas delved into three specific systems, providing insights into critical elements such as impeller speed, fluid volume, pH setpoints, and inline feeding control. The incorporation of feedback controller logic into simulations emerged as a pivotal factor in bridging the gap between operating conditions and precise process outcomes. The presentation underscored the strength of fully coupled simulation models, offering a mechanistically self-consistent approach for a comprehensive understanding of bioprocess dynamics. Thomas demonstrated simulations of fluid flow and bubble dynamics, leveraging GPU-based computing for efficiency. Validation against laboratory data cemented the model’s reliability, positioning digital twins as a transformative tool for optimizing bioprocesses and deciphering the complexities of reactor systems. In essence, John Thomas’s presentation unveiled the potential of digital twins in revolutionizing reactor design and control, marking a paradigm shift in the field.