Reduced Order Model for the CFD Simulations of Stirred Bioreactors
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Continuous stirred-tank reactors are commonly used in the manufacturing of various biopharmaceuticals. A suitable environment is required for the living organism inside a bioreactor to reliably and efficiently produce the relevant compounds. Therefore, scientists often conduct various wet-lab and in-silico experiments to find the optimal values for the critical process parameters. Computational fluid dynamics is often used to compute the mixing time, hydrodynamic stress, and oxygen mass transfer coefficient. However, these simulations are computationally demanding which often prevents their full potential from being realized during the design phase. Surrogate models aim to solve this challenge by providing a computationally favorable model, but with lower accuracy and/or resolution. A potential modeling approach is the POD-Galerkin reduced order methods. The applications of this approach to complex 3D geometries are limited and not fully explored. In this work, we provide the first results on a large geometry (~3M cells) with rotational boundary conditions (using multiple reference frame).