Euler–Lagrange approach to model heterogeneities in stirred tank bioreactors – Comparison to experimental flow characterization and particle tracking

The aim of this work is the validation of an Euler–Lagrange modeling approach coupling a CFD-based compartment model (Eulerian approach) and a stochastic model based on a Continuous-Time Markov Chain (Lagrangian approach). The turbulent flow structure and the mixing process in a bioreactor stirred by an axial Mixel TT impeller is characterized by PIV and tracer experiments. Comparison between experimental and numerical data shows that the CFD-based compartment model is able to reproduce accurately the spatial heterogeneities inside the bioreactor. The trajectory of a small tracer particle which perfectly follows the fluid flow is measured by optical trajectography. It is then simulated by a stochastic model which is either based on an homogeneous or on an inhomogeneous Continuous Time Markov Chain (CTMC). Comparison of residence and circulation time distributions in three zones defined inside the bioreactor shows that the inhomogeneous CTMC model predicts with an excellent accuracy the particle trajectories inside the bioreactor. The modeling approach proposed here could be an useful tool to design scale-down bioreactors in order to reproduce at lab-scale the stress levels encountered in large-scale production bioreactors and to characterize and compare different bioreactor configurations.