Dr.-Ing. Marko Hoffmann

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  • Construction and Apparatus Engineering
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Title: Lagrangian sensors in a stirred tank reactor: Comparing trajectories from 4D-Particle Tracking Velocimetry and Lattice-Boltzmann simulations.
Written by: Hofmann, S.; Weiland, C.; Fitschen, J.; von Kameke, A., Hoffmann, M.; Schlüter, M.
in: <em>Chemical Engineering Journal</em>. (2022).
Volume: <strong>449</strong>. Number:
on pages:
how published:
DOI: https://doi.org/10.1016/j.cej.2022.137549


Abstract: In this study, three-dimensional flow measurements by means of 4D-Particle Tracking Velocimetry (4D-PTV) are carried out in a laboratory-scale 3 L stirred tank reactor in order to investigate the flow-following behavior of two different inertial particle types, Polyethylene (PE) particles and alginate beads, at different impeller frequencies. Applied particles mimic Lagrangian sensor particles, which are intended to determine process parameters such as oxygen concentration at their corresponding position inside a bioreactor. Accompanying Lattice-Boltzmann Large Eddy Simulations (LB LES) provide additional information about the fluid flow and the difference in the trajectories between inertial and non-inertial particles. The data acquired from LB LES is validated with the experimental data by means of a Lagrangian and a Eulerian approach. In their tail, the probability distributions show higher Lagrangian velocities and accelerations for 4D-PTV data compared to LB LES data. Time-averaged Eulerian data is utilized to determine particle Reynolds numbers lower than 200. The Stokes number distributions show 10-fold higher values for the alginate beads than for PE particles, however, both particle types do not sufficiently meet the criterion of a flow-following Stokes number of St≤0.01. Generally, time-averaged results from LB LES are in good accordance to the 4D-PTV data. From the LB LES, a theoretical, maximum particle diameter of approx. 20 μm is determined, which meets the criterion of St≤0.01 throughout the reactor. This result implies that with current sensor particle technology it is not possible to meet the flow-following behavior and depict the lifelines of cells during a cultivation process. Therefore, further research is necessary to understand particle trajectories and to translate them into lifelines of cells.