LAPSE:2023.5220
Published Article
LAPSE:2023.5220
Automated Compartment Model Development Based on Data from Flow-Following Sensor Devices
Jonas Bisgaard, Tannaz Tajsoleiman, Monica Muldbak, Thomas Rydal, Tue Rasmussen, Jakob K. Huusom, Krist V. Gernaey
February 23, 2023
Due to the heterogeneous nature of large-scale fermentation processes they cannot be modelled as ideally mixed reactors, and therefore flow models are necessary to accurately represent the processes. Computational fluid dynamics (CFD) is used more and more to derive flow fields for the modelling of bioprocesses, but the computational demands associated with simulation of multiphase systems with biokinetics still limits their wide applicability. Hence, a demand for simpler flow models persists. In this study, an approach to develop data-based flow models in the form of compartment models is presented, which utilizes axial-flow rates obtained from flow-following sensor devices in combination with a proposed procedure for automatic zoning of volume. The approach requires little experimental effort and eliminates the necessity for computational determination of inter-compartmental flow rates and manual zoning. The concept has been demonstrated in a 580 L stirred vessel, of which models have been developed for two types of impellers with varying agitation intensities. The sensor device measurements were corroborated by CFD simulations, and the performance of the developed compartment models was evaluated by comparing predicted mixing times with experimentally determined mixing times. The data-based compartment models predicted the mixing times for all examined conditions with relative errors in the range of 3−27%. The deviations were ascribed to limitations in the flow-following behavior of the sensor devices, whose sizes were relatively large compared to the examined system. The approach provides a versatile and automated flow modelling platform which can be applied to large-scale bioreactors.
Keywords
automatic zoning, compartment model, flow-follower, hydrodynamics, Mixing, stirred bioreactor
Suggested Citation
Bisgaard J, Tajsoleiman T, Muldbak M, Rydal T, Rasmussen T, Huusom JK, Gernaey KV. Automated Compartment Model Development Based on Data from Flow-Following Sensor Devices. (2023). LAPSE:2023.5220
Author Affiliations
Bisgaard J: Freesense ApS, 2300 Copenhagen, Denmark; Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 228A, 2800 Kgs. Lyngby, Denmark
Tajsoleiman T: Freesense ApS, 2300 Copenhagen, Denmark; Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 228A, 2800 Kgs. Lyngby, Denmark
Muldbak M: Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 228A, 2800 Kgs. Lyngby, Denmark
Rydal T: Freesense ApS, 2300 Copenhagen, Denmark; Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 228A, 2800 Kgs. Lyngby, Denmark
Rasmussen T: Freesense ApS, 2300 Copenhagen, Denmark
Huusom JK: Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 228A, 2800 Kgs. Lyngby, Denmark
Gernaey KV: Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 228A, 2800 Kgs. Lyngby, Denmark [ORCID]
Journal Name
Processes
Volume
9
Issue
9
First Page
1651
Year
2021
Publication Date
2021-09-13
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr9091651, Publication Type: Journal Article
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LAPSE:2023.5220
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doi:10.3390/pr9091651
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