Industrial bioreactors featuring inadequate geometry and operating conditions may depress the effectiveness and the efficiency of the hosted bioprocess. Computational fluid dynamics (CFD) can be used to find a suitable operating match between the target bioprocess and the available bioreactor. The aim of this work is to investigate the feasibility of addressing bioreactor improvement problems in the bioprocess industry with the aid of such mainstream tools as industry-standard CFD. This study illustrates how to effectively simulate both the impeller rotation and air supply and discusses the way toward model validation at the 4.1 m3 capacity scale. Referring to experimentally measured process values, the developed full-scale model successfully predicted the power draw, liquid phase level, and mixing time with errors lower than 4.6, 1.1, and 6.7%, respectively, thus suggesting the illustrated approach as a best practice design method for the bioprocess industry. The validated model was employed to improve performance by reducing the power draw in aerated conditions with a minimal operational derating.

Industrial Case-Study-Based Computational Fluid Dynamic (CFD) Modeling of Stirred and Aerated Bioreactors

Alessio Panunzi
Primo
Investigation
;
Monica Moroni
Secondo
Investigation
;
Alessio Mazzelli
Penultimo
Membro del Collaboration Group
;
Marco Bravi
Ultimo
Supervision
2022

Abstract

Industrial bioreactors featuring inadequate geometry and operating conditions may depress the effectiveness and the efficiency of the hosted bioprocess. Computational fluid dynamics (CFD) can be used to find a suitable operating match between the target bioprocess and the available bioreactor. The aim of this work is to investigate the feasibility of addressing bioreactor improvement problems in the bioprocess industry with the aid of such mainstream tools as industry-standard CFD. This study illustrates how to effectively simulate both the impeller rotation and air supply and discusses the way toward model validation at the 4.1 m3 capacity scale. Referring to experimentally measured process values, the developed full-scale model successfully predicted the power draw, liquid phase level, and mixing time with errors lower than 4.6, 1.1, and 6.7%, respectively, thus suggesting the illustrated approach as a best practice design method for the bioprocess industry. The validated model was employed to improve performance by reducing the power draw in aerated conditions with a minimal operational derating.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11573/1652540
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