Preprint Article Version 1 This version is not peer-reviewed

Modeling the Separation of Microorganisms in Bioprocesses by Flotation

Version 1 : Received: 22 August 2018 / Approved: 22 August 2018 / Online: 22 August 2018 (11:58:12 CEST)

A peer-reviewed article of this Preprint also exists.

Schmideder, S.; Kirse, C.; Hofinger, J.; Rollié, S.; Briesen, H. Modeling the Separation of Microorganisms in Bioprocesses by Flotation. Processes 2018, 6, 184. Schmideder, S.; Kirse, C.; Hofinger, J.; Rollié, S.; Briesen, H. Modeling the Separation of Microorganisms in Bioprocesses by Flotation. Processes 2018, 6, 184.

Journal reference: Processes 2018, 6, 184
DOI: 10.3390/pr6100184

Abstract

Bioprocesses for the production of renewable energies and materials lack efficient separation processes for the utilized microorganisms such as algae and yeasts. Dissolved air flotation (DAF) and microflotation are promising approaches to overcome this problem. The efficiency of these processes depends on the ability of microorganisms to aggregate with microbubbles in the flotation tank. In this study, different new or adapted aggregation models for microbubbles and microorganisms are compared and investigated for their range of suitability to predict the separation efficiency of microorganisms from fermentation broths. The complexity of the heteroaggregation models range from an algebraic model to a 2D population balance model (PBM) including the formation of clusters containing several bubbles and microorganisms. The effect of bubble and cell size distributions on the flotation efficiency is considered by applying PBMs, as well. To determine the impact of the model assumptions, the modeling approaches are compared and classified for their range of applicability. Evaluating computational fluid dynamics (CFD) of a DAF system shows the heterogeneity of the fluid dynamics in the flotation tank. Since analysis of the streamlines of the tank show negligible backmixing, the proposed aggregation models are coupled to the CFD data by applying a Lagrangian approach.

Subject Areas

flotation; separation of microorganisms; bioseparation; heteroaggregation; population balance modeling; coupling of aggregation and CFD; model comparison

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