Euler-Lagrange analysis towards representative down-scaling of a 22 m3 aerobic S. cerevisiae fermentation. (12th October 2017)

• Record Type: Journal Article
• Authors: Haringa, Cees; Deshmukh, Amit T.; Mudde, Robert F.; Noorman, Henk J.
• Is Part Of: Chemical engineering science. Volume 170(2017)
• Page Start: 653
• Page End: 669
• Publication Date: 2017-10-12
• Subjects: SD scale-down -- DO dissolved oxygen -- RTD residence time distribution -- PFR plug flow reactor -- STR stirred tank reactor -- MRF multiple reference frames -- DRW dynamic random walk; 76T10 -- 92-08; Industrial scale -- Euler-Lagrange -- CFD -- Scale-down -- Fermentation; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; Chemical engineering; Periodicals; Electronic journals; 660
• DOI: 10.1016/j.ces.2017.01.014
• Languages: English
• ISSNs: 0009-2509

Abstract

Graphical abstract: Highlights: We propose the scale-down simulator designs based directly on CFD data. We present a validated CFD study of a multiphase, large scale fermentor. Substrate concentration variations are monitored from the microbial point of view. Substrate gradients between fermentors with different relevant timescales are compared. Several hitherto used scale-down simulators are compared with the large scale simulation. Abstract: With reaction timescales equal to or shorter than the circulation time, the ideal mixing assumption typically does not hold for large scale bioreactors. As a consequence large scale gradients in extra-cellular conditions such as the substrate concentration exist, which may significantly impact the metabolism of micro-organisms and thereby the process performance. The influence of extra-cellular variations on the organism can be tested using so-called scale-down simulators, laboratory scale setups where deliberate, controlled fluctuations are imposed in the extra-cellular environment. The major challenge associated with this scale-down philosophy is to design a scale-down simulator that resembles the extra-cellular environment of the industrial process. Previously, Euler-Lagrange CFD was explored to investigate the large scale environment from the microbial point of view (Haringa et al., 2016a), collecting statistics of the frequency and magnitude of environmental fluctuations that can serve as a basis for scale-down design. In this work, we apply this methodology to a validated CFD simulation of a 22 m 3 aerated fermentation of S. cerevisiae, and devise possible scale-down strategies based on this CFD data, both with fluctuating feed profiles and multiple compartments. All designs are deemed feasible within the limitations of current scale-down equipment.