The production rate of fed-batch aerobic fermenters is often limited by the oxygen transfer rate that depends on the fluid dynamics of the gas-liquid system. In turn, ideal flow regimes with homogenous distribution of the gas bubbles in the stirred fermenter are not viable, especially at large scale, due huge power requirement at increasing impeller speeds. In this work, a typical flow condition adopted in industrial multiple impeller fermenters is investigated, that leads to gas accumulation on the rear of flat blades, a reduction of the power transferred to the fluid and limitations of the volumetric mass transfer coefficient. Such fluid dynamics features, that are challenging to obtain by fully predictive methods, are well predicted by a Reynolds Averaged Two-Fluid Model and a suitable set of closure equations. The computational method is validated by experimental gas hold-up, gassed power consumption and mixing time data purposely collected in an aerated tank stirred with four Rushton turbines. The importance of the drag and turbulent dispersion forces magnitude is discussed. The calculated distribution of the oxygen transfer rate highlights the effectiveness of the simulation method as a tool for overcoming mass transfer limitations, which are often a critical step towards the fermentation intensification.

Maluta F., Paglianti A., Montante G. (2021). Two-fluids RANS predictions of gas cavities, power consumption, mixing time and oxygen transfer rate in an aerated fermenter scale-down stirred with multiple impellers. BIOCHEMICAL ENGINEERING JOURNAL, 166(February 2021), 1-12 [10.1016/j.bej.2020.107867].

Two-fluids RANS predictions of gas cavities, power consumption, mixing time and oxygen transfer rate in an aerated fermenter scale-down stirred with multiple impellers

Maluta F.
Primo
;
Paglianti A.;Montante G.
2021

Abstract

The production rate of fed-batch aerobic fermenters is often limited by the oxygen transfer rate that depends on the fluid dynamics of the gas-liquid system. In turn, ideal flow regimes with homogenous distribution of the gas bubbles in the stirred fermenter are not viable, especially at large scale, due huge power requirement at increasing impeller speeds. In this work, a typical flow condition adopted in industrial multiple impeller fermenters is investigated, that leads to gas accumulation on the rear of flat blades, a reduction of the power transferred to the fluid and limitations of the volumetric mass transfer coefficient. Such fluid dynamics features, that are challenging to obtain by fully predictive methods, are well predicted by a Reynolds Averaged Two-Fluid Model and a suitable set of closure equations. The computational method is validated by experimental gas hold-up, gassed power consumption and mixing time data purposely collected in an aerated tank stirred with four Rushton turbines. The importance of the drag and turbulent dispersion forces magnitude is discussed. The calculated distribution of the oxygen transfer rate highlights the effectiveness of the simulation method as a tool for overcoming mass transfer limitations, which are often a critical step towards the fermentation intensification.
2021
Maluta F., Paglianti A., Montante G. (2021). Two-fluids RANS predictions of gas cavities, power consumption, mixing time and oxygen transfer rate in an aerated fermenter scale-down stirred with multiple impellers. BIOCHEMICAL ENGINEERING JOURNAL, 166(February 2021), 1-12 [10.1016/j.bej.2020.107867].
Maluta F.; Paglianti A.; Montante G.
File in questo prodotto:
File Dimensione Formato  
BEJ.pdf

Open Access dal 24/01/2023

Tipo: Postprint
Licenza: Licenza per Accesso Aperto. Creative Commons Attribuzione - Non commerciale - Non opere derivate (CCBYNCND)
Dimensione 1.23 MB
Formato Adobe PDF
1.23 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/788886
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 26
  • ???jsp.display-item.citation.isi??? 24
social impact