CFD-based compartment model for description of mixing in bioreactors

被引:91
作者
Delafosse, Angelique [1 ,2 ]
Collignon, Marie-Laure [1 ,2 ]
Calvo, Sebastien [1 ]
Delvigne, Frank [3 ]
Crine, Michel [1 ]
Thonart, Philippe [3 ]
Toye, Dominique [1 ]
机构
[1] Univ Liege, Chem Engn Lab, B-4000 Liege, Belgium
[2] Fonds Rech Sci FRS FNRS, B-1000 Brussels, Belgium
[3] Univ Liege, Unite Bioind CWBI, Gembloux Agrobio Tech, B-5030 Gembloux, Belgium
关键词
Bioreactor; Stirred tank; Mixing; CFD; Compartment model; Model comparison; HYBRID MULTIZONAL/CFD MODELS; LARGE-SCALE BIOREACTORS; MASS-TRANSFER; GENERAL METHODOLOGY; STIRRED-TANK; REACTOR; FLOW; SIMULATIONS; IMPELLER; FERMENTER;
D O I
10.1016/j.ces.2013.11.033
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
In most bioprocesses, it is fundamental to accurately predict the hydrodynamics behavior of bioreactors of different size and its interaction with the biological reaction. Computational Fluid Dynamics can provide detailed modeling about hydrodynamics and mixing. However, it is computationally intensive, especially when reactions are taken into account. Another way to predict hydrodynamics is the use of "Compartment" or "Network-of-zones" model which are much less demanding in computation time than CFD. However, compartments and fluxes between them are often defined by considering global quantities not representative of the flow complexity. To overcome the limitations of these two methods, a solution is to combine compartment modeling and CFD simulations. The aim of this study is to propose a compartment model where the flow rates between two adjacent compartments are easily computed From the velocity fields obtained by CFD. The mixing evolution predicted by the CFD-based compartment model have been then compared with mixing experiment results. Unlike a CFD mixing simulation and a classical compartment model, the CFD-based compartment model proposed in this work reproduces with a good accuracy the spatial distribution of concentrations during the mixing process and this, without any adjustable parameters. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:76 / 85
页数:10
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