化工学报 ›› 2022, Vol. 73 ›› Issue (6): 2698-2707.doi: 10.11949/0438-1157.20220089

• 催化、动力学与反应器 • 上一篇    下一篇

基于介尺度PBM模型的生物反应器放大模拟及实验研究

万景1(),张霖2,樊亚超2,刘勰民1,骆培成3,张锋1(),张志炳1   

  1. 1.南京大学化学化工学院,江苏 南京 210023
    2.中国石化大连石油化工研究院,辽宁 大连 116045
    3.东南大学化学化工学院,江苏 南京 211189
  • 收稿日期:2022-01-17 修回日期:2022-03-31 出版日期:2022-06-05 发布日期:2022-06-30
  • 通讯作者: 张锋 E-mail:1146866379@qq.com;zf@nju.edu.cn
  • 作者简介:万景(1998—),男,硕士研究生,1146866379@qq.com
  • 基金资助:
    国家自然科学基金项目(21776122);中国石油化工股份有限公司大连石油化工研究院合作项目(418012-3)

Bioreactor scale-up simulation and experimental study based on mesoscale PBM model

Jing WAN1(),Lin ZHANG2,Yachao FAN2,Xiemin LIU1,Peicheng LUO3,Feng ZHANG1(),Zhibing ZHANG1   

  1. 1.School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, Jiangsu, China
    2.Dalian Research Institute of Petroleum and Petrochemicals, SINOPEC, Dalian 116045, Liaoning, China
    3.School of Chemistry and Chemical Engineering, Southeast University, Nanjing 211189, Jiangsu, China
  • Received:2022-01-17 Revised:2022-03-31 Published:2022-06-05 Online:2022-06-30
  • Contact: Feng ZHANG E-mail:1146866379@qq.com;zf@nju.edu.cn

摘要:

对于通气搅拌式工业生物反应器的放大设计而言,精确预测气泡尺寸和体积传质系数非常重要,因此需要建立合适的气泡聚并和破碎模型,以保证反应器的高效操作。以5 L通气搅拌式生物反应器为对象,以气泡尺寸和体积传质系数的实验数据为基准,模拟并考察了两种聚并模型和四种破碎模型对生物反应器内流体流动行为以及传质能力的影响。结果表明,基于介尺度理论的修正聚并模型与考虑黏流剪切的破碎模型组合,所得模拟结果与实验数据吻合最好,这为大型生物反应器的桨型优化提供了模型基础。因为工业化生物发酵通常是在大型生物反应器中进行,搅拌桨型对生物反应器效能至关重要,故本研究在选定最优气泡聚并破碎模型的基础上,通过叶轮末端剪切力相等的放大原则将5 L通气搅拌式工业生物反应器放大到400 m3,同时考察了六斜叶圆盘搅拌桨、非对称式抛物线搅拌桨、布鲁马金式搅拌桨以及六直叶圆盘搅拌桨等桨型组合对气泡破碎能力和气体分散效果的影响,并通过综合对比气含率、体积传质系数等参数,得到400 m3通气搅拌式生物反应器的最优桨型组合。

关键词: 生物反应器, 计算流体力学, 放大设计, 聚并模型, 破碎模型, 优化设计

Abstract:

Accurate prediction of bubble size and volumetric mass transfer coefficient is very important for the scale-up design of aerated-stirred industrial bioreactors, and thus it is necessary to establish a suitable bubble coalescence and breakup model to ensure the efficient operation of the reactor. In this work, taking a 5 L aerated agitated bioreactor as a sample, and based on experimental data of bubble size and volumetric mass transfer coefficient, the effects of two coalescence models and five breakup models on the simulated flow behavior and mass transfer capacity were investigated. The results show that the combined simulation results of the modified coalescence model proposed based on the mesoscale and the breakup model considering viscous shear are in the best agreement with the experimental data, this provides a model basis for the paddle type optimization of large bioreactors. Because industrial bio-fermentation is usually carried out in large bioreactors, where the stirring paddle type is crucial to the bioreactor efficiency, this paper enlarges the 5 L aerated stirred industrial bioreactor to 400 m3 by the principle of equal terminal shearing force of the impeller on the basis of the optimal bubble aggregation and fragmentation model, and the influence of the combination of six-vertical-leaf disk turbine impellers, asymmetric parabolic impellers, Blumarkin impellers and six straight-blade disk turbine impellers on the bubble breaking capacity and gas dispersion effect were discussed. The optimal model combination is further used to optimize the stirring paddle type of a 400 m3 large-scale industrial bioreactor, meanwhile, the optimal combination of 400 m3 aeration-stirred bioreactor is obtained by comprehensively comparing multiple parameters such as gas holdup and volumetric mass transfer coefficient.

Key words: bioreactors, computational fluid dynamics, scale-up design, coalescence model, breakup model, optimal design

中图分类号: 

  • TQ 021.4

图1

生物反应器实验装置"

表1

本文研究的聚并模型详细信息"

聚并模型简称聚并模型
C1Luo
C2Mc-Luo

表2

本文研究的破碎模型详细信息"

破碎模型简称碰撞频率
B1ω1
B2ω2+ω3
B3ω2+ω4
B4ω5

图2

网格数量对模拟kLa和d32的影响"

图3

0、200、300、400 r/min的气泡图(a); 不同模型不同转速下的平均直径(b)"

图4

最优模型组合下不同转速的气泡直径分布"

图5

DO值随时间的变化曲线(a)和拟合曲线(b),不同模型组合在不同转速下的kLa(c)"

表3

不同实验次数下kLa随转速的变化情况"

试验次数传质系数kLa
200 r/min300 r/min400 r/min
第一次0.01550.02420.0384
第二次0.01530.02370.0378
第三次0.01580.02440.0387

图6

最优模型组合下不同转速的体积传质系数分布"

图7

400 m3生物反应器桨型组合"

图8

400 m3生物反应器不同桨型气含率分布"

图9

400 m3生物反应器kLa分布"

8 Yang N, Xiao Q. A mesoscale approach for population balance modeling of bubble size distribution in bubble column reactors[J]. Chemical Engineering Science, 2017, 170: 241-250.
9 肖颀, 杨宁. 基于EMMS模型的搅拌釜内气液两相流数值模拟[J]. 化工学报, 2016, 67(7): 2732-2739.
Xiao Q, Yang N. Numerical simulation of gas-liquid flow in stirred tanks based on EMMS model[J]. CIESC Journal, 2016, 67(7): 2732-2739.
10 Luo H A, Svendsen H F. Theoretical model for drop and bubble breakup in turbulent dispersions[J]. AIChE Journal, 1996, 42(5): 1225-1233.
11 Han L C, Luo H A, Liu Y J. A theoretical model for droplet breakup in turbulent dispersions[J]. Chemical Engineering Science, 2011, 66(4): 766-776.
12 Han L C, Gong S G, Li Y Q, et al. Influence of energy spectrum distribution on drop breakage in turbulent flows[J]. Chemical Engineering Science, 2014, 117: 55-70.
13 Han L C, Gong S G, Ding Y W, et al. Consideration of low viscous droplet breakage in the framework of the wide energy spectrum and the multiple fragments[J]. AIChE Journal, 2015, 61(7): 2147-2168.
14 Solsvik J, Tangen S, Jakobsen H A. On the constitutive equations for fluid particle breakage[J]. Reviews in Chemical Engineering, 2013, 29(5): 241-356.
15 Shi W B, Yang X G, Sommerfeld M, et al. Modelling of mass transfer for gas-liquid two-phase flow in bubble column reactor with a bubble breakage model considering bubble-induced turbulence[J]. Chemical Engineering Journal, 2019, 371: 470-485.
16 Luo P, Wu J, Pan X, et al. Gas-liquid mass transfer behavior in a surface-aerated vessel stirred by a novel long-short blades agitator[J]. AIChE Journal, 2016, 62(4): 1322-1330.
17 Martínez-Delgadillo S A, Alonzo-Garcia A, Mendoza-Escamilla V X, et al. Analysis of the turbulent flow and trailing vortices induced by new design grooved blade impellers in a baffled tank[J]. Chemical Engineering Journal, 2019, 358: 225-235.
18 Mule G M, Kulkarni A A. Mixing of medium viscosity liquids in a stirred tank with fractal impeller[J]. Theoretical Foundations of Chemical Engineering, 2016, 50(6): 914-921.
1 Straathof A J J, Wahl S A, Benjamin K R, et al. Grand research challenges for sustainable industrial biotechnology[J]. Trends in Biotechnology, 2019, 37(10): 1042-1050.
2 Amer B, Baidoo E E K. Omics-driven biotechnology for industrial applications[J]. Frontiers in Bioengineering and Biotechnology, 2021, 9: 613307.
19 Gaddis E S. Mass transfer in gas-liquid contactors[J]. Chemical Engineering and Processing: Process Intensification, 1999, 38(4/5/6): 503-510.
20 Montante G, Horn D, Paglianti A. Gas-liquid flow and bubble size distribution in stirred tanks[J]. Chemical Engineering Science, 2008, 63(8): 2107-2118.
21 Khopkar A R, Rammohan A R, Ranade V V, et al. Gas-liquid flow generated by a Rushton turbine in stirred vessel: CARPT/CT measurements and CFD simulations[J]. Chemical Engineering Science, 2005, 60(8/9): 2215-2229.
22 Sanyal J, Vásquez S, Roy S, et al. Numerical simulation of gas-liquid dynamics in cylindrical bubble column reactors[J]. Chemical Engineering Science, 1999, 54(21): 5071-5083.
23 van Baten J M, Krishna R. CFD simulations of a bubble column operating in the homogeneous and heterogeneous flow regimes[J]. Chemical Engineering & Technology, 2002, 25(11): 1081-1086.
24 Schiller L, Naumann A. A drag coefficient correlation[J]. Zeitschrift des Vereins Deutscher Ingenieure, 1935, 77: 318-320.
25 Orszag S A, Yakhot V, Flannery W S, et al. Renormalization group modeling and turbulence simulations[C]// Proceedings of International Conference on Near-Wall Turbulent Flows. 1993.
26 Prince M J, Blanch H W. Bubble coalescence and break-up in air-sparged bubble columns[J]. AIChE Journal, 1990, 36(10): 1485-1499.
27 Wang T F, Wang J F, Jin Y. A novel theoretical breakup kernel function for bubbles/droplets in a turbulent flow[J]. Chemical Engineering Science, 2003, 58(20): 4629-4637.
28 Garcia-Ochoa F, Gomez E. Bioreactor scale-up and oxygen transfer rate in microbial processes: an overview[J]. Biotechnology Advances, 2009, 27(2): 153-176.
29 Danckwerts P V. Significance of liquid-film coefficients in gas absorption[M]//Insights Into Chemical Engineering. Amsterdam: Elsevier, 1981: 51-75.
30 Kerdouss F, Bannari A, Proulx P, et al. Two-phase mass transfer coefficient prediction in stirred vessel with a CFD model[J]. Computers & Chemical Engineering, 2008, 32(8): 1943-1955.
31 Xiao H, Geng S J, Chen A Q, et al. Bubble formation in continuous liquid phase under industrial jetting conditions[J]. Chemical Engineering Science, 2019, 200: 214-224.
3 Maluta F, Paglianti A, Montante G. Modelling of biohydrogen production in stirred fermenters by computational fluid dynamics[J]. Process Safety and Environmental Protection, 2019, 125: 342-357.
4 Wang H N, Jia X Q, Wang X, et al. CFD modeling of hydrodynamic characteristics of a gas-liquid two-phase stirred tank[J]. Applied Mathematical Modelling, 2014, 38(1): 63-92.
5 Shen X Z, Hibiki T. Bubble coalescence and breakup model evaluation and development for two-phase bubbly flows[J]. International Journal of Multiphase Flow, 2018, 109: 131-149.
6 Zhang X B, Luo Z H. Effects of bubble coalescence and breakup models on the simulation of bubble columns[J]. Chemical Engineering Science, 2020, 226: 115850.
7 Luo H. Coalescence, breakup and liquid circulation in bubble column reactors[D]. Trondheim: Norwegian Institute of Technology, 1993.
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