基于生物反应器内非均匀环境的流体动力学研究
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摘要
现代生物技术应用需要大量低成本、高质量的产品。而产品的获得必须以实验室规模的生物过程准确放大到工业级规模为前提。但准确放大往往由于放大效应而难以实现,其中一个主要的表现就是反应器内环境的非均匀分布。因此本文的主要研究方向就是基于反应器内非均匀环境的流体动力学研究。为了消除反应器内的非均匀环境,本文采取了两种研究方式。
在200L冷模反应器中,通过将计算流体力学(Computational Fluid Dynamics, CFD)模拟与实际测定相结合,优化得到了八种能够消除反应器内环境梯度,功率消耗较低、气液分散特性较好的气液两相搅拌系统。
本文还采用了Scale-down方法,通过构建Scale-down反应器来模拟工业级反应器内的非均匀环境。实验中通过测定Scale-down系统中的混合时间及停留时间分布等流体动力学参数,对系统的流体动力学特性有了初步了解。混合实验结果表明,混合时间受循环流量和PFR形式的影响较大。增大循环流量、PFR部分体积或者采用较小的管径均有利于保持PFR中平推流特性。在数据处理中,通过引入虚拟体积(Vvrit)本文对所得混合时间数据进行拟合,对混合时间特性进行了深入的分析。停留时间分布在验证了系统内存在死区或者返混情况的同时,表明PFR内的流体动力学特性受循环流量和管径的影响较大。但由于PFR体积与系统体积相比较小,所以在停留时间分布测定中表现出PFR部分差异对系统流体动力学特性影响较小的特点。在实验测定的基础上,本文对Scale-down内的流场及流体动力参数进行了CFD模拟验证。模拟结果表明实验中所得数据及结论真实有效,为后期的发酵试验提供了坚实的理论基础。
Present biotechnological applications demand large amounts of low-cost and high-quality products. This can only be obtained if processes developed at laboratory scale are accurately translated to full industrial scale. But because of the emergence of scale-up effect, it is likely that conditions in laboratory-scale cultures will differ from those at pilot-plant and production scale. In addition to altering culture variables, changing scales can also affect the degree of homogeneity, with the concomitant appearance of environmental gradients. In this work, two methods were utilized to study fluid dynamics of the Heterogeneities in the reactor.
In 200L reactor, Computational Fluid Dynamics (CFD) simulation combined with experiments was utilized to determine the Gas-liquid two-phase impeller system. They could eliminate the degree of homogeneity within the reactor with low power consumption and good Gas-Liquid Dispersion.
In this paper, Scale-down method was introduced to simulate the heterogeneities in large-scale bioreactor by constructing Scale-down system. The characteristic parameters of fluid dynamics in Scale-down system, such as mixing time and residence time distribution, were measured to initiate to us in the fluid dynamics character. The results show that tm was mainly influenced by circulation flow and PFR form. Plug flow feature in the PFR was maintained with high circulation flow, large PFR volume and small diameter. Virtual volume (Vvrit) was introduced to analyze the mixing time character. RTD experiments validate the existence of dead zone or backmixing. It was also stated that fluid dynamics character in the PFR was affected by circulation flow and diameter. But influence was reduced when PFR account for a small proportion. Based on experiments, fluid flied and hydrodynamic parameters within Scale-down system were proved by CFD simulation. Our conclusions were validated by simulation results to supply fermentation test with a solid theoretical basis
在200L冷模反应器中,通过将计算流体力学(Computational Fluid Dynamics, CFD)模拟与实际测定相结合,优化得到了八种能够消除反应器内环境梯度,功率消耗较低、气液分散特性较好的气液两相搅拌系统。
本文还采用了Scale-down方法,通过构建Scale-down反应器来模拟工业级反应器内的非均匀环境。实验中通过测定Scale-down系统中的混合时间及停留时间分布等流体动力学参数,对系统的流体动力学特性有了初步了解。混合实验结果表明,混合时间受循环流量和PFR形式的影响较大。增大循环流量、PFR部分体积或者采用较小的管径均有利于保持PFR中平推流特性。在数据处理中,通过引入虚拟体积(Vvrit)本文对所得混合时间数据进行拟合,对混合时间特性进行了深入的分析。停留时间分布在验证了系统内存在死区或者返混情况的同时,表明PFR内的流体动力学特性受循环流量和管径的影响较大。但由于PFR体积与系统体积相比较小,所以在停留时间分布测定中表现出PFR部分差异对系统流体动力学特性影响较小的特点。在实验测定的基础上,本文对Scale-down内的流场及流体动力参数进行了CFD模拟验证。模拟结果表明实验中所得数据及结论真实有效,为后期的发酵试验提供了坚实的理论基础。
Present biotechnological applications demand large amounts of low-cost and high-quality products. This can only be obtained if processes developed at laboratory scale are accurately translated to full industrial scale. But because of the emergence of scale-up effect, it is likely that conditions in laboratory-scale cultures will differ from those at pilot-plant and production scale. In addition to altering culture variables, changing scales can also affect the degree of homogeneity, with the concomitant appearance of environmental gradients. In this work, two methods were utilized to study fluid dynamics of the Heterogeneities in the reactor.
In 200L reactor, Computational Fluid Dynamics (CFD) simulation combined with experiments was utilized to determine the Gas-liquid two-phase impeller system. They could eliminate the degree of homogeneity within the reactor with low power consumption and good Gas-Liquid Dispersion.
In this paper, Scale-down method was introduced to simulate the heterogeneities in large-scale bioreactor by constructing Scale-down system. The characteristic parameters of fluid dynamics in Scale-down system, such as mixing time and residence time distribution, were measured to initiate to us in the fluid dynamics character. The results show that tm was mainly influenced by circulation flow and PFR form. Plug flow feature in the PFR was maintained with high circulation flow, large PFR volume and small diameter. Virtual volume (Vvrit) was introduced to analyze the mixing time character. RTD experiments validate the existence of dead zone or backmixing. It was also stated that fluid dynamics character in the PFR was affected by circulation flow and diameter. But influence was reduced when PFR account for a small proportion. Based on experiments, fluid flied and hydrodynamic parameters within Scale-down system were proved by CFD simulation. Our conclusions were validated by simulation results to supply fermentation test with a solid theoretical basis
引文
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[2].张元兴,许学书.生物反应器工程,第一版.2001,上海：华东理工大学出版社.199-214.
[3]. Lara, A. R., Galindo, E., Ramirez, O. T., and Palomares, L. A. Living with heterogeneities in bioreactors. Molecular Biotechnology.2006,34(3):355-381.
[4].Oosterhuis, N.M.G. Scale-up of bioreactors:a Scale-down approach., in Delft University of Technology.1984, Delft University of Technology:Delft.
[5].Oosterhuis, N.M.G., K., N. W. F. Dissolved oxygen concentration profiles in a productionscale bioreactor. Biotechnol. Bioeng.1984,26:546-550.
[6]. Sandoval-Basurto, E. A., Gosset, G., Bolivar, F., Ramirez, O. T. Culture of Escherichia coli under dissolved oxygen gradients simulated in a two-compartment Scale-down system:Metabolic response and production of recombinant protein. Biotechnology and Bioengineering.2005,89(4): 453-463.
[7].Borys, M.C., D.I.H. Linzer, E.T. Papoutsakis. Culture pH affects expression rates and glycosylation of recombinant mouse placental lactogen proteins by chinese hamster ovary (CHO) cells. Bio/Technology.1993,11:720-724.
[8].Reuss, M., S. Schmalzriedt, M. Jenne. Structured Modelling of Bioreactors. in Advances in Bioprocess Engineering.1994,207-215.
[9].Langheinrich, C.,A.W. Nienow. Control of pH in large-scale, free suspension animal cell bioreactors:Alkali addition and pH excursions. Biotechnology and Bioengineering.1999,66(3): 171-179.
[10]. Amanullah, A., McFarlane, C. M., Emery, A. N., and Nienow, A. W. Scale-down model to simulate spatial pH variations in large-scale bioreactors. Biotechnology and Bioengineering.2001, 73(5):390-399.
[11].Haggstrom, L. Cell Metabolism, Animal. The Encyclopedia of Cell Technology.2000,1: 392-411.
[12].Onyeaka, H., A.W. Nienow,C.J. Hewitt.Further studies related to the scale-up of high cell density Escherichia coli fed-batch fermentations:The additional effect of a changing microenvironment when using aqueous ammonia to control pH. Biotechnology and Bioengineering. 2003,84(4):474-484.
[13].Zheng, J.Y, L.J.Janis. Influence of pH, buffer species, and storage temperature on physicochemical stability of a humanized monoclonal antibody LA298. International Journal of Pharmaceutics.2006,308(1-2):46-51.
[14].Hristov, H., Mann, R., Lossev, V., Vlaev, S. D., Seichter. P. A 3-D analysis of gas-liquid mixing, mass transfer and bioreaction in a stirred bio-reactor. Food and Bioproducts Processing. 2001,79(C4):232-241.
[15].Larsson, G.,M. Tornkvist. Rapid sampling, cell inactivation and evaluation of low extracellular glucose concentrations during fed-batch cultivation. J Biotechnol.1996,49(1-3):69-82.
[16]. Larsson, G., Tornkvist, M., Stahl-Wernersson E., Tragardh, C., Noorman, H., and Enfors, S. O. Substrate gradients in fed-batch bioreactors:origin and consequences. Bioprocess Engineering. 1996,14:281-289.
[17]. Lara, A. R., Taymaz-Nikerel, H., Mashego, M. R., van Gulik, W. M., Heijnen, J. J., Ramirez, O. T., and van Winden, W. A. Fast Dynamic Response of the Fermentative Metabolism of Escherichia coli to Aerobic and Anaerobic Glucose Pulses. Biotechnology and Bioengineering. 2009,104(6):1153-1161.
[18].Mollet, M., Ma, N. N., Zhao, Y., Brodkey, R., Taticek, R., and Chalmers, J. J. Bioprocess equipment:Characterization of energy dissipation rate and its potential to damage cells. Biotechnology Progress.2004,20(5):1437-1448.
[19].Ranjan, V., Waterbury, R., Xiao, Z., Diamond, S. L. Fluid shear stress induction of the transcriptional activator c-fos in human and bovine endothelial cells, HeLa, and Chinese hamster ovary cells. Biotechnology and Bioengineering.1996,49(4):383-90.
[20].Lakhotia, S., K.D. Bauer,E.T. Papoutsakis. Damaging agitation intensities increase DNA synthesis rate and alter cell-cycle phase distributions of CHO cells. Biotechnology and Bioengineering.1992,40(8):978-90.
[21].Gorenflo, V.M., P. Beauchesne, V. Tayi. Acoustic cell processing for viral transduction or bioreactor cell retention.. in Proceedings of the 19th ESACT meeting.2005.
[22].Caspeta, L., Flores, N., Perez, N. O., Bolivar, F., and Ramirez, O. T. The effect of heating rate on Escherichia coli metabolism, physiological stress, transcriptional response, and production of temperature-induced recombinant protein:a Scale-down study. Biotechnology and Bioengineering. 2009,102(2):468-82.
[23].Baez, A., Flores, N., Bolivar, F., and Ramirez, O. T. Metabolic and Transcriptional Response of Recombinant Escherichia coli to Elevated Dissolved Carbon Dioxide Concentrations. Biotechnology and Bioengineering.2009,104(1):102-110.
[24].Van't Riet K, S.J.M. The Behavior of Gas-Liquid Mixtures Near Rushton Turbine Blades. Chem. Eng. Sci.1973,28(4):1031-1037.
[25].Nienow A W, W.M.M.C.G., Smith J M, et al. On the Flooding/Loading Transition and the Complete Dispersal Condition in Aerated Vessels Agitated by a Rushton-turbine. in British Hydromechanics Research Association. Proceedings of the 5th European Conference on Mixing. 1985, The Fluid Engineering Centre Cranfield:Bedford:143-154.
[26].Nienow A W. Gas-Liquid Mixing Studies:A Comparison of Rushton Turbines with Some Modern Impellers. Trans. IChemE.1996,74:414-422.
[27].侯治中,冯连芳,李允明等.不同类型搅拌器的气-液分散和混合特性.合成橡胶工业.1995,18(3)：147-150.
[28].张新年.半椭圆管盘式涡轮搅拌器气-液分散特性.过程工程学报.2008,8(3)：444-448.
[29].马志超.不同叶片形状盘式涡轮搅拌器的气-液分散特性.过程工程报.2009,9(5)：854-859.
[30].Buziol S, Bashir I, Baumeister A, Claassen W, Noisommit-Rizzi N, Mailinger W, Reuss M. New bioreactor-coupled rapid stopped-flow sampling technique for measurements of metabolite dynamics on a subsecond time scale. Biotechnology and Bioengineering.2002,80(6):632-636.
[31].Serrato JA, Palomares LA, Meneses-Acosta A, Ramirez OT. Heterogeneous conditions in dissolved oxygen affect N-glycosylation but not productivity of a monoclonal antibody in hybridoma cultures. Biotechnology and Bioengineering.2004.88(2):176-88.
[32].Neubauer, P.S. Junne. Scale-down simulators for metabolic analysis of large-scale bioprocesses. Current Opinion in Biotechnology.2010,21(1):114-121.
[33].Cashel, M., Gentry, D. R., Hernandez, V. J., Vinella, D. The stringent response. Escherichia coli and Salmonella. Cellular and MolecularBiology.1996:1458-1496.
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