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首页> 外文期刊>Energy & fuels >Dynamic Modeling of a Fermentation Process with Ex situ Butanol Recovery (ESBR) for Continuous Biobutanol Production
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Dynamic Modeling of a Fermentation Process with Ex situ Butanol Recovery (ESBR) for Continuous Biobutanol Production

机译:用于异丁醇连续生产的异位丁醇回收(ESBR)发酵过程的动态建模

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摘要

A dynamic model for a fermentation process equipped with an ex situ butanol recovery (termed "ESBR" hereafter) system: is proposed for continuous production of biobutanol. Since the proposed ESBR system integrates a,fermenter with a stirred-tank-type adsorption column, the dynamic model includes kinetic Models for both the fermentation (the Monod/Luedelcing-Piret model) and the adsorption (the extended Langmuir Model). Parameters in the kinetic models are initially determined using data from batch and fed batch fermentation experiments with in situ butanol recovery (ISBR). The initially developed model is then used to find a feasible operating condition for an experimental ESBR system, and its parameter values are further tuned using experimental data from the proposed ESBR system for accurate predictions in the butanol and glucose concentration range seen in the ESBR operation. The approach to improving the Model accuracy consists of two steps: (1) identifying the critical parameters by performing a sensitivity analysis and (2) re-estimating the,Selected parameters using data obtained during cyclic operation of the proposed,ESBR System. Accordingly, the developed model based on the kinetics for both,fermentation and adsorption can describe and predict the behavior of the proposed ESBR,system. Thus, the proposed systematic approach provides a reliable platform for the optimal scale-up design and control studies of the ESBR system.
机译:装备有异位丁醇回收(以下称为“ ESBR”)系统的发酵过程的动态模型:建议用于连续生产生物丁醇。由于拟议的ESBR系统将发酵罐与搅拌罐式吸附柱集成在一起,因此动态模型包括用于发酵的动力学模型(Monod / Luedelcing-Piret模型)和吸附的动力学模型(扩展的Langmuir模型)。动力学模型中的参数最初是使用分批和补料分批发酵实验的数据(具有原位丁醇回收率(ISBR))确定的。然后使用最初开发的模型为实验ESBR系统找到可行的操作条件,并使用所提出的ESBR系统的实验数据进一步调整其参数值,以准确预测ESBR操作中看到的丁醇和葡萄糖浓度范围。提高模型精度的方法包括两个步骤:(1)通过执行敏感性分析来识别关键参数;(2)使用在建议的ESBR系统的循环运行过程中获得的数据重新估算所选参数。因此,基于发酵和吸附动力学的开发模型可以描述和预测所提出的ESBR系统的行为。因此,提出的系统方法为ESBR系统的最佳放大设计和控制研究提供了可靠的平台。

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  • 来源
    《Energy & fuels》 |2015年第novaadeca期|7254-7265|共12页
  • 作者单位

    Korea Adv Inst Sci & Technol, Dept Chem & Biomol Engn, Taejon 34141, South Korea|GS Caltex Corp, R&D Ctr, Taejon 305380, South Korea;

    Korea Adv Inst Sci & Technol, Dept Chem & Biomol Engn, Taejon 34141, South Korea;

    Korea Adv Inst Sci & Technol, Dept Chem & Biomol Engn, Taejon 34141, South Korea;

    GS Caltex Corp, R&D Ctr, Taejon 305380, South Korea;

    Korea Adv Inst Sci & Technol, Dept Chem & Biomol Engn, Taejon 34141, South Korea;

    GS Caltex Corp, R&D Ctr, Taejon 305380, South Korea;

    Korea Adv Inst Sci & Technol, Dept Chem & Biomol Engn, Taejon 34141, South Korea;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
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  • 正文语种 eng
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