Multi-objective Optimization of a Fermentation Process Integrated with Cell Recycling and Inter-stage Extraction

被引:0
作者
Sharma, Shivom [1 ]
Rangaiah, G. P. [1 ]
机构
[1] Natl Univ Singapore, Dept Chem & Biomol Engn, Singapore 117576, Singapore
来源
11TH INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING, PTS A AND B | 2012年 / 31卷
关键词
Fermentation Process; Inter-stage Extraction; Multi-objective Optimization;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Bio-fuels are clean, renewable energy with potential to replace fossil fuels. Bio-ethanol is the widely used bio-fuel, which can be produced from a variety of agricultural feedstocks. Its production from fermentable sugars is well established. Production of bioethanol from starchy and cellulosic materials requires hydrolysis as an additional step to produce fermentable sugars. In SHF (separate hydrolysis and fermentation) process, hydrolysis and fermentation are performed at their respective optimal temperatures, but end products (i.e., glucose and cellobiose) inhibit hydrolysis. SSF (simultaneous saccharification and fermentation) process removes product inhibition by immediate consumption of end products of hydrolysis. Ethanol concentration also inhibits glucose to ethanol conversion in the fermentor, which results in low ethanol productivity and yield. To avoid this, ethanol can be continuously removed from the fermentor using either extraction or perm-selective membrane. In this study, a three-stage fermentation process integrated with cell recycling and inter-stage extraction is considered, for producing ethanol from the lignocellulosic feed-stocks. The integrated process is optimized using a multi-objective differential evolution algorithm for two objectives simultaneously. Finally, improvement in the performance of the fermentation process due to inter-stage extraction is evaluated quantitatively.
引用
收藏
页码:860 / 864
页数:5
相关论文
共 8 条
[1]   Optimization of a Fed-Batch Simultaneous Saccharification and Cofermentation Process from Lignocellulose to Ethanol [J].
Chen, Ming-Liang ;
Wang, Feng-Sheng .
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2010, 49 (12) :5775-5785
[2]   Optimal trade-off design of integrated fermentation processes for ethanol production using genetically engineered yeast [J].
Chen, Ming-Liang ;
Wang, Feng-Sheng .
CHEMICAL ENGINEERING JOURNAL, 2010, 158 (02) :271-280
[3]  
da Silva FLH, 1999, J CHEM TECHNOL BIOT, V74, P176, DOI 10.1002/(SICI)1097-4660(199902)74:2<176::AID-JCTB995>3.0.CO
[4]  
2-C
[5]   A fast and elitist multiobjective genetic algorithm: NSGA-II [J].
Deb, K ;
Pratap, A ;
Agarwal, S ;
Meyarivan, T .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) :182-197
[6]   Fermentation kinetics of ethanol production from glucose and xylose by recombinant Saccharomyces 1400(pLNH33) [J].
Mahesh S. Krishnan ;
Nancy W. Y. Ho ;
George T. Tsao .
Applied Biochemistry and Biotechnology, 1999, 78 (1-3) :373-388
[7]   Performance Assessment of Generalized Differential Evolution 3 with a Given Set of Constrained Multi-Objective Test Problems [J].
Kukkonen, Saku ;
Lampinen, Jouni .
2009 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-5, 2009, :1943-+
[8]   Fuzzy Optimization of Continuous Fermentations with Cell Recycling for Ethanol Production [J].
Wang, Feng-Sheng ;
Lin, Hsun-Tung .
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2010, 49 (05) :2306-2311