On-line identification of fermentation processes for ethanol production
A strategy for monitoring fermentation processes, specifically, simultaneous saccharification and fermentation (SSF) of corn mash, was developed. The strategy covered the development and use of first principles, semimechanistic and unstructured process model based on major kinetic phenomena, along w...
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Veröffentlicht in: | Bioprocess and biosystems engineering 2017-07, Vol.40 (7), p.989-1006 |
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creator | Câmara, M. M. Soares, R. M. Feital, T. Naomi, P. Oki, S. Thevelein, J. M. Amaral, M. Pinto, J. C. |
description | A strategy for monitoring fermentation processes, specifically, simultaneous saccharification and fermentation (SSF) of corn mash, was developed. The strategy covered the development and use of first principles, semimechanistic and unstructured process model based on major kinetic phenomena, along with mass and energy balances. The model was then used as a reference model within an identification procedure capable of running on-line. The on-line identification procedure consists on updating the reference model through the estimation of corrective parameters for certain reaction rates using the most recent process measurements. The strategy makes use of standard laboratory measurements for sugars quantification and in situ temperature and liquid level data. The model, along with the on-line identification procedure, has been tested against real industrial data and have been able to accurately predict the main variables of operational interest, i.e., state variables and its dynamics, and key process indicators. The results demonstrate that the strategy is capable of monitoring, in real time, this complex industrial biomass fermentation. This new tool provides a great support for decision-making and opens a new range of opportunities for industrial optimization. |
doi_str_mv | 10.1007/s00449-017-1762-6 |
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M. ; Soares, R. M. ; Feital, T. ; Naomi, P. ; Oki, S. ; Thevelein, J. M. ; Amaral, M. ; Pinto, J. C.</creator><creatorcontrib>Câmara, M. M. ; Soares, R. M. ; Feital, T. ; Naomi, P. ; Oki, S. ; Thevelein, J. M. ; Amaral, M. ; Pinto, J. C.</creatorcontrib><description>A strategy for monitoring fermentation processes, specifically, simultaneous saccharification and fermentation (SSF) of corn mash, was developed. The strategy covered the development and use of first principles, semimechanistic and unstructured process model based on major kinetic phenomena, along with mass and energy balances. The model was then used as a reference model within an identification procedure capable of running on-line. The on-line identification procedure consists on updating the reference model through the estimation of corrective parameters for certain reaction rates using the most recent process measurements. The strategy makes use of standard laboratory measurements for sugars quantification and in situ temperature and liquid level data. The model, along with the on-line identification procedure, has been tested against real industrial data and have been able to accurately predict the main variables of operational interest, i.e., state variables and its dynamics, and key process indicators. The results demonstrate that the strategy is capable of monitoring, in real time, this complex industrial biomass fermentation. This new tool provides a great support for decision-making and opens a new range of opportunities for industrial optimization.</description><identifier>ISSN: 1615-7591</identifier><identifier>EISSN: 1615-7605</identifier><identifier>DOI: 10.1007/s00449-017-1762-6</identifier><identifier>PMID: 28391378</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Bioengineering ; Biomass ; Biotechnology ; Carbohydrates ; Chemistry ; Chemistry and Materials Science ; Corn ; Decision making ; Energy ; Energy balance ; Environmental Engineering/Biotechnology ; Ethanol ; Fermentation ; Food Science ; Indicators ; Industrial and Production Engineering ; Industrial Chemistry/Chemical Engineering ; Mathematical models ; Monitoring ; Optimization ; Parameter estimation ; Real time ; Research Paper ; Running ; Saccharification ; Saccharomyces cerevisiae ; Sugar ; Temperature effects ; Zea mays</subject><ispartof>Bioprocess and biosystems engineering, 2017-07, Vol.40 (7), p.989-1006</ispartof><rights>Springer-Verlag Berlin Heidelberg 2017</rights><rights>Bioprocess and Biosystems Engineering is a copyright of Springer, 2017.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c409t-44677c568de32d9a520858a71762e35ac58e7b43909267af4b28c7b7c1d493433</citedby><cites>FETCH-LOGICAL-c409t-44677c568de32d9a520858a71762e35ac58e7b43909267af4b28c7b7c1d493433</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00449-017-1762-6$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00449-017-1762-6$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28391378$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Câmara, M. M.</creatorcontrib><creatorcontrib>Soares, R. M.</creatorcontrib><creatorcontrib>Feital, T.</creatorcontrib><creatorcontrib>Naomi, P.</creatorcontrib><creatorcontrib>Oki, S.</creatorcontrib><creatorcontrib>Thevelein, J. M.</creatorcontrib><creatorcontrib>Amaral, M.</creatorcontrib><creatorcontrib>Pinto, J. C.</creatorcontrib><title>On-line identification of fermentation processes for ethanol production</title><title>Bioprocess and biosystems engineering</title><addtitle>Bioprocess Biosyst Eng</addtitle><addtitle>Bioprocess Biosyst Eng</addtitle><description>A strategy for monitoring fermentation processes, specifically, simultaneous saccharification and fermentation (SSF) of corn mash, was developed. The strategy covered the development and use of first principles, semimechanistic and unstructured process model based on major kinetic phenomena, along with mass and energy balances. 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M.</au><au>Soares, R. M.</au><au>Feital, T.</au><au>Naomi, P.</au><au>Oki, S.</au><au>Thevelein, J. M.</au><au>Amaral, M.</au><au>Pinto, J. C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>On-line identification of fermentation processes for ethanol production</atitle><jtitle>Bioprocess and biosystems engineering</jtitle><stitle>Bioprocess Biosyst Eng</stitle><addtitle>Bioprocess Biosyst Eng</addtitle><date>2017-07-01</date><risdate>2017</risdate><volume>40</volume><issue>7</issue><spage>989</spage><epage>1006</epage><pages>989-1006</pages><issn>1615-7591</issn><eissn>1615-7605</eissn><abstract>A strategy for monitoring fermentation processes, specifically, simultaneous saccharification and fermentation (SSF) of corn mash, was developed. The strategy covered the development and use of first principles, semimechanistic and unstructured process model based on major kinetic phenomena, along with mass and energy balances. The model was then used as a reference model within an identification procedure capable of running on-line. The on-line identification procedure consists on updating the reference model through the estimation of corrective parameters for certain reaction rates using the most recent process measurements. The strategy makes use of standard laboratory measurements for sugars quantification and in situ temperature and liquid level data. The model, along with the on-line identification procedure, has been tested against real industrial data and have been able to accurately predict the main variables of operational interest, i.e., state variables and its dynamics, and key process indicators. The results demonstrate that the strategy is capable of monitoring, in real time, this complex industrial biomass fermentation. 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subjects | Bioengineering Biomass Biotechnology Carbohydrates Chemistry Chemistry and Materials Science Corn Decision making Energy Energy balance Environmental Engineering/Biotechnology Ethanol Fermentation Food Science Indicators Industrial and Production Engineering Industrial Chemistry/Chemical Engineering Mathematical models Monitoring Optimization Parameter estimation Real time Research Paper Running Saccharification Saccharomyces cerevisiae Sugar Temperature effects Zea mays |
title | On-line identification of fermentation processes for ethanol production |
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