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An investigation in food process simulation using data reconciliation
This paper deals with the application of a data reconciliation method to an industrial food plant. A distillation process performs high standard level alcohol purification downstream a fermentation unit of beet molasses. The ability to take samples as well as the difficulty of their analytical analy...
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Published in: | Computers & chemical engineering 1993, Vol.17, p.S257-S262 |
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container_end_page | S262 |
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container_title | Computers & chemical engineering |
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creator | Meyer, M. Pingaud, H. Enjalbert, M. |
description | This paper deals with the application of a data reconciliation method to an industrial food plant. A distillation process performs high standard level alcohol purification downstream a fermentation unit of beet molasses. The ability to take samples as well as the difficulty of their analytical analysis have limited the available off-line information on chemical composition of the process streams. Furthermore, each process stream has not been instrumented by a flowmeter.
In the first part of this article, we will show how it is possible to partition the set of flowrates and mass compositions of the process streams in terms of observability and redundancy of the process mass balances. It will lead to an adapted formulation of the optimisation problem.
In the second part, the numerical difficulty due to the presence of very low mass fraction components, whose characterization is essential to validate the quality specification, is discussed. Emphasis is laid on the numerical methods selected to solve a problem with hundreds of variables.
Finally, the “a posteriori” statistical tests on the adjusted measures are discussed. It constitutes an essential step to judge the pertinence of the results and to point out the gross measurement errors. |
doi_str_mv | 10.1016/0098-1354(93)80239-J |
format | article |
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In the first part of this article, we will show how it is possible to partition the set of flowrates and mass compositions of the process streams in terms of observability and redundancy of the process mass balances. It will lead to an adapted formulation of the optimisation problem.
In the second part, the numerical difficulty due to the presence of very low mass fraction components, whose characterization is essential to validate the quality specification, is discussed. Emphasis is laid on the numerical methods selected to solve a problem with hundreds of variables.
Finally, the “a posteriori” statistical tests on the adjusted measures are discussed. It constitutes an essential step to judge the pertinence of the results and to point out the gross measurement errors.</description><identifier>ISSN: 0098-1354</identifier><identifier>EISSN: 1873-4375</identifier><identifier>DOI: 10.1016/0098-1354(93)80239-J</identifier><identifier>CODEN: CCENDW</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Biological and medical sciences ; Computer simulation ; Data processing ; Food industries ; Fundamental and applied biological sciences. Psychology ; General aspects ; Methods of analysis, processing and quality control, regulation, standards ; Numerical methods</subject><ispartof>Computers & chemical engineering, 1993, Vol.17, p.S257-S262</ispartof><rights>1992 Pergamon Press Ltd</rights><rights>1993 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c364t-95556fc2677e9da3dd64ca8b1bea2933e5f7bb8e84ee57fd91e986641f8133413</citedby><cites>FETCH-LOGICAL-c364t-95556fc2677e9da3dd64ca8b1bea2933e5f7bb8e84ee57fd91e986641f8133413</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/009813549380239J$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>309,310,314,780,784,789,790,3400,4024,4050,4051,23930,23931,25140,27923,27924,27925,45982</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=4789068$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Meyer, M.</creatorcontrib><creatorcontrib>Pingaud, H.</creatorcontrib><creatorcontrib>Enjalbert, M.</creatorcontrib><title>An investigation in food process simulation using data reconciliation</title><title>Computers & chemical engineering</title><description>This paper deals with the application of a data reconciliation method to an industrial food plant. A distillation process performs high standard level alcohol purification downstream a fermentation unit of beet molasses. The ability to take samples as well as the difficulty of their analytical analysis have limited the available off-line information on chemical composition of the process streams. Furthermore, each process stream has not been instrumented by a flowmeter.
In the first part of this article, we will show how it is possible to partition the set of flowrates and mass compositions of the process streams in terms of observability and redundancy of the process mass balances. It will lead to an adapted formulation of the optimisation problem.
In the second part, the numerical difficulty due to the presence of very low mass fraction components, whose characterization is essential to validate the quality specification, is discussed. Emphasis is laid on the numerical methods selected to solve a problem with hundreds of variables.
Finally, the “a posteriori” statistical tests on the adjusted measures are discussed. It constitutes an essential step to judge the pertinence of the results and to point out the gross measurement errors.</description><subject>Biological and medical sciences</subject><subject>Computer simulation</subject><subject>Data processing</subject><subject>Food industries</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General aspects</subject><subject>Methods of analysis, processing and quality control, regulation, standards</subject><subject>Numerical methods</subject><issn>0098-1354</issn><issn>1873-4375</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1993</creationdate><recordtype>article</recordtype><recordid>eNp9kEtLAzEQgIMoWKv_wMMeRPSwmmwem1yEUuqjFLzoOWSTSYlsd-tmt-C_N9tKj56GYb55fQhdE_xAMBGPGCuZE8rZnaL3EhdU5csTNCGypDmjJT9FkyNyji5i_MIYF0zKCVrMmiw0O4h9WJs-tGOW-bZ12bZrLcSYxbAZ6kNpiKFZZ870JuvAto0NddhXLtGZN3WEq784RZ_Pi4_5a756f3mbz1a5pYL1ueKcC28LUZagnKHOCWaNrEgFplCUAvdlVUmQDICX3ikCSgrBiJeEUkboFN0e5qbjvod0tN6EaKGuTQPtEHUhCKcFwQlkB9B2bYwdeL3twsZ0P5pgPTrToxA9CtGK6r0zvUxtN3_zTbSm9p1JP8ZjLyulwkIm7OmAQfp1F6DT0QZoLLiQvPTateH_Pb_VwoB0</recordid><startdate>1993</startdate><enddate>1993</enddate><creator>Meyer, M.</creator><creator>Pingaud, H.</creator><creator>Enjalbert, M.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SU</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>1993</creationdate><title>An investigation in food process simulation using data reconciliation</title><author>Meyer, M. ; Pingaud, H. ; Enjalbert, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c364t-95556fc2677e9da3dd64ca8b1bea2933e5f7bb8e84ee57fd91e986641f8133413</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1993</creationdate><topic>Biological and medical sciences</topic><topic>Computer simulation</topic><topic>Data processing</topic><topic>Food industries</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>General aspects</topic><topic>Methods of analysis, processing and quality control, regulation, standards</topic><topic>Numerical methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Meyer, M.</creatorcontrib><creatorcontrib>Pingaud, H.</creatorcontrib><creatorcontrib>Enjalbert, M.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Environmental Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computers & chemical engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Meyer, M.</au><au>Pingaud, H.</au><au>Enjalbert, M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An investigation in food process simulation using data reconciliation</atitle><jtitle>Computers & chemical engineering</jtitle><date>1993</date><risdate>1993</risdate><volume>17</volume><spage>S257</spage><epage>S262</epage><pages>S257-S262</pages><issn>0098-1354</issn><eissn>1873-4375</eissn><coden>CCENDW</coden><abstract>This paper deals with the application of a data reconciliation method to an industrial food plant. A distillation process performs high standard level alcohol purification downstream a fermentation unit of beet molasses. The ability to take samples as well as the difficulty of their analytical analysis have limited the available off-line information on chemical composition of the process streams. Furthermore, each process stream has not been instrumented by a flowmeter.
In the first part of this article, we will show how it is possible to partition the set of flowrates and mass compositions of the process streams in terms of observability and redundancy of the process mass balances. It will lead to an adapted formulation of the optimisation problem.
In the second part, the numerical difficulty due to the presence of very low mass fraction components, whose characterization is essential to validate the quality specification, is discussed. Emphasis is laid on the numerical methods selected to solve a problem with hundreds of variables.
Finally, the “a posteriori” statistical tests on the adjusted measures are discussed. It constitutes an essential step to judge the pertinence of the results and to point out the gross measurement errors.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/0098-1354(93)80239-J</doi><tpages>6</tpages></addata></record> |
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source | Backfile Package - Chemical Engineering (Legacy) [YCC] |
subjects | Biological and medical sciences Computer simulation Data processing Food industries Fundamental and applied biological sciences. Psychology General aspects Methods of analysis, processing and quality control, regulation, standards Numerical methods |
title | An investigation in food process simulation using data reconciliation |
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