Flow Regime Identification in a Bubble Column via Nuclear Gauge Densitometry and Chaos Analysis
The bubble column performance can change significantly as a result of flow regime change. Since reactor volume productivity, mass and heat transfer as well as mixing are affected by the prevailing flow regime, it is very important to know how to identify it. In this work, flow regime identification...
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Veröffentlicht in: | Chemical engineering & technology 2011-02, Vol.34 (2), p.225-233 |
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description | The bubble column performance can change significantly as a result of flow regime change. Since reactor volume productivity, mass and heat transfer as well as mixing are affected by the prevailing flow regime, it is very important to know how to identify it. In this work, flow regime identification was performed on the basis of the Kolmogorov entropy (KE) algorithm applied to nuclear gauge densitometry data. In addition, the average cycle time was used for validation of the results. Three transition velocities were identified that delineated the boundaries of the three main hydrodynamic regimes. The first two transition points were also confirmed by the information entropy concept. The increasing KE trend in the bubbly flow regime and the decreasing KE trend in the churn‐turbulent regime were predicted successfully by means of new semi‐theoretical models.
The Kolmogorov entropy (KE) algorithm was applied to nuclear gauge densitometry data. The main goal of the research was to identify the three main transition velocities (points of instability). Each of these values was predicted on the basis of some theoretical considerations about the change of bubble shape. |
doi_str_mv | 10.1002/ceat.201000308 |
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The Kolmogorov entropy (KE) algorithm was applied to nuclear gauge densitometry data. The main goal of the research was to identify the three main transition velocities (points of instability). Each of these values was predicted on the basis of some theoretical considerations about the change of bubble shape.</description><identifier>ISSN: 0930-7516</identifier><identifier>EISSN: 1521-4125</identifier><identifier>DOI: 10.1002/ceat.201000308</identifier><identifier>CODEN: CETEER</identifier><language>eng</language><publisher>Weinheim: WILEY-VCH Verlag</publisher><subject>Applied sciences ; Bubble columns ; Chaotic behavior ; Chemical engineering ; Exact sciences and technology ; Heat and mass transfer. Packings, plates ; Hydrodynamics of contact apparatus ; Information entropy ; Kolmogorov entropy modeling ; Nuclear gauge densitometry ; Reactors</subject><ispartof>Chemical engineering & technology, 2011-02, Vol.34 (2), p.225-233</ispartof><rights>Copyright © 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3578-c01abda726f7de268ca17ab2c0e2928a314b39eb16135d36a7133f8f5bcc77e03</citedby><cites>FETCH-LOGICAL-c3578-c01abda726f7de268ca17ab2c0e2928a314b39eb16135d36a7133f8f5bcc77e03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fceat.201000308$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fceat.201000308$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=24265991$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Nedeltchev, S.</creatorcontrib><creatorcontrib>Shaikh, A.</creatorcontrib><creatorcontrib>Al-Dahhan, M.</creatorcontrib><title>Flow Regime Identification in a Bubble Column via Nuclear Gauge Densitometry and Chaos Analysis</title><title>Chemical engineering & technology</title><addtitle>Chem. Eng. Technol</addtitle><description>The bubble column performance can change significantly as a result of flow regime change. Since reactor volume productivity, mass and heat transfer as well as mixing are affected by the prevailing flow regime, it is very important to know how to identify it. In this work, flow regime identification was performed on the basis of the Kolmogorov entropy (KE) algorithm applied to nuclear gauge densitometry data. In addition, the average cycle time was used for validation of the results. Three transition velocities were identified that delineated the boundaries of the three main hydrodynamic regimes. The first two transition points were also confirmed by the information entropy concept. The increasing KE trend in the bubbly flow regime and the decreasing KE trend in the churn‐turbulent regime were predicted successfully by means of new semi‐theoretical models.
The Kolmogorov entropy (KE) algorithm was applied to nuclear gauge densitometry data. The main goal of the research was to identify the three main transition velocities (points of instability). Each of these values was predicted on the basis of some theoretical considerations about the change of bubble shape.</description><subject>Applied sciences</subject><subject>Bubble columns</subject><subject>Chaotic behavior</subject><subject>Chemical engineering</subject><subject>Exact sciences and technology</subject><subject>Heat and mass transfer. Packings, plates</subject><subject>Hydrodynamics of contact apparatus</subject><subject>Information entropy</subject><subject>Kolmogorov entropy modeling</subject><subject>Nuclear gauge densitometry</subject><subject>Reactors</subject><issn>0930-7516</issn><issn>1521-4125</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNqFkE1PwkAQhjdGExG9et6Lx-J-0N32iBWQBDEhGI-b6XaKq6Ul3SL231uCId48zUzyPO8kLyG3nA04Y-LeIjQDwbqdSRadkR4PBQ-GXITnpMdiyQIdcnVJrrz_6BjeHT1iJkW1p0tcuw3SWYZl43JnoXFVSV1JgT7s0rRAmlTFblPSLwd0sbMFQk2nsFsjfcTSu6baYFO3FMqMJu9QeToqoWi989fkIofC483v7JPXyXiVPAXzl-ksGc0DK0MdBZZxSDPQQuU6Q6EiC1xDKixDEYsIJB-mMsaUKy7DTCrQXMo8ysPUWq2RyT4ZHHNtXXlfY262tdtA3RrOzKEec6jHnOrphLujsAVvochrKK3zJ0sMhQrjmHdcfOT2rsD2n1STjEervz-Co-t8g98nF-pPo7TUoXlbTM3weSmU0sJE8gchv4VC</recordid><startdate>201102</startdate><enddate>201102</enddate><creator>Nedeltchev, S.</creator><creator>Shaikh, A.</creator><creator>Al-Dahhan, M.</creator><general>WILEY-VCH Verlag</general><general>WILEY‐VCH Verlag</general><general>Wiley-VCH</general><scope>BSCLL</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>201102</creationdate><title>Flow Regime Identification in a Bubble Column via Nuclear Gauge Densitometry and Chaos Analysis</title><author>Nedeltchev, S. ; Shaikh, A. ; Al-Dahhan, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3578-c01abda726f7de268ca17ab2c0e2928a314b39eb16135d36a7133f8f5bcc77e03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Applied sciences</topic><topic>Bubble columns</topic><topic>Chaotic behavior</topic><topic>Chemical engineering</topic><topic>Exact sciences and technology</topic><topic>Heat and mass transfer. Packings, plates</topic><topic>Hydrodynamics of contact apparatus</topic><topic>Information entropy</topic><topic>Kolmogorov entropy modeling</topic><topic>Nuclear gauge densitometry</topic><topic>Reactors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nedeltchev, S.</creatorcontrib><creatorcontrib>Shaikh, A.</creatorcontrib><creatorcontrib>Al-Dahhan, M.</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><jtitle>Chemical engineering & technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nedeltchev, S.</au><au>Shaikh, A.</au><au>Al-Dahhan, M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Flow Regime Identification in a Bubble Column via Nuclear Gauge Densitometry and Chaos Analysis</atitle><jtitle>Chemical engineering & technology</jtitle><addtitle>Chem. Eng. Technol</addtitle><date>2011-02</date><risdate>2011</risdate><volume>34</volume><issue>2</issue><spage>225</spage><epage>233</epage><pages>225-233</pages><issn>0930-7516</issn><eissn>1521-4125</eissn><coden>CETEER</coden><abstract>The bubble column performance can change significantly as a result of flow regime change. Since reactor volume productivity, mass and heat transfer as well as mixing are affected by the prevailing flow regime, it is very important to know how to identify it. In this work, flow regime identification was performed on the basis of the Kolmogorov entropy (KE) algorithm applied to nuclear gauge densitometry data. In addition, the average cycle time was used for validation of the results. Three transition velocities were identified that delineated the boundaries of the three main hydrodynamic regimes. The first two transition points were also confirmed by the information entropy concept. The increasing KE trend in the bubbly flow regime and the decreasing KE trend in the churn‐turbulent regime were predicted successfully by means of new semi‐theoretical models.
The Kolmogorov entropy (KE) algorithm was applied to nuclear gauge densitometry data. The main goal of the research was to identify the three main transition velocities (points of instability). Each of these values was predicted on the basis of some theoretical considerations about the change of bubble shape.</abstract><cop>Weinheim</cop><pub>WILEY-VCH Verlag</pub><doi>10.1002/ceat.201000308</doi><tpages>9</tpages></addata></record> |
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subjects | Applied sciences Bubble columns Chaotic behavior Chemical engineering Exact sciences and technology Heat and mass transfer. Packings, plates Hydrodynamics of contact apparatus Information entropy Kolmogorov entropy modeling Nuclear gauge densitometry Reactors |
title | Flow Regime Identification in a Bubble Column via Nuclear Gauge Densitometry and Chaos Analysis |
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