Multi‐objective optimization design of plate‐fin vapor generator for supercritical organic Rankine cycle
Summary Supercritical organic Rankine cycle (SORC) is an improved ORC architecture with lower exergy destruction and better heat source utilization when compared with a subcritical one. The accurate design of its vapor generator is of critical importance due to the fact that heat transfer performanc...
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| Veröffentlicht in: | International journal of energy research 2019-05, Vol.43 (6), p.2312-2326, Article er.4451 |
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| creator | Xu, Guoqiang Zhu, Pengju Quan, Yongkai Dong, Bensi Jin, Ruifan |
| description | Summary
Supercritical organic Rankine cycle (SORC) is an improved ORC architecture with lower exergy destruction and better heat source utilization when compared with a subcritical one. The accurate design of its vapor generator is of critical importance due to the fact that heat transfer performance significantly affects thermal efficiency, power output, and size of the overall system. This paper aims to develop a mathematical model of the SORC vapor generator using plate‐fin heat exchanger. The finite volume method is applied to deal with the properties' variation problem of the supercritical fluids. Multi‐objective optimization is employed by the nondominated sorting genetic algorithm II to find the optimum geometry design. The objective functions are the number of entropy production units, annual cost, and volume. For a specific SORC system, an optimum vapor generator is designed using the developed model. Parametric studies are conducted to assess the effect of geometry parameters on the vapor generator performance. The off‐design performance of the vapor generator is also evaluated under different mass flow rates and different heat source inlet temperature conditions.
A mathematical model of the SORC vapor generator using plate‐fin heat exchanger is developed. The finite volume method is applied to deal with the properties variation problem of the supercritical fluids. Multi‐objective optimization is employed by the nondominated sorting genetic algorithm II to find the optimum geometry design of the vapor generator according to its entropy generation units, annual cost, and volume. |
| doi_str_mv | 10.1002/er.4451 |
| format | Article |
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Supercritical organic Rankine cycle (SORC) is an improved ORC architecture with lower exergy destruction and better heat source utilization when compared with a subcritical one. The accurate design of its vapor generator is of critical importance due to the fact that heat transfer performance significantly affects thermal efficiency, power output, and size of the overall system. This paper aims to develop a mathematical model of the SORC vapor generator using plate‐fin heat exchanger. The finite volume method is applied to deal with the properties' variation problem of the supercritical fluids. Multi‐objective optimization is employed by the nondominated sorting genetic algorithm II to find the optimum geometry design. The objective functions are the number of entropy production units, annual cost, and volume. For a specific SORC system, an optimum vapor generator is designed using the developed model. Parametric studies are conducted to assess the effect of geometry parameters on the vapor generator performance. The off‐design performance of the vapor generator is also evaluated under different mass flow rates and different heat source inlet temperature conditions.
A mathematical model of the SORC vapor generator using plate‐fin heat exchanger is developed. The finite volume method is applied to deal with the properties variation problem of the supercritical fluids. Multi‐objective optimization is employed by the nondominated sorting genetic algorithm II to find the optimum geometry design of the vapor generator according to its entropy generation units, annual cost, and volume.</description><identifier>ISSN: 0363-907X</identifier><identifier>EISSN: 1099-114X</identifier><identifier>DOI: 10.1002/er.4451</identifier><language>eng</language><publisher>Bognor Regis: Hindawi Limited</publisher><subject>Classification ; Computational fluid dynamics ; Design ; Design optimization ; Entropy ; Exergy ; Finite volume method ; Flow rates ; Flow velocity ; Fluids ; genetic algorithm ; Genetic algorithms ; Heat exchangers ; Heat recovery ; Heat transfer ; Inlet temperature ; Mass flow ; Mathematical models ; Mathematics ; multi‐objective optimization ; plate‐fin heat exchanger ; Power efficiency ; Rankine cycle ; Sorting algorithms ; Supercritical fluids ; supercritical organic Rankine cycle ; Thermodynamic efficiency ; vapor generator ; Vaporizers ; Vapors</subject><ispartof>International journal of energy research, 2019-05, Vol.43 (6), p.2312-2326, Article er.4451</ispartof><rights>2019 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3221-3170e70835eab03d4f384e054fabffe1c23451afc52ce1ca262e4bbd41ef75903</citedby><cites>FETCH-LOGICAL-c3221-3170e70835eab03d4f384e054fabffe1c23451afc52ce1ca262e4bbd41ef75903</cites><orcidid>0000-0002-9340-2804</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fer.4451$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fer.4451$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>315,781,785,1418,27926,27927,45576,45577</link.rule.ids></links><search><creatorcontrib>Xu, Guoqiang</creatorcontrib><creatorcontrib>Zhu, Pengju</creatorcontrib><creatorcontrib>Quan, Yongkai</creatorcontrib><creatorcontrib>Dong, Bensi</creatorcontrib><creatorcontrib>Jin, Ruifan</creatorcontrib><title>Multi‐objective optimization design of plate‐fin vapor generator for supercritical organic Rankine cycle</title><title>International journal of energy research</title><description>Summary
Supercritical organic Rankine cycle (SORC) is an improved ORC architecture with lower exergy destruction and better heat source utilization when compared with a subcritical one. The accurate design of its vapor generator is of critical importance due to the fact that heat transfer performance significantly affects thermal efficiency, power output, and size of the overall system. This paper aims to develop a mathematical model of the SORC vapor generator using plate‐fin heat exchanger. The finite volume method is applied to deal with the properties' variation problem of the supercritical fluids. Multi‐objective optimization is employed by the nondominated sorting genetic algorithm II to find the optimum geometry design. The objective functions are the number of entropy production units, annual cost, and volume. For a specific SORC system, an optimum vapor generator is designed using the developed model. Parametric studies are conducted to assess the effect of geometry parameters on the vapor generator performance. The off‐design performance of the vapor generator is also evaluated under different mass flow rates and different heat source inlet temperature conditions.
A mathematical model of the SORC vapor generator using plate‐fin heat exchanger is developed. The finite volume method is applied to deal with the properties variation problem of the supercritical fluids. Multi‐objective optimization is employed by the nondominated sorting genetic algorithm II to find the optimum geometry design of the vapor generator according to its entropy generation units, annual cost, and volume.</description><subject>Classification</subject><subject>Computational fluid dynamics</subject><subject>Design</subject><subject>Design optimization</subject><subject>Entropy</subject><subject>Exergy</subject><subject>Finite volume method</subject><subject>Flow rates</subject><subject>Flow velocity</subject><subject>Fluids</subject><subject>genetic algorithm</subject><subject>Genetic algorithms</subject><subject>Heat exchangers</subject><subject>Heat recovery</subject><subject>Heat transfer</subject><subject>Inlet temperature</subject><subject>Mass flow</subject><subject>Mathematical models</subject><subject>Mathematics</subject><subject>multi‐objective optimization</subject><subject>plate‐fin heat exchanger</subject><subject>Power efficiency</subject><subject>Rankine cycle</subject><subject>Sorting algorithms</subject><subject>Supercritical fluids</subject><subject>supercritical organic Rankine cycle</subject><subject>Thermodynamic efficiency</subject><subject>vapor generator</subject><subject>Vaporizers</subject><subject>Vapors</subject><issn>0363-907X</issn><issn>1099-114X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp10M1KAzEQAOAgCtYqvkLAgwfZmr_d7R6l1B-oCEWht5BNJyV1m6zZtFJPPoLP6JOYWq8ehpmQjxlmEDqnZEAJYdcQBkLk9AD1KKmqjFIxO0Q9wgueVaScHaOTrlsSkv5o2UPN47qJ9vvzy9dL0NFuAPs22pX9UNF6h-fQ2YXD3uC2URESNNbhjWp9wAtwEFRMlUnRrVsIOthotWqwDwvlrMZT5V6tA6y3uoFTdGRU08HZX-6jl9vx8-g-mzzdPYxuJpnmjNGM05JASYY8B1UTPheGDwWQXBhVGwNUM54WVEbnTKeXYgUDUddzQcGUeUV4H13s-7bBv62hi3Lp18GlkZIxUuWcF1WR1OVe6eC7LoCRbbArFbaSErk7pYQgd6dM8mov320D2_-YHE9_9Q9Z_ngK</recordid><startdate>201905</startdate><enddate>201905</enddate><creator>Xu, Guoqiang</creator><creator>Zhu, Pengju</creator><creator>Quan, Yongkai</creator><creator>Dong, Bensi</creator><creator>Jin, Ruifan</creator><general>Hindawi Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7ST</scope><scope>7TB</scope><scope>7TN</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>F28</scope><scope>FR3</scope><scope>H96</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0002-9340-2804</orcidid></search><sort><creationdate>201905</creationdate><title>Multi‐objective optimization design of plate‐fin vapor generator for supercritical organic Rankine cycle</title><author>Xu, Guoqiang ; Zhu, Pengju ; Quan, Yongkai ; Dong, Bensi ; Jin, Ruifan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3221-3170e70835eab03d4f384e054fabffe1c23451afc52ce1ca262e4bbd41ef75903</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Classification</topic><topic>Computational fluid dynamics</topic><topic>Design</topic><topic>Design optimization</topic><topic>Entropy</topic><topic>Exergy</topic><topic>Finite volume method</topic><topic>Flow rates</topic><topic>Flow velocity</topic><topic>Fluids</topic><topic>genetic algorithm</topic><topic>Genetic algorithms</topic><topic>Heat exchangers</topic><topic>Heat recovery</topic><topic>Heat transfer</topic><topic>Inlet temperature</topic><topic>Mass flow</topic><topic>Mathematical models</topic><topic>Mathematics</topic><topic>multi‐objective optimization</topic><topic>plate‐fin heat exchanger</topic><topic>Power efficiency</topic><topic>Rankine cycle</topic><topic>Sorting algorithms</topic><topic>Supercritical fluids</topic><topic>supercritical organic Rankine cycle</topic><topic>Thermodynamic efficiency</topic><topic>vapor generator</topic><topic>Vaporizers</topic><topic>Vapors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xu, Guoqiang</creatorcontrib><creatorcontrib>Zhu, Pengju</creatorcontrib><creatorcontrib>Quan, Yongkai</creatorcontrib><creatorcontrib>Dong, Bensi</creatorcontrib><creatorcontrib>Jin, Ruifan</creatorcontrib><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Environment Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Environment Abstracts</collection><jtitle>International journal of energy research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xu, Guoqiang</au><au>Zhu, Pengju</au><au>Quan, Yongkai</au><au>Dong, Bensi</au><au>Jin, Ruifan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multi‐objective optimization design of plate‐fin vapor generator for supercritical organic Rankine cycle</atitle><jtitle>International journal of energy research</jtitle><date>2019-05</date><risdate>2019</risdate><volume>43</volume><issue>6</issue><spage>2312</spage><epage>2326</epage><pages>2312-2326</pages><artnum>er.4451</artnum><issn>0363-907X</issn><eissn>1099-114X</eissn><abstract>Summary
Supercritical organic Rankine cycle (SORC) is an improved ORC architecture with lower exergy destruction and better heat source utilization when compared with a subcritical one. The accurate design of its vapor generator is of critical importance due to the fact that heat transfer performance significantly affects thermal efficiency, power output, and size of the overall system. This paper aims to develop a mathematical model of the SORC vapor generator using plate‐fin heat exchanger. The finite volume method is applied to deal with the properties' variation problem of the supercritical fluids. Multi‐objective optimization is employed by the nondominated sorting genetic algorithm II to find the optimum geometry design. The objective functions are the number of entropy production units, annual cost, and volume. For a specific SORC system, an optimum vapor generator is designed using the developed model. Parametric studies are conducted to assess the effect of geometry parameters on the vapor generator performance. The off‐design performance of the vapor generator is also evaluated under different mass flow rates and different heat source inlet temperature conditions.
A mathematical model of the SORC vapor generator using plate‐fin heat exchanger is developed. The finite volume method is applied to deal with the properties variation problem of the supercritical fluids. Multi‐objective optimization is employed by the nondominated sorting genetic algorithm II to find the optimum geometry design of the vapor generator according to its entropy generation units, annual cost, and volume.</abstract><cop>Bognor Regis</cop><pub>Hindawi Limited</pub><doi>10.1002/er.4451</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-9340-2804</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | International journal of energy research, 2019-05, Vol.43 (6), p.2312-2326, Article er.4451 |
| issn | 0363-907X 1099-114X |
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| source | Wiley-Blackwell Journals |
| subjects | Classification Computational fluid dynamics Design Design optimization Entropy Exergy Finite volume method Flow rates Flow velocity Fluids genetic algorithm Genetic algorithms Heat exchangers Heat recovery Heat transfer Inlet temperature Mass flow Mathematical models Mathematics multi‐objective optimization plate‐fin heat exchanger Power efficiency Rankine cycle Sorting algorithms Supercritical fluids supercritical organic Rankine cycle Thermodynamic efficiency vapor generator Vaporizers Vapors |
| title | Multi‐objective optimization design of plate‐fin vapor generator for supercritical organic Rankine cycle |
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