Applications of ANNs in flow and heat transfer problems in nuclear engineering: A review work
Artificial Neural Networks (ANNs) have been applied to deal with flow and heat transfer problems over the past two decades. In the present paper, recent work on the applications of ANNs for predicting the flow regime, pressure drop, void fraction, critical heat flux, onset of nucleate boiling, heat...
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| Veröffentlicht in: | Progress in nuclear energy (New series) 2013-01, Vol.62, p.54-71 |
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| creator | Cong, Tenglong Su, Guanghui Qiu, Suizheng Tian, Wenxi |
| description | Artificial Neural Networks (ANNs) have been applied to deal with flow and heat transfer problems over the past two decades. In the present paper, recent work on the applications of ANNs for predicting the flow regime, pressure drop, void fraction, critical heat flux, onset of nucleate boiling, heat transfer coefficient and boiling curve has been reviewed, respectively. As can be noted in this review work, various types of ANNs can be employed as predictors with acceptable precisions. At the end of this review, methods to improve performance of ANNs and further applications of ANNs in flow and heat transfer problems were introduced.
► ANNs used in flow and heat transfer problems in nuclear engineering were reviewed. ► ANNs have been widely used in nuclear thermohydraulic problems with good performance. ► Methods to improve performance of ANNs were introduced. ► Further applications of ANNs in flow and heat transfer problems were introduced. |
| doi_str_mv | 10.1016/j.pnucene.2012.09.003 |
| format | Article |
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► ANNs used in flow and heat transfer problems in nuclear engineering were reviewed. ► ANNs have been widely used in nuclear thermohydraulic problems with good performance. ► Methods to improve performance of ANNs were introduced. ► Further applications of ANNs in flow and heat transfer problems were introduced.</description><identifier>ISSN: 0149-1970</identifier><identifier>DOI: 10.1016/j.pnucene.2012.09.003</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Acceptability ; Artificial neural network ; Boiling ; Critical heat flux ; Flow regime identification ; Heat flux ; Heat transfer ; Heat transfer coefficient ; Heat transfer coefficients ; Nuclear engineering ; Nuclear reactor components ; Pressure drop ; Void fraction</subject><ispartof>Progress in nuclear energy (New series), 2013-01, Vol.62, p.54-71</ispartof><rights>2012 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c342t-893804f15259613e73360ddaffefd3a06a505b468decdeb020d2b4cb48f1c7013</citedby><cites>FETCH-LOGICAL-c342t-893804f15259613e73360ddaffefd3a06a505b468decdeb020d2b4cb48f1c7013</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.pnucene.2012.09.003$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Cong, Tenglong</creatorcontrib><creatorcontrib>Su, Guanghui</creatorcontrib><creatorcontrib>Qiu, Suizheng</creatorcontrib><creatorcontrib>Tian, Wenxi</creatorcontrib><title>Applications of ANNs in flow and heat transfer problems in nuclear engineering: A review work</title><title>Progress in nuclear energy (New series)</title><description>Artificial Neural Networks (ANNs) have been applied to deal with flow and heat transfer problems over the past two decades. In the present paper, recent work on the applications of ANNs for predicting the flow regime, pressure drop, void fraction, critical heat flux, onset of nucleate boiling, heat transfer coefficient and boiling curve has been reviewed, respectively. As can be noted in this review work, various types of ANNs can be employed as predictors with acceptable precisions. At the end of this review, methods to improve performance of ANNs and further applications of ANNs in flow and heat transfer problems were introduced.
► ANNs used in flow and heat transfer problems in nuclear engineering were reviewed. ► ANNs have been widely used in nuclear thermohydraulic problems with good performance. ► Methods to improve performance of ANNs were introduced. ► Further applications of ANNs in flow and heat transfer problems were introduced.</description><subject>Acceptability</subject><subject>Artificial neural network</subject><subject>Boiling</subject><subject>Critical heat flux</subject><subject>Flow regime identification</subject><subject>Heat flux</subject><subject>Heat transfer</subject><subject>Heat transfer coefficient</subject><subject>Heat transfer coefficients</subject><subject>Nuclear engineering</subject><subject>Nuclear reactor components</subject><subject>Pressure drop</subject><subject>Void fraction</subject><issn>0149-1970</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNqFkLtOwzAUhjOARCk8ApJHloRjO1cWVFXcpKosMCLLsY-LS-oEO6Xi7XFpd6az_Jfzf0lyRSGjQMubdTa4rUKHGQPKMmgyAH6STIDmTUqbCs6S8xDWALSiRTFJ3mfD0FklR9u7QHpDZstlINYR0_U7Ip0mHyhHMnrpgkFPBt-3HW7-JLGoQ-kJupV1iN661S2ZEY_fFndk1_vPi-TUyC7g5fFOk7eH-9f5U7p4eXyezxap4jkb07rhNeSGFqxoSsqx4rwEraUxaDSXUMoCijYva41KYwsMNGtz1ea1oaoCyqfJ9SE3vve1xTCKjQ0Ku0467LdB0DKuZTRnLEqLg1T5PgSPRgzebqT_ERTEHqFYiyNCsUcooBERYfTdHXwYd8SBXgRl0SnU1qMahe7tPwm_0b1_Vg</recordid><startdate>201301</startdate><enddate>201301</enddate><creator>Cong, Tenglong</creator><creator>Su, Guanghui</creator><creator>Qiu, Suizheng</creator><creator>Tian, Wenxi</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope></search><sort><creationdate>201301</creationdate><title>Applications of ANNs in flow and heat transfer problems in nuclear engineering: A review work</title><author>Cong, Tenglong ; Su, Guanghui ; Qiu, Suizheng ; Tian, Wenxi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c342t-893804f15259613e73360ddaffefd3a06a505b468decdeb020d2b4cb48f1c7013</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Acceptability</topic><topic>Artificial neural network</topic><topic>Boiling</topic><topic>Critical heat flux</topic><topic>Flow regime identification</topic><topic>Heat flux</topic><topic>Heat transfer</topic><topic>Heat transfer coefficient</topic><topic>Heat transfer coefficients</topic><topic>Nuclear engineering</topic><topic>Nuclear reactor components</topic><topic>Pressure drop</topic><topic>Void fraction</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cong, Tenglong</creatorcontrib><creatorcontrib>Su, Guanghui</creatorcontrib><creatorcontrib>Qiu, Suizheng</creatorcontrib><creatorcontrib>Tian, Wenxi</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Progress in nuclear energy (New series)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cong, Tenglong</au><au>Su, Guanghui</au><au>Qiu, Suizheng</au><au>Tian, Wenxi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Applications of ANNs in flow and heat transfer problems in nuclear engineering: A review work</atitle><jtitle>Progress in nuclear energy (New series)</jtitle><date>2013-01</date><risdate>2013</risdate><volume>62</volume><spage>54</spage><epage>71</epage><pages>54-71</pages><issn>0149-1970</issn><abstract>Artificial Neural Networks (ANNs) have been applied to deal with flow and heat transfer problems over the past two decades. In the present paper, recent work on the applications of ANNs for predicting the flow regime, pressure drop, void fraction, critical heat flux, onset of nucleate boiling, heat transfer coefficient and boiling curve has been reviewed, respectively. As can be noted in this review work, various types of ANNs can be employed as predictors with acceptable precisions. At the end of this review, methods to improve performance of ANNs and further applications of ANNs in flow and heat transfer problems were introduced.
► ANNs used in flow and heat transfer problems in nuclear engineering were reviewed. ► ANNs have been widely used in nuclear thermohydraulic problems with good performance. ► Methods to improve performance of ANNs were introduced. ► Further applications of ANNs in flow and heat transfer problems were introduced.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.pnucene.2012.09.003</doi><tpages>18</tpages></addata></record> |
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| ispartof | Progress in nuclear energy (New series), 2013-01, Vol.62, p.54-71 |
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| language | eng |
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| source | ScienceDirect Journals (5 years ago - present) |
| subjects | Acceptability Artificial neural network Boiling Critical heat flux Flow regime identification Heat flux Heat transfer Heat transfer coefficient Heat transfer coefficients Nuclear engineering Nuclear reactor components Pressure drop Void fraction |
| title | Applications of ANNs in flow and heat transfer problems in nuclear engineering: A review work |
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