Metamodels of a gas turbine powered marine propulsion system for simulation and diagnostic purposes
The paper presents the application of artificial neural network for simulation and diagnostic purposes applied to a gas turbine powered marine propulsion plant. A simulation code for the propulsion system, developed by the authors, has been extended to take into account components degradation or mal...
Gespeichert in:
Veröffentlicht in: | Journal of naval architecture and marine engineering 2015-07, Vol.12 (1), p.1-14 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 14 |
---|---|
container_issue | 1 |
container_start_page | 1 |
container_title | Journal of naval architecture and marine engineering |
container_volume | 12 |
creator | Campora, U. Capelli, M. Cravero, C. Zaccone, R. |
description | The paper presents the application of artificial neural network for simulation and diagnostic purposes applied to a gas turbine powered marine propulsion plant. A simulation code for the propulsion system, developed by the authors, has been extended to take into account components degradation or malfunctioning with the addition of performance reduction coefficients. The above coefficients become input variables to the analysis method and define the system status at a given operating point. The simulator is used to generate databases needed to perform a variable selection analysis and to tune response surfaces for both direct (simulation) and inverse (diagnostic) purposes. The application of the methodology to the propulsion system of an existing frigate version demonstrate the potential of the approach. |
doi_str_mv | 10.3329/jname.v12i1.19719 |
format | Article |
fullrecord | <record><control><sourceid>crossref</sourceid><recordid>TN_cdi_crossref_primary_10_3329_jname_v12i1_19719</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>10_3329_jname_v12i1_19719</sourcerecordid><originalsourceid>FETCH-LOGICAL-c245t-7f6440fb98fac9e39cb4e23a282413f8fcbbee6d1bed09b8d198de26b4c9feb33</originalsourceid><addsrcrecordid>eNot0MtOwzAQBVALgURV-gHs_AMpfqWxl6jiJRWxgXXkx7gySuLIk4D699DAanRncXV1CLnlbCulMHefg-1h-8VF4ltuGm4uyEqwhlXaGH1JVlxzWela1tdkg5gcU6pRNW_kivhXmGyfA3RIc6SWHi3SaS4uDUDH_A0FAu1tWWLJ49xhygPFE07Q05gLxdTPnZ3OXzsEGpI9Dhmn5Ok4lzEj4A25irZD2PzfNfl4fHjfP1eHt6eX_f2h8kLVU9XEnVIsOqOj9Qak8U6BkFZoobiMOnrnAHaBOwjMOB240QHEzilvIjgp14T_9fqSEQvEdizpd_up5aw9Q7ULVLtAtQuU_AEMUGG1</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Metamodels of a gas turbine powered marine propulsion system for simulation and diagnostic purposes</title><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Campora, U. ; Capelli, M. ; Cravero, C. ; Zaccone, R.</creator><creatorcontrib>Campora, U. ; Capelli, M. ; Cravero, C. ; Zaccone, R.</creatorcontrib><description>The paper presents the application of artificial neural network for simulation and diagnostic purposes applied to a gas turbine powered marine propulsion plant. A simulation code for the propulsion system, developed by the authors, has been extended to take into account components degradation or malfunctioning with the addition of performance reduction coefficients. The above coefficients become input variables to the analysis method and define the system status at a given operating point. The simulator is used to generate databases needed to perform a variable selection analysis and to tune response surfaces for both direct (simulation) and inverse (diagnostic) purposes. The application of the methodology to the propulsion system of an existing frigate version demonstrate the potential of the approach.</description><identifier>ISSN: 1813-8535</identifier><identifier>EISSN: 2070-8998</identifier><identifier>DOI: 10.3329/jname.v12i1.19719</identifier><language>eng</language><ispartof>Journal of naval architecture and marine engineering, 2015-07, Vol.12 (1), p.1-14</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c245t-7f6440fb98fac9e39cb4e23a282413f8fcbbee6d1bed09b8d198de26b4c9feb33</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,860,27901,27902</link.rule.ids></links><search><creatorcontrib>Campora, U.</creatorcontrib><creatorcontrib>Capelli, M.</creatorcontrib><creatorcontrib>Cravero, C.</creatorcontrib><creatorcontrib>Zaccone, R.</creatorcontrib><title>Metamodels of a gas turbine powered marine propulsion system for simulation and diagnostic purposes</title><title>Journal of naval architecture and marine engineering</title><description>The paper presents the application of artificial neural network for simulation and diagnostic purposes applied to a gas turbine powered marine propulsion plant. A simulation code for the propulsion system, developed by the authors, has been extended to take into account components degradation or malfunctioning with the addition of performance reduction coefficients. The above coefficients become input variables to the analysis method and define the system status at a given operating point. The simulator is used to generate databases needed to perform a variable selection analysis and to tune response surfaces for both direct (simulation) and inverse (diagnostic) purposes. The application of the methodology to the propulsion system of an existing frigate version demonstrate the potential of the approach.</description><issn>1813-8535</issn><issn>2070-8998</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNot0MtOwzAQBVALgURV-gHs_AMpfqWxl6jiJRWxgXXkx7gySuLIk4D699DAanRncXV1CLnlbCulMHefg-1h-8VF4ltuGm4uyEqwhlXaGH1JVlxzWela1tdkg5gcU6pRNW_kivhXmGyfA3RIc6SWHi3SaS4uDUDH_A0FAu1tWWLJ49xhygPFE07Q05gLxdTPnZ3OXzsEGpI9Dhmn5Ok4lzEj4A25irZD2PzfNfl4fHjfP1eHt6eX_f2h8kLVU9XEnVIsOqOj9Qak8U6BkFZoobiMOnrnAHaBOwjMOB240QHEzilvIjgp14T_9fqSEQvEdizpd_up5aw9Q7ULVLtAtQuU_AEMUGG1</recordid><startdate>20150709</startdate><enddate>20150709</enddate><creator>Campora, U.</creator><creator>Capelli, M.</creator><creator>Cravero, C.</creator><creator>Zaccone, R.</creator><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20150709</creationdate><title>Metamodels of a gas turbine powered marine propulsion system for simulation and diagnostic purposes</title><author>Campora, U. ; Capelli, M. ; Cravero, C. ; Zaccone, R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c245t-7f6440fb98fac9e39cb4e23a282413f8fcbbee6d1bed09b8d198de26b4c9feb33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Campora, U.</creatorcontrib><creatorcontrib>Capelli, M.</creatorcontrib><creatorcontrib>Cravero, C.</creatorcontrib><creatorcontrib>Zaccone, R.</creatorcontrib><collection>CrossRef</collection><jtitle>Journal of naval architecture and marine engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Campora, U.</au><au>Capelli, M.</au><au>Cravero, C.</au><au>Zaccone, R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Metamodels of a gas turbine powered marine propulsion system for simulation and diagnostic purposes</atitle><jtitle>Journal of naval architecture and marine engineering</jtitle><date>2015-07-09</date><risdate>2015</risdate><volume>12</volume><issue>1</issue><spage>1</spage><epage>14</epage><pages>1-14</pages><issn>1813-8535</issn><eissn>2070-8998</eissn><abstract>The paper presents the application of artificial neural network for simulation and diagnostic purposes applied to a gas turbine powered marine propulsion plant. A simulation code for the propulsion system, developed by the authors, has been extended to take into account components degradation or malfunctioning with the addition of performance reduction coefficients. The above coefficients become input variables to the analysis method and define the system status at a given operating point. The simulator is used to generate databases needed to perform a variable selection analysis and to tune response surfaces for both direct (simulation) and inverse (diagnostic) purposes. The application of the methodology to the propulsion system of an existing frigate version demonstrate the potential of the approach.</abstract><doi>10.3329/jname.v12i1.19719</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1813-8535 |
ispartof | Journal of naval architecture and marine engineering, 2015-07, Vol.12 (1), p.1-14 |
issn | 1813-8535 2070-8998 |
language | eng |
recordid | cdi_crossref_primary_10_3329_jname_v12i1_19719 |
source | DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
title | Metamodels of a gas turbine powered marine propulsion system for simulation and diagnostic purposes |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-30T08%3A00%3A49IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Metamodels%20of%20a%20gas%20turbine%20powered%20marine%20propulsion%20system%20for%20simulation%20and%20diagnostic%20purposes&rft.jtitle=Journal%20of%20naval%20architecture%20and%20marine%20engineering&rft.au=Campora,%20U.&rft.date=2015-07-09&rft.volume=12&rft.issue=1&rft.spage=1&rft.epage=14&rft.pages=1-14&rft.issn=1813-8535&rft.eissn=2070-8998&rft_id=info:doi/10.3329/jname.v12i1.19719&rft_dat=%3Ccrossref%3E10_3329_jname_v12i1_19719%3C/crossref%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |