Mechanical Characterisation of Thermal Barrier Coatings Using a Micro-Indentation Instrumented Technique

Mechanical Characterisation of Thermal Barrier Coatings Using a Micro-Indentation Instrumented Technique

An original instrumented microindenter capable of testing materials up to 1000°C in an inert atmosphere has been developed. The method of neural networks is used to solve the inverse problem, in order to determine the constitutive equation of the materials tested. To obtain a data basis for the trai...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Key engineering materials 2007-08, Vol.345-346, p.829-832
Hauptverfasser: Leroy, Francois Henri, Passily, Bruno, Kanoute, Pascale
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 832
container_issue
container_start_page 829
container_title Key engineering materials
container_volume 345-346
creator Leroy, Francois Henri
Passily, Bruno
Kanoute, Pascale
description An original instrumented microindenter capable of testing materials up to 1000°C in an inert atmosphere has been developed. The method of neural networks is used to solve the inverse problem, in order to determine the constitutive equation of the materials tested. To obtain a data basis for the training and validation of the neural network, finite element simulations were carried out for various sets of material parameters. To reduce the number of simulations a representative sampling of the loading-strain responses is performed using an unsupervised network, so-called self-organizing map.
doi_str_mv 10.4028/www.scientific.net/KEM.345-346.829
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_29848125</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>29848125</sourcerecordid><originalsourceid>FETCH-LOGICAL-c236t-a47cde72da4e1106a2a558cd8d8d92ba0e1d9130bc7f99b5cc7d51ee29992a723</originalsourceid><addsrcrecordid>eNqVkE1PwzAMhisEEmPwH3rigNQuST9zZGPAxCYu2znyUpdm2tKRpJr49xgNiTOKIsey89rvE0UPnKU5E_XkdDqlXhu0wbRGpxbD5G2-SrO8SLK8TGshL6IRL0uRyEoWl_RmPEtkLcrr6Mb7HWMZr3kxiroV6g6s0bCPZx040AGd8RBMb-O-jdcdugPVpuCcQRfPeirZDx9vPIUY4pXRrk8WtqFdzr8W1gc3HCjHJl6TvDWfA95GVy3sPd79xnG0eZ6vZ6_J8v1lMXtcJlpkZUggr3SDlWggR85ZCQKKotZNTUeKLTDkjeQZ2-qqlXJbaF01BUcUUkoBlcjG0f1Z9-h6GuuDOhivcb8Hi_3glZB1XnNRUOP03Ej7e--wVUdnDuC-FGfqB7IiyOoPsiLIiiArgky3VASZRJ7OIsEB2SazatcPzpLD_8h8Ax9RkoI</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>29848125</pqid></control><display><type>article</type><title>Mechanical Characterisation of Thermal Barrier Coatings Using a Micro-Indentation Instrumented Technique</title><source>Scientific.net Journals</source><creator>Leroy, Francois Henri ; Passily, Bruno ; Kanoute, Pascale</creator><creatorcontrib>Leroy, Francois Henri ; Passily, Bruno ; Kanoute, Pascale</creatorcontrib><description>An original instrumented microindenter capable of testing materials up to 1000°C in an inert atmosphere has been developed. The method of neural networks is used to solve the inverse problem, in order to determine the constitutive equation of the materials tested. To obtain a data basis for the training and validation of the neural network, finite element simulations were carried out for various sets of material parameters. To reduce the number of simulations a representative sampling of the loading-strain responses is performed using an unsupervised network, so-called self-organizing map.</description><identifier>ISSN: 1013-9826</identifier><identifier>ISSN: 1662-9795</identifier><identifier>EISSN: 1662-9795</identifier><identifier>DOI: 10.4028/www.scientific.net/KEM.345-346.829</identifier><language>eng</language><publisher>Trans Tech Publications Ltd</publisher><ispartof>Key engineering materials, 2007-08, Vol.345-346, p.829-832</ispartof><rights>2007 Trans Tech Publications Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c236t-a47cde72da4e1106a2a558cd8d8d92ba0e1d9130bc7f99b5cc7d51ee29992a723</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttps://www.scientific.net/Image/TitleCover/70?width=600</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Leroy, Francois Henri</creatorcontrib><creatorcontrib>Passily, Bruno</creatorcontrib><creatorcontrib>Kanoute, Pascale</creatorcontrib><title>Mechanical Characterisation of Thermal Barrier Coatings Using a Micro-Indentation Instrumented Technique</title><title>Key engineering materials</title><description>An original instrumented microindenter capable of testing materials up to 1000°C in an inert atmosphere has been developed. The method of neural networks is used to solve the inverse problem, in order to determine the constitutive equation of the materials tested. To obtain a data basis for the training and validation of the neural network, finite element simulations were carried out for various sets of material parameters. To reduce the number of simulations a representative sampling of the loading-strain responses is performed using an unsupervised network, so-called self-organizing map.</description><issn>1013-9826</issn><issn>1662-9795</issn><issn>1662-9795</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><recordid>eNqVkE1PwzAMhisEEmPwH3rigNQuST9zZGPAxCYu2znyUpdm2tKRpJr49xgNiTOKIsey89rvE0UPnKU5E_XkdDqlXhu0wbRGpxbD5G2-SrO8SLK8TGshL6IRL0uRyEoWl_RmPEtkLcrr6Mb7HWMZr3kxiroV6g6s0bCPZx040AGd8RBMb-O-jdcdugPVpuCcQRfPeirZDx9vPIUY4pXRrk8WtqFdzr8W1gc3HCjHJl6TvDWfA95GVy3sPd79xnG0eZ6vZ6_J8v1lMXtcJlpkZUggr3SDlWggR85ZCQKKotZNTUeKLTDkjeQZ2-qqlXJbaF01BUcUUkoBlcjG0f1Z9-h6GuuDOhivcb8Hi_3glZB1XnNRUOP03Ej7e--wVUdnDuC-FGfqB7IiyOoPsiLIiiArgky3VASZRJ7OIsEB2SazatcPzpLD_8h8Ax9RkoI</recordid><startdate>20070815</startdate><enddate>20070815</enddate><creator>Leroy, Francois Henri</creator><creator>Passily, Bruno</creator><creator>Kanoute, Pascale</creator><general>Trans Tech Publications Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SR</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope></search><sort><creationdate>20070815</creationdate><title>Mechanical Characterisation of Thermal Barrier Coatings Using a Micro-Indentation Instrumented Technique</title><author>Leroy, Francois Henri ; Passily, Bruno ; Kanoute, Pascale</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c236t-a47cde72da4e1106a2a558cd8d8d92ba0e1d9130bc7f99b5cc7d51ee29992a723</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Leroy, Francois Henri</creatorcontrib><creatorcontrib>Passily, Bruno</creatorcontrib><creatorcontrib>Kanoute, Pascale</creatorcontrib><collection>CrossRef</collection><collection>Engineered Materials Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><jtitle>Key engineering materials</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Leroy, Francois Henri</au><au>Passily, Bruno</au><au>Kanoute, Pascale</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mechanical Characterisation of Thermal Barrier Coatings Using a Micro-Indentation Instrumented Technique</atitle><jtitle>Key engineering materials</jtitle><date>2007-08-15</date><risdate>2007</risdate><volume>345-346</volume><spage>829</spage><epage>832</epage><pages>829-832</pages><issn>1013-9826</issn><issn>1662-9795</issn><eissn>1662-9795</eissn><abstract>An original instrumented microindenter capable of testing materials up to 1000°C in an inert atmosphere has been developed. The method of neural networks is used to solve the inverse problem, in order to determine the constitutive equation of the materials tested. To obtain a data basis for the training and validation of the neural network, finite element simulations were carried out for various sets of material parameters. To reduce the number of simulations a representative sampling of the loading-strain responses is performed using an unsupervised network, so-called self-organizing map.</abstract><pub>Trans Tech Publications Ltd</pub><doi>10.4028/www.scientific.net/KEM.345-346.829</doi><tpages>4</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1013-9826
ispartof Key engineering materials, 2007-08, Vol.345-346, p.829-832
issn 1013-9826
1662-9795
1662-9795
language eng
recordid cdi_proquest_miscellaneous_29848125
source Scientific.net Journals
title Mechanical Characterisation of Thermal Barrier Coatings Using a Micro-Indentation Instrumented Technique
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-14T08%3A53%3A09IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Mechanical%20Characterisation%20of%20Thermal%20Barrier%20Coatings%20Using%20a%20Micro-Indentation%20Instrumented%20Technique&rft.jtitle=Key%20engineering%20materials&rft.au=Leroy,%20Francois%20Henri&rft.date=2007-08-15&rft.volume=345-346&rft.spage=829&rft.epage=832&rft.pages=829-832&rft.issn=1013-9826&rft.eissn=1662-9795&rft_id=info:doi/10.4028/www.scientific.net/KEM.345-346.829&rft_dat=%3Cproquest_cross%3E29848125%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=29848125&rft_id=info:pmid/&rfr_iscdi=true