{"title":"Detection of fatigue damage in stainless steel by EBSD analysis (analysis focused on grain boundaries)","authors":"M. Kuroda, M. Kamaya, Takayuki Mori, T. Izaki","doi":"10.1299/KIKAIA.79.1690","DOIUrl":null,"url":null,"abstract":"In order to develop more sensitive EBSD parameters to detect fatigue damage in austenitic stainless steel used as key material for nuclear reactor components, the new EBSD parameter focused on grain boundaries, which was referred to as the averaged grain boundary local misorientation (BMave), has been proposed by modifying the existing EBSD parameter of the averaged local misorientation (Mave). The applicability of the new parameter BMave to the fatigue damage detection was discussed by comparing with the exiting parameter Mave. As a result, it was found that BMave was more sensitive parameter than Mave. Especially, BMave (Option 1), which was calculated using the crystal orientations at points just adjacent to grain boundaries, was the most effective parameter for the fatigue damage detection.","PeriodicalId":388675,"journal":{"name":"Transactions of the Japan Society of Mechanical Engineers. A","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transactions of the Japan Society of Mechanical Engineers. A","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1299/KIKAIA.79.1690","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In order to develop more sensitive EBSD parameters to detect fatigue damage in austenitic stainless steel used as key material for nuclear reactor components, the new EBSD parameter focused on grain boundaries, which was referred to as the averaged grain boundary local misorientation (BMave), has been proposed by modifying the existing EBSD parameter of the averaged local misorientation (Mave). The applicability of the new parameter BMave to the fatigue damage detection was discussed by comparing with the exiting parameter Mave. As a result, it was found that BMave was more sensitive parameter than Mave. Especially, BMave (Option 1), which was calculated using the crystal orientations at points just adjacent to grain boundaries, was the most effective parameter for the fatigue damage detection.