小数据集评价主曲线材料不均匀性

K. Wallin
{"title":"小数据集评价主曲线材料不均匀性","authors":"K. Wallin","doi":"10.1115/PVP2018-84297","DOIUrl":null,"url":null,"abstract":"The standard Master Curve (MC) deals only with materials assumed to be homogeneous, but MC analysis methods for inhomogeneous materials have also been developed. Especially the bi-modal and multi-modal analysis methods are becoming more and more standard. Their drawback is that these methods are generally reliable only with sufficiently large data sets (number of valid tests, r ≥ 15–20). Here, the possibility of using the multi-modal analysis method with smaller data sets is assessed, and a new procedure to conservatively account for possible inhomogeneities is proposed.","PeriodicalId":128383,"journal":{"name":"Volume 1A: Codes and Standards","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessment of Master Curve Material Inhomogeneity Using Small Data Sets\",\"authors\":\"K. Wallin\",\"doi\":\"10.1115/PVP2018-84297\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The standard Master Curve (MC) deals only with materials assumed to be homogeneous, but MC analysis methods for inhomogeneous materials have also been developed. Especially the bi-modal and multi-modal analysis methods are becoming more and more standard. Their drawback is that these methods are generally reliable only with sufficiently large data sets (number of valid tests, r ≥ 15–20). Here, the possibility of using the multi-modal analysis method with smaller data sets is assessed, and a new procedure to conservatively account for possible inhomogeneities is proposed.\",\"PeriodicalId\":128383,\"journal\":{\"name\":\"Volume 1A: Codes and Standards\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Volume 1A: Codes and Standards\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/PVP2018-84297\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 1A: Codes and Standards","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/PVP2018-84297","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

标准的主曲线(MC)只处理假定为均匀的材料,但也发展了非均匀材料的MC分析方法。特别是双模态和多模态分析方法越来越规范。它们的缺点是,这些方法通常只有在足够大的数据集(有效测试的数量,r≥15-20)时才可靠。本文评估了在较小数据集上使用多模态分析方法的可能性,并提出了一种保守地考虑可能的不均匀性的新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessment of Master Curve Material Inhomogeneity Using Small Data Sets
The standard Master Curve (MC) deals only with materials assumed to be homogeneous, but MC analysis methods for inhomogeneous materials have also been developed. Especially the bi-modal and multi-modal analysis methods are becoming more and more standard. Their drawback is that these methods are generally reliable only with sufficiently large data sets (number of valid tests, r ≥ 15–20). Here, the possibility of using the multi-modal analysis method with smaller data sets is assessed, and a new procedure to conservatively account for possible inhomogeneities is proposed.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信