基于亚体素的纤维增强复合材料有限元建模

IF 1.3 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Software Impacts Pub Date : 2024-06-07 DOI:10.1016/j.simpa.2024.100668
Robert M. Auenhammer , Carolyn Oddy , Jisoo Kim , Lars P. Mikkelsen
{"title":"基于亚体素的纤维增强复合材料有限元建模","authors":"Robert M. Auenhammer ,&nbsp;Carolyn Oddy ,&nbsp;Jisoo Kim ,&nbsp;Lars P. Mikkelsen","doi":"10.1016/j.simpa.2024.100668","DOIUrl":null,"url":null,"abstract":"<div><p>For fibre-reinforced composites, most of their mechanical properties is tied to the fibre scale. Thus, imaging-based characterisation demands resolving fibres to characterise these materials accurately. However, high resolutions limit the field of view and lead to lengthy acquisition times. Emerging non-destructive imaging technologies and algorithms now accurately provide fibre orientations without detecting individual fibres. Studies show that voxel sizes up to fifteen times the fibre diameter are feasible, still allowing accurate tensile modulus predictions. Our presented software incorporates sub-voxel fibre orientation distributions using ultra-low-resolution three-dimensional X-ray tomography data in a numerical model, providing an effective method for characterising these materials.</p></div>","PeriodicalId":29771,"journal":{"name":"Software Impacts","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665963824000563/pdfft?md5=eee17d9ca87024d7732bf38424b4ffac&pid=1-s2.0-S2665963824000563-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Sub-voxel based finite element modelling of fibre-reinforced composites\",\"authors\":\"Robert M. Auenhammer ,&nbsp;Carolyn Oddy ,&nbsp;Jisoo Kim ,&nbsp;Lars P. Mikkelsen\",\"doi\":\"10.1016/j.simpa.2024.100668\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>For fibre-reinforced composites, most of their mechanical properties is tied to the fibre scale. Thus, imaging-based characterisation demands resolving fibres to characterise these materials accurately. However, high resolutions limit the field of view and lead to lengthy acquisition times. Emerging non-destructive imaging technologies and algorithms now accurately provide fibre orientations without detecting individual fibres. Studies show that voxel sizes up to fifteen times the fibre diameter are feasible, still allowing accurate tensile modulus predictions. Our presented software incorporates sub-voxel fibre orientation distributions using ultra-low-resolution three-dimensional X-ray tomography data in a numerical model, providing an effective method for characterising these materials.</p></div>\",\"PeriodicalId\":29771,\"journal\":{\"name\":\"Software Impacts\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2024-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2665963824000563/pdfft?md5=eee17d9ca87024d7732bf38424b4ffac&pid=1-s2.0-S2665963824000563-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Software Impacts\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2665963824000563\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software Impacts","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2665963824000563","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0

摘要

对于纤维增强复合材料而言,其大部分机械特性都与纤维尺度有关。因此,基于成像的表征技术要求对纤维进行分辨,以准确表征这些材料。然而,高分辨率限制了视野,导致采集时间过长。现在,新兴的非破坏性成像技术和算法可以在不检测单个纤维的情况下准确提供纤维方向。研究表明,体素尺寸可达纤维直径的 15 倍是可行的,但仍能准确预测拉伸模量。我们介绍的软件将使用超低分辨三维 X 射线断层扫描数据的子体素纤维取向分布纳入数值模型中,为表征这些材料提供了一种有效的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Sub-voxel based finite element modelling of fibre-reinforced composites

For fibre-reinforced composites, most of their mechanical properties is tied to the fibre scale. Thus, imaging-based characterisation demands resolving fibres to characterise these materials accurately. However, high resolutions limit the field of view and lead to lengthy acquisition times. Emerging non-destructive imaging technologies and algorithms now accurately provide fibre orientations without detecting individual fibres. Studies show that voxel sizes up to fifteen times the fibre diameter are feasible, still allowing accurate tensile modulus predictions. Our presented software incorporates sub-voxel fibre orientation distributions using ultra-low-resolution three-dimensional X-ray tomography data in a numerical model, providing an effective method for characterising these materials.

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
Software Impacts
Software Impacts Software
CiteScore
2.70
自引率
9.50%
发文量
0
审稿时长
16 days
期刊最新文献
HoughVG:Hough Transform Toolbox for Straight-Line Detection and Fingerprint Recognition rXTalkViz: A R package to quantify, visualize, and report carcinogenic footprints of functional pathway cross-talks AudioSecure: An open-source code to secure data using interpolation and multi-layering techniques within audio covers HV-Inv: A MATLAB-based graphical tool for the direct and inverse problems of the horizontal-to-vertical spectral ratio under the diffuse field theory FEGC 1.0: Flow Energy Gradient Calculator as a toolbox for predicting fluid flow instability initiation locus
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1