Data- and simulation-based material behaviour prediction

Anton Dybov, Carina Fresemann, Rainer Stark
{"title":"Data- and simulation-based material behaviour prediction","authors":"Anton Dybov, Carina Fresemann, Rainer Stark","doi":"10.1017/pds.2024.59","DOIUrl":null,"url":null,"abstract":"In research environments and laboratories e.g. for material sciences the in- and output of simulation data is manually managed. Therefore, physical experiments as well as simulations might be carried out several times, learnings are not systematically gathered, and experiments do not systematically build on learnings from data. This paper proposes to engage an ontology in conjunction with a simulation to use data from already carried out experiments and on that basis predict material behaviour under certain condition and plan further physical experiments.","PeriodicalId":489438,"journal":{"name":"Proceedings of the Design Society","volume":"4 10","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Design Society","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.1017/pds.2024.59","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In research environments and laboratories e.g. for material sciences the in- and output of simulation data is manually managed. Therefore, physical experiments as well as simulations might be carried out several times, learnings are not systematically gathered, and experiments do not systematically build on learnings from data. This paper proposes to engage an ontology in conjunction with a simulation to use data from already carried out experiments and on that basis predict material behaviour under certain condition and plan further physical experiments.
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
基于数据和模拟的材料性能预测
在材料科学等研究环境和实验室中,模拟数据的输入和输出都是人工管理的。因此,物理实验和仿真可能要进行多次,学习成果无法系统地收集,实验也无法系统地从数据中吸取经验教训。本文建议将本体与模拟结合起来,使用已进行过的实验数据,在此基础上预测材料在特定条件下的行为,并计划进一步的物理实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Designing lab-on-a-chip systems with attribute dependency graphs Implementing an open innovation process in the premium marine industry Variability in complex product/system design: case study in automotive industry Computing solution spaces for gear box design Machine learning-based virtual sensors for reduced energy consumption in frost-free refrigerators
×
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