A mechanical characteristic capture method considering printing configurations for buildability modeling in concrete 3D printing

IF 10.3 1区 工程技术 Q1 ENGINEERING, MANUFACTURING
Yuning Chen , Kailun Xia , Enlai Dong , Ruilin Cao , Yueyi Gao , Yamei Zhang
{"title":"A mechanical characteristic capture method considering printing configurations for buildability modeling in concrete 3D printing","authors":"Yuning Chen ,&nbsp;Kailun Xia ,&nbsp;Enlai Dong ,&nbsp;Ruilin Cao ,&nbsp;Yueyi Gao ,&nbsp;Yamei Zhang","doi":"10.1016/j.addma.2024.104462","DOIUrl":null,"url":null,"abstract":"<div><div>The structure failure modeling of 3D printing concrete (3DPC) during production is crucial for structure design, manufacturing process control and optimization. Serving as model inputs, the accuracy of 3DPC fresh material properties measurement highly affects the model prediction performance. The measured mechanical properties of freshly printed concrete strongly depend on the geometry, deformation and hardening process of used samples in testing. Herein, we propose an all-in-one method (AIOM) that synchronously considers these key factors (layer geometry, deformation, and hardening process) to more accurately capture the early-age mechanical performance distribution in printed structures. Different parametric-mechanical buckling models and two printable cementitious materials with distinct hardening characteristics (printable cement and printable geopolymer) were used to validate the performance of AIOM, with the traditional testing method, uniaxial unconfined compression test (UUCT), as the reference. Compared with UUCT, AIOM can improve the buildability prediction accuracy by 11.9 % to 50.8 % for different validation scenarios. This novel testing method for 3DPC fresh material properties contributes to improving the accuracy of 3DPC structure failure models, thereby facilitating a better production phase control for 3DPC.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"94 ","pages":"Article 104462"},"PeriodicalIF":10.3000,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Additive manufacturing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214860424005086","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0

Abstract

The structure failure modeling of 3D printing concrete (3DPC) during production is crucial for structure design, manufacturing process control and optimization. Serving as model inputs, the accuracy of 3DPC fresh material properties measurement highly affects the model prediction performance. The measured mechanical properties of freshly printed concrete strongly depend on the geometry, deformation and hardening process of used samples in testing. Herein, we propose an all-in-one method (AIOM) that synchronously considers these key factors (layer geometry, deformation, and hardening process) to more accurately capture the early-age mechanical performance distribution in printed structures. Different parametric-mechanical buckling models and two printable cementitious materials with distinct hardening characteristics (printable cement and printable geopolymer) were used to validate the performance of AIOM, with the traditional testing method, uniaxial unconfined compression test (UUCT), as the reference. Compared with UUCT, AIOM can improve the buildability prediction accuracy by 11.9 % to 50.8 % for different validation scenarios. This novel testing method for 3DPC fresh material properties contributes to improving the accuracy of 3DPC structure failure models, thereby facilitating a better production phase control for 3DPC.
一种考虑到打印配置的力学特征捕捉方法,用于混凝土三维打印中的可建性建模
三维打印混凝土(3DPC)生产过程中的结构失效建模对于结构设计、生产过程控制和优化至关重要。作为模型输入,3DPC 新材料性能测量的准确性对模型预测性能影响很大。新打印混凝土的测量力学性能与测试中所用样品的几何形状、变形和硬化过程密切相关。在此,我们提出一种多合一方法(AIOM),同步考虑这些关键因素(层几何形状、变形和硬化过程),以更准确地捕捉打印结构的早期力学性能分布。以传统的测试方法--单轴无约束压缩试验(UUCT)为参考,使用不同的参数力学屈曲模型和两种硬化特性不同的可印刷胶凝材料(可印刷水泥和可印刷土工聚合物)来验证 AIOM 的性能。与单轴无约束压缩试验相比,在不同的验证情况下,AIOM 可将可建性预测精度提高 11.9% 至 50.8%。这种新型的 3DPC 新材料性能测试方法有助于提高 3DPC 结构失效模型的准确性,从而更好地控制 3DPC 的生产阶段。
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 求助全文
来源期刊
Additive manufacturing
Additive manufacturing Materials Science-General Materials Science
CiteScore
19.80
自引率
12.70%
发文量
648
审稿时长
35 days
期刊介绍: Additive Manufacturing stands as a peer-reviewed journal dedicated to delivering high-quality research papers and reviews in the field of additive manufacturing, serving both academia and industry leaders. The journal's objective is to recognize the innovative essence of additive manufacturing and its diverse applications, providing a comprehensive overview of current developments and future prospects. The transformative potential of additive manufacturing technologies in product design and manufacturing is poised to disrupt traditional approaches. In response to this paradigm shift, a distinctive and comprehensive publication outlet was essential. Additive Manufacturing fulfills this need, offering a platform for engineers, materials scientists, and practitioners across academia and various industries to document and share innovations in these evolving technologies.
×
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