• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

基于图形的瓦楞纸板压缩特性分析

Graph-Based Analysis for the Characterization of Corrugated Board Compression.

作者信息

Belfekih Taieb, Fitas Ricardo, Schaffrath Heinz-Joachim, Schabel Samuel

机构信息

Chair of Paper Technology and Mechanical Process Engineering, Technical University of Darmstadt, 64289 Darmstadt, Germany.

出版信息

Materials (Basel). 2024 Dec 12;17(24):6083. doi: 10.3390/ma17246083.

DOI:10.3390/ma17246083
PMID:39769683
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11727766/
Abstract

This paper proposes a novel approach to represent the geometry of the corrugated board profile during compression using graphs. Graphs are lighter than images, and the computational time of compression analysis is then significantly reduced compared to using the original image data for the same analysis. The main goal of using such graphs is to gain more knowledge about the mechanical behavior of corrugated boards under compression compared to the current load-deformation curve approach. A node tracking algorithm is applied to characterize the different phases occurring during the compression test in order to predict physical phenomena, including buckling and contact. The main results show that analyzing the nodes provides significant insights into the compression phases, which has not been achieved in the current state of the art. The authors believe that the objective of this research is crucial to better understanding the physics of corrugated boards under compression, and it can also be extended to other engineering structures.

摘要

本文提出了一种新颖的方法,利用图形来表示瓦楞纸板在压缩过程中的轮廓几何形状。图形比图像更轻量级,因此与使用原始图像数据进行相同分析相比,压缩分析的计算时间显著减少。使用此类图形的主要目的是,相较于当前的载荷-变形曲线方法,能够获取更多关于瓦楞纸板在压缩状态下力学行为的知识。应用节点跟踪算法来表征压缩测试过程中出现的不同阶段,以便预测包括屈曲和接触在内的物理现象。主要结果表明,分析节点能为压缩阶段提供重要见解,这是当前技术水平尚未实现的。作者认为,本研究的目标对于更好地理解瓦楞纸板在压缩状态下的物理特性至关重要,并且该方法还可扩展到其他工程结构。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/221a5a7d783d/materials-17-06083-g030.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/1968b0315c83/materials-17-06083-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/274dbdeb6c7b/materials-17-06083-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/d7a9b0f8e957/materials-17-06083-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/848bb0142b2d/materials-17-06083-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/3317348b817c/materials-17-06083-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/4a8b1e905658/materials-17-06083-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/34cb1f20d873/materials-17-06083-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/731e0c6a6e57/materials-17-06083-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/8286dfa275cc/materials-17-06083-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/687343576fa2/materials-17-06083-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/b474ccc1fb21/materials-17-06083-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/ccd3d1d2f5d3/materials-17-06083-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/045bc3d4aa60/materials-17-06083-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/21d9cdd8f59d/materials-17-06083-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/0b3534f136d8/materials-17-06083-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/2f8ca82d7b94/materials-17-06083-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/ba977bd1a332/materials-17-06083-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/6dd003e85374/materials-17-06083-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/bcedf8e45a2c/materials-17-06083-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/8046df533583/materials-17-06083-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/7011b3eefc1b/materials-17-06083-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/343211dfaf9d/materials-17-06083-g022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/e94c4979b624/materials-17-06083-g023.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/2032a98279bd/materials-17-06083-g024.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/4e7cb2c1061d/materials-17-06083-g025.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/f7c777f1bac5/materials-17-06083-g026.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/9b4721971b27/materials-17-06083-g027.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/b36ccc3a2279/materials-17-06083-g028.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/09ec7b3fdccb/materials-17-06083-g029.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/221a5a7d783d/materials-17-06083-g030.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/1968b0315c83/materials-17-06083-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/274dbdeb6c7b/materials-17-06083-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/d7a9b0f8e957/materials-17-06083-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/848bb0142b2d/materials-17-06083-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/3317348b817c/materials-17-06083-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/4a8b1e905658/materials-17-06083-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/34cb1f20d873/materials-17-06083-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/731e0c6a6e57/materials-17-06083-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/8286dfa275cc/materials-17-06083-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/687343576fa2/materials-17-06083-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/b474ccc1fb21/materials-17-06083-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/ccd3d1d2f5d3/materials-17-06083-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/045bc3d4aa60/materials-17-06083-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/21d9cdd8f59d/materials-17-06083-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/0b3534f136d8/materials-17-06083-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/2f8ca82d7b94/materials-17-06083-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/ba977bd1a332/materials-17-06083-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/6dd003e85374/materials-17-06083-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/bcedf8e45a2c/materials-17-06083-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/8046df533583/materials-17-06083-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/7011b3eefc1b/materials-17-06083-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/343211dfaf9d/materials-17-06083-g022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/e94c4979b624/materials-17-06083-g023.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/2032a98279bd/materials-17-06083-g024.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/4e7cb2c1061d/materials-17-06083-g025.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/f7c777f1bac5/materials-17-06083-g026.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/9b4721971b27/materials-17-06083-g027.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/b36ccc3a2279/materials-17-06083-g028.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/09ec7b3fdccb/materials-17-06083-g029.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8ee/11727766/221a5a7d783d/materials-17-06083-g030.jpg

相似文献

1
Graph-Based Analysis for the Characterization of Corrugated Board Compression.基于图形的瓦楞纸板压缩特性分析
Materials (Basel). 2024 Dec 12;17(24):6083. doi: 10.3390/ma17246083.
2
Identification of Geometric Features of the Corrugated Board Using Images and Genetic Algorithm.使用图像和遗传算法识别瓦楞纸板的几何特征。
Sensors (Basel). 2023 Jul 7;23(13):6242. doi: 10.3390/s23136242.
3
Deciphering Double-Walled Corrugated Board Geometry Using Image Analysis and Genetic Algorithms.利用图像分析和遗传算法解析双壁波纹纸板几何形状
Sensors (Basel). 2024 Mar 9;24(6):1772. doi: 10.3390/s24061772.
4
Evaluation of wave configurations in corrugated boards by experimental analysis (EA) and finite element modeling (FEM): the role of the micro-wave in packaging design.通过实验分析(EA)和有限元建模(FEM)评估瓦楞纸板中的波状结构:微波在包装设计中的作用。
Int J Adv Manuf Technol. 2023;126(11-12):4963-4982. doi: 10.1007/s00170-023-11397-y. Epub 2023 Apr 25.
5
In-Situ Classification of Highly Deformed Corrugated Board Using Convolution Neural Networks.基于卷积神经网络的高度变形瓦楞纸板原位分类
Sensors (Basel). 2024 Feb 6;24(4):1051. doi: 10.3390/s24041051.
6
Mechanical Behavior Modeling of Containers and Octabins Made of Corrugated Cardboard Subjected to Vertical Stacking Loads.承受垂直堆叠载荷的瓦楞纸板制成的容器和八格箱的力学行为建模
Materials (Basel). 2021 May 4;14(9):2392. doi: 10.3390/ma14092392.
7
Analytical Determination of the Bending Stiffness of a Five-Layer Corrugated Cardboard with Imperfections.具有缺陷的五层瓦楞纸板弯曲刚度的解析测定
Materials (Basel). 2022 Jan 16;15(2):663. doi: 10.3390/ma15020663.
8
Investigation of the Effect of Pallet Top-Deck Stiffness on Corrugated Box Compression Strength as a Function of Multiple Unit Load Design Variables.托盘顶层刚度对瓦楞纸箱抗压强度的影响研究——作为多单元负载设计变量的函数
Materials (Basel). 2021 Nov 3;14(21):6613. doi: 10.3390/ma14216613.
9
Proximity-Based Compression for Network Embedding.基于邻近度的网络嵌入压缩
Front Big Data. 2021 Jan 26;3:608043. doi: 10.3389/fdata.2020.608043. eCollection 2020.
10
Influence of Analog and Digital Crease Lines on Mechanical Parameters of Corrugated Board and Packaging.瓦楞纸板和包装的模拟和数字压痕线对机械参数的影响。
Sensors (Basel). 2022 Jun 25;22(13):4800. doi: 10.3390/s22134800.

本文引用的文献

1
Deciphering Double-Walled Corrugated Board Geometry Using Image Analysis and Genetic Algorithms.利用图像分析和遗传算法解析双壁波纹纸板几何形状
Sensors (Basel). 2024 Mar 9;24(6):1772. doi: 10.3390/s24061772.
2
Identification of Geometric Features of the Corrugated Board Using Images and Genetic Algorithm.使用图像和遗传算法识别瓦楞纸板的几何特征。
Sensors (Basel). 2023 Jul 7;23(13):6242. doi: 10.3390/s23136242.