Experimental investigation, using 3D digital image correlation, into the effect of component geometry on the wrinkling behaviour and the wrinkling mechanisms of a biaxial NCF during preforming
Experimental investigation, using 3D digital image correlation, into the effect of component geometry on the wrinkling behaviour and the wrinkling mechanisms of a biaxial NCF during preforming
复制标题
使用 3D 数字图像相关性进行实验研究,研究部件几何形状对预成型过程中双轴 NCF 起皱行为和起皱机制的影响
DOI:
10.1016/j.compositesa.2020.106248
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发表时间:
2021
期刊:
影响因子:
--
通讯作者:
Viisainen J
中科院分区:
文献类型:
--
作者:
Viisainen J
This study investigates the effect of component geometry on the wrinkling mechanisms of non-crimp fabrics (NCFs) during preforming. Using 3D digital image correlation, the wrinkling behaviour of a biaxial NCF formed over four benchmark geometries is characterised and related to the NCF’s surface strains. It is shown that the effect of geometry on the severity of wrinkling is highly significant and that there are two possible wrinkling mechanisms (via shear lockup or via compression) for large wrinkles to occur, which are consistent across geometries. Importantly, an increase in local shear resistance (due to the stitches in this case) is shown to cause severe wrinkles in textile reinforcements at low shear angles due to lateral fabric compression. Additionally, tow wrinkling in NCFs is shown to correlate with local tow compression. Thus, it is not always valid to assume that fabrics are only likely to wrinkle during forming due to excessive shearing.
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影响因子:
6.3
作者:
H. Montazerian;A. Rashidi;M. Hoorfar;A. Milani
通讯作者:
H. Montazerian;A. Rashidi;M. Hoorfar;A. Milani
DOI:
10.1016/j.compositesa.2013.03.017
发表时间:
2013-08-01
影响因子:
8.7
作者:
Ouagne, P.;Soulat, D.;Gueret, S.
通讯作者:
Gueret, S.
DOI:
10.1016/j.compositesa.2019.105643
发表时间:
2020-01
期刊:
Composites Part A: Applied Science and Manufacturing
影响因子:
--
作者:
Mark A. Turk;Brúnó Vermes;A. Thompson;J. Belnoue;S. Hallett;D. Ivanov
通讯作者:
Mark A. Turk;Brúnó Vermes;A. Thompson;J. Belnoue;S. Hallett;D. Ivanov
影响因子:
9.1
作者:
Yu F
通讯作者:
Yu F
DOI:
10.1016/j.compositesa.2019.105651
发表时间:
2019-12-01
影响因子:
8.7
作者:
Shen, Hao;Wang, Peng;Liu, Lingshan
通讯作者:
Liu, Lingshan