An accurate forming model for capturing the nonlinear material behaviour of multilayered binder-stabilised fabrics and predicting fibre wrinkling
An accurate forming model for capturing the nonlinear material behaviour of multilayered binder-stabilised fabrics and predicting fibre wrinkling
复制标题
精确的成型模型，用于捕获多层粘合剂稳定织物的非线性材料行为并预测纤维起皱
DOI：
10.1016/j.compositesb.2024.111268
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发表时间：
2024
期刊：
影响因子：
12.8
通讯作者：
Broberg P
中科院分区：
文献类型：
--
作者：
Broberg P
在制造大型复合结构（如风力涡轮机叶片）时，使用预制的粘结剂稳定干织物堆叠来增加钢筋沉积速率。为了确保最佳的零件质量，可以使用精确的仿真工具来避免昂贵的试错实验。本文介绍了一种新的模型框架，用于预测由准单向无卷曲织物形成厚粘结剂稳定堆叠而产生的褶皱缺陷。在这种情况下，准单向无卷曲织物是用衬底层稳定的单向粗纱。采用非对称压缩模量对织物的非恒定弯曲刚度进行建模，采用自定义损伤演化的混合模内聚公式对织物的初始非恒定弹性粘结剂界面刚度和界面退化进行建模。通过单织物层的悬臂弯曲试验和粘结织物层的横向剪切试验对模型进行了验证。与预成形实验结果的比较表明，该模型能准确预测厚粘结剂稳定预成形过程中的褶皱位置和几何形状。与传统建模方法预测的皱纹相比，新建模方法预测的皱纹几何形状与实验测量的皱纹几何形状之间的误差减少了35%至94%。建模框架可以在https://doi.org/10.5281/zenodo.10077428上免费获得。
Prefabricated stacks of binder-stabilised dry fabrics are used to increase reinforcement deposition rates in the manufacturing of large composite structures such as wind turbine blades. To ensure optimal part quality, accurate simulation tools may be used to avoid costly trial-and-error experiments. This paper introduces a new modelling framework for predicting wrinkle defects that arise from forming thick binder-stabilised stacks of quasi-unidirectional non-crimp fabric. In this context, quasi-unidirectional non-crimp fabrics are unidirectional rovings stabilised with a backing layer. The non-constant bending stiffness of the fabric is modelled using an asymmetric compressive modulus, while a mixed-mode cohesive formulation with user-defined damage evolution is used for modelling the initial non-constant elastic binder interface stiffness and interface degradation. The model is verified against cantilever bending tests of single fabric layers and transverse shear experiments of bindered fabric layers. Comparison with experimental results on the forming of preforms shows that the model accurately predicts wrinkle location and geometry during the forming of thick binder-stabilised preforms. The error between the wrinkle geometry predicted by the new modelling approach and the experimentally measured wrinkle geometry is reduced by 35% to 94% compared to wrinkles predicted by conventional modelling approaches. The modelling framework is freely available at https://doi.org/10.5281/zenodo.10077428.
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