A-SMC压缩成型的三维流动和纤维取向建模:挤压流动的模拟和实验验证

Gustaf Alnersson, Erik Lejon, Hana Zrida, Yvonne Aitomäki, Anna-Lena Ljung, T. Staffan Lundström
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引用次数: 0

摘要

由于可以实现相对较短的制造时间,基于片状成型化合物(SMC)的复合材料在工业环境中具有很大的潜力。然而,能够数值预测零件的机械性能和可制造性是必要的。本文描述和讨论了基于流体力学的SMC压缩成型的全三维半经验模型,其中纤维和树脂被建模为单一的、不可分割的流体,其粘度取决于纤维的体积分数、剪切应变率和温度。该模型应用于具有高纤维体积分数(35%)的先进碳纤维SMC。模拟在一个挤压试验台模型上运行,允许与该试验台的实验结果进行比较。由该模型生成的流动数据随后被用作Advani-Tucker类型的模型的输入,该模型用于在挤压过程中纤维取向的演变。在3DTimon软件中也得到了数值结果。然后将所得纤维取向分布与显微镜获得的实验结果进行比较。利用椭圆法对取向张量进行了实验测量。提出了一种新的、自动化的、精确的、快速的椭圆拟合方法。实验结果与数值方法的对比表明,三维Timon能更好地捕捉到圆盘外缘的随机方向,而三维CFD在面外分量方面的一致性更强。新成像技术的优点之一是,只需较少的工作就能获得质量足够好的显微镜图像进行分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3D flow and fibre orientation modelling of compression moulding of A-SMC: simulations and experimental validation in squeeze flow

Sheet Moulding Compound (SMC) based composites have a large potential in industrial contexts due to the possibility of achieving comparatively short manufacturing times. It is however necessary to be able to numerically predict both mechanical properties as well as manufacturability of parts.

In this paper a fully 3D, semi-empirical model based on fluid mechanics for the compression moulding of SMC is described and discussed, in which the fibres and the resin are modelled as a single, inseparable fluid with a viscosity that depends on volume fraction of fibres, shear strain rate and temperature. This model is applied to an advanced carbon-fibre SMC with a high fibre volume fraction (35%). Simulations are run on a model of a squeeze test rig, allowing comparison to experimental results from such a rig. The flow data generated by this model is then used as input for an Advani-Tucker type of model for the evolution of the fibre orientation during the pressing process. Numerical results are also obtained from the software 3DTimon. The resulting fibre orientation distributions are then compared to experimental results that are obtained from microscopy. The experimental measurement of the orientation tensors is performed using the Method of Ellipses. A new, automated, accurate and fast method for the ellipse fitting is developed using machine learning. For the studied case, comparison between the experimental results and numerical methods indicate that 3D Timon better captures the random orientation at the outer edges of the circular disc, while 3D CFD show larger agreement in terms of the out-of-plane component. One of the advantages of the new image technique is that less work is required to obtain microscope images with a quality good enough for the analysis.

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