Robert M. Auenhammer , Carolyn Oddy , Jisoo Kim , Lars P. Mikkelsen
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引用次数: 0
摘要
对于纤维增强复合材料而言,其大部分机械特性都与纤维尺度有关。因此,基于成像的表征技术要求对纤维进行分辨,以准确表征这些材料。然而,高分辨率限制了视野,导致采集时间过长。现在,新兴的非破坏性成像技术和算法可以在不检测单个纤维的情况下准确提供纤维方向。研究表明,体素尺寸可达纤维直径的 15 倍是可行的,但仍能准确预测拉伸模量。我们介绍的软件将使用超低分辨三维 X 射线断层扫描数据的子体素纤维取向分布纳入数值模型中,为表征这些材料提供了一种有效的方法。
Sub-voxel based finite element modelling of fibre-reinforced composites
For fibre-reinforced composites, most of their mechanical properties is tied to the fibre scale. Thus, imaging-based characterisation demands resolving fibres to characterise these materials accurately. However, high resolutions limit the field of view and lead to lengthy acquisition times. Emerging non-destructive imaging technologies and algorithms now accurately provide fibre orientations without detecting individual fibres. Studies show that voxel sizes up to fifteen times the fibre diameter are feasible, still allowing accurate tensile modulus predictions. Our presented software incorporates sub-voxel fibre orientation distributions using ultra-low-resolution three-dimensional X-ray tomography data in a numerical model, providing an effective method for characterising these materials.