Research Planning Grant: Conformability of Fiber Preform Architectures

这项研究的目的是确定纤维预制件的结构对其与某些零件形状(例如，角、曲线)的一致性的影响。纤维预制件的使用可以极大地开拓中到大批量复合材料市场，因为它具有生产成本效益高但结构合理的近净形状零件的潜力。然而，复杂的零件形状可能会导致纤维的排列不在最大载荷方向上。此外，纤维运动会导致纤维体积分数较低的区域，从而导致薄弱点。这两种变化往往发生在应力集中也是一个令人担忧的领域，导致故障低于预计的承载能力。该项目将研究几种测量预制件变形(例如，拉伸、剪切和弯曲行为)的方法，包括使用光学和图像分析技术、示踪纤维和模拟加工条件的各种载荷配置。预计这项初步工作将导致更详细的研究，从而量化定向、双轴和随机纤维垫的变形响应。通过了解不同纤维毡几何形状的变形行为，可以预测各种预制件结构对工艺条件的响应，从而优化以适应所需的零件形状。对纤维垫性能的详细了解对于复合材料在“大众市场”应用领域的广泛使用至关重要，尤其是在汽车行业。

The objective of this research is to determine the effect of the structure of a fiber preform on its conformability to certain part shapes -- e.g., corners, curves. The use of fiber preforms can significantly open up the medium to high volume composite markets due to its potential to produce cost-effective yet structurally sound, near net shape parts. However, complex part shapes can result in regions where the alignment of fibers is not in the direction of maximum loading. In addition, fiber movement can result in regions of low fiber volume fraction leading to weak spots. Both of these variations tend to occur in areas where stress concentrations are also a concern, resulting in failures below projected loading capacity. The project will investigate several methods of measuring preform deformation (e.g., tensile, shear, and bending behavior) -- including the use of optical and image analysis techniques, tracer fibers, and various load configurations simulating processing conditions. It is expected that this preliminary work will lead to a more detailed study resulting in the quantification of the deformation response of aligned, biaxial, and random fiber mats. By understanding the deformation behavior of different fiber mat geometries, the response of various preform architectures to processing conditions can be predicted and thus optimized to fit the desired part shape. A detailed understanding of the behavior of fiber mats is essential to the widespread use of composite materials in the "mass market" application areas, particularly in the automotive industry.