论文标题
使用贝叶斯优化的非惯性复合材料设计的底漆设计
Ply-drop design of non-conventional composites using Bayesian optimization
论文作者
论文摘要
自动化纤维放置(AFP)技术具有出色的能力,可以有效地生产具有复杂表面的大型碳纤维增强复合结构。法新社具有广泛的拖放角度,用户可以设计上篮角度,以便可以定制结构的性能。然而,尽管设计自由,但该行业通常采用0度,90度的分层和45度的ply-drop角度。在这里,我们证明了非惯性复合材料的ply滴度角度的优化。具体来说,我们使用经典的层压板理论和贝叶斯优化来在刚度,泰河 - 沃失败标准和制造时间方面实现更好的上篮角度。我们的方法在机械性能和生产效率方面使用非常规角度设计了使用非常规角度设计碳纤维复合结构的有效性。我们的方法有可能用于更复杂的场景,例如弯曲表面的产生和有限元分析的利用。
Automated Fiber Placement (AFP) technology provides a great ability to efficiently produce large carbon fiber reinforced composite structures with complex surfaces. AFP has a wide range of tow placement angles, and the users can design layup angles so that they can tailor the performance of the structure. However, despite the design freedom, the industry generally adopts a layering of 0 deg, 90 deg, and plus-minus 45 deg ply-drop angles. Here, we demonstrate the optimization of ply-drop angles of non-conventional composites. Specifically, we use classical laminate theory and Bayesian optimization to achieve better layup angles in terms of stiffness, Tsai-Wu failure criteria, and manufacturing time. Our approach shows its effectiveness in designing carbon fiber composite structures using unconventional angles in terms of both mechanical properties and production efficiency. Our method has the potential to be used for more complex scenarios, such as the production of curved surfaces and the utilization of finite element analysis.