【机器学习】复合材料力学SCI最新文章案例复现

今日更新：Composite Structures 1 篇，Composites Science and Technology 1 篇Composite StructuresMachine learning-accelerated inverse design of programmable bi-functional metamaterialsBeicheng Lin, Fucong Lu, Chuanbiao Zhang, Tinghui Wei, Weijia Li, Yilin Zhudoi:10.1016/j.compstruct.2024.118445机器学习加速可编程双功能超材料的逆向设计Bi-functional metamaterials with programmable coefficients of thermal expansion (CTEs) and Poisson’s ratios (PRs) have garnered significant attention among researchers due to the ability to manifest desired deformations under thermal and mechanical loads. Nevertheless, a current challenge lies in efficiently achieving the inverse design of these metamaterials to meet diverse application requirements. This paper presents a machine learning (ML) model that can establish a logical mapping relationship between geometric/material parameters and mechanical properties, and it is applied to the inverse design of bi-functional metamaterials with desired CTEs and PRs. Furthermore, the inverse design capability of the ML model was validated by the finite element analysis and experimental test. The results demonstrate that the geometric models obtained from the inverse prediction can effectively exhibit the desired deformation behavior under thermal and mechanical loads. And the ML model proves to be a valuable tool, offering effective guidance for the design of bi-functional metamaterials with specific CTEs and PRs.具有可编程热膨胀系数(CTEs)和泊松比(pr)的双功能超材料由于能够在热载荷和机械载荷下表现出所需的变形而引起了研究人员的极大关注。然而，当前的挑战在于如何有效地实现这些超材料的逆设计，以满足不同的应用需求。本文提出了一种机器学习(ML)模型，该模型可以建立几何/材料参数与力学性能之间的逻辑映射关系，并将其应用于具有期望cte和pr的双功能超材料的反设计。通过有限元分析和实验验证了该模型的反设计能力。结果表明，由逆预测得到的几何模型能有效地表现出在热载荷和机械载荷下所需的变形行为。ML模型为设计具有特定cte和pr的双功能超材料提供了有效的指导。Composites Science and TechnologyNitsche’s Method Enhanced Isogeometric Homogenization of Unidirectional Composites with Cylindrically Orthotropic Carbon/Graphite FibersXiaoxiao Du, Qiang Chen, George Chatzigeorgiou, Fodil Meraghni, Gang Zhao, Xuefeng Chendoi:10.1016/j.compscitech.2024.110787 Nitsche方法增强了圆柱正交异性碳/石墨纤维单向复合材料的等几何均匀化An isogeometric homogenization (IGH) technique is constructed for the homogenization and localization of unidirectional composites with radially or circumferentially orthotropic carbon/graphite fibers. The proposed theory employs multiple non-conforming Non-Uniform Rational B-Splines (NURBS) patches to depict repeating unit cells (RUCs) representative of composite microstructures. Displacements are formulated using a two-scale expansion that integrates macroscopic and microscopic contributions, with the latter addressed through the isogeometric analysis technique. Nitsche’s method is utilized to apply the interfacial traction and displacement continuity and periodicity conditions. The capability and accuracy of the IGH theory were validated upon comparison with the elasticity solutions that take into account explicitly fiber morphologies, along with classical micromechanics solutions based on equivalent fiber moduli. A comparative analysis with conventional finite-element techniques showcases the developed theory’s ability to accurately replicate the singular stress field at the fiber center and to capture smooth stress distributions where significant stress gradients are encountered.提出了一种等几何均质(IGH)技术，用于径向或周向正交异性碳/石墨纤维单向复合材料的均质和局部化。提出的理论采用多个不一致的非均匀有理b样条(NURBS)斑块来描述复合微观结构的重复单元(RUCs)代表。位移采用双尺度扩展，整合了宏观和微观贡献，后者通过等几何分析技术解决。采用Nitsche的方法来应用界面牵引和位移的连续性和周期性条件。通过与明确考虑纤维形态的弹性解以及基于等效纤维模量的经典微观力学解进行比较，验证了IGH理论的能力和准确性。与传统有限元技术的对比分析表明，该理论能够准确地复 制光纤中心的单一应力场，并在遇到显著应力梯度时捕获平滑的应力分布。来源：复合材料力学仿真Composites FEM