三维针刺复合材料精细化结构重构方法及力学性能预测

Reconstruction method of microstructure and mechanical properties simulation of three-dimensional needling composites

摘要

采用原位拉伸X射线micro-CT技术和图像分析及精细化结构重构方法，定量化描述三维针刺复合材料纤维以及裂纹精细化结构，建立针刺纤维束等纤维结构的重构模型，提出三维针刺复合材料微细宏观有限元模型建模方法，并应用于三维针刺复合材料拉伸力学性能仿真分析。结果表明：拉伸载荷下三维针刺复合材料断裂位置出现纤维整体断裂，编织层承担较多的拉伸载荷，断裂纤维数量高于其他铺层纤维。通过ABAQUS用户子程序UMAT的二次开发和工艺参数化建模算法，在周期性单胞有限元分析中调用典型代表性单元模型进行细观渐进损伤分析，实现宏细观尺度之间工艺参数传递，并且与实验进行对比，预测的拉伸模量数值大于实验结果，误差为10.1%。本研究方法和结果可以为材料针刺工艺参数化建模和工艺设计及力学分析研究提供依据。

Abstract

The in-situ tensile X-ray micro-CT technology，image analysis and fine structure reconstruction method are used to complete the quantitative description of complex geometric structures such as fiber and crack of three-dimensional needling composites. The reconstruction model of fibre structures such as needling fiber bundle is established. A multi-scale finite element modeling method for three-dimensional needling composites is proposed and applied to the simulation and analysis of tensile mechanical properties. The results show that the three-dimensional needling composites fracture location under tensile loading shows overall fibre fracture，and woven layer bears more tensile load and has a higher number of broken fibers than other layers. The user subroutine UMAT in ABAQUS software and the method of process parametric modelling，representative volume element is used in unit cell analysis to carry out meso-progressive damage analysis，the process parameter transfer between macro and micro scales is achieved and the predicted value of the tensile modulus is greater than the experimental result，with an error of 9.2%. The research method and results of this paper can provide the basis for the parametric modelling of material needling process and the research of process design and mechanical analysis.

关键词

三维针刺复合材料 / 精细化结构重构方法 / 原位X射线micro-CT技术 / 弹性模量 / 拉伸强度

Key words

three-dimensional needling composite / reconstruction methods for refined structure / X-ray in-situ micro-CT / elastic modulus / tensile strength

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基金资助

国家自然科学基金(12272321)

河南省高等学校重点科研项目(26A590006)

河南省高等学校重点科研项目(23A590004)