平纹编织碳纤维增强碳化硅复合材料孔隙分级及性能预测

Pore classification and performance prediction of 2D carbon fiber reinforced silicon carbide composites

  • 摘要: 为了更精确快速的进行孔隙建模,需要寻找大小孔隙的临界体积。本研究采用micro-CT技术与三维重建方法,对2D Cf /SiC中的微结构进行了提取与重建。在孔隙建模方面,提出了一种避免孔隙重叠和纤维束阻隔的方法,并通过孔隙体积及其长宽比两种划分标准,建立了相应的单胞模型。通过有限元分析技术计算模量,界定了大孔隙与小孔隙的体积临界值。根据体积的划分,孔隙体积小于0.04 mm3时对Cf/SiC单胞的力学性能较小;依据长宽比的划分,发现当孔隙体积小于0.021 mm3时,其形状对材料性能的影响可以忽略不计。以0.021 mm3作为临界体积,大于临界体积的精确建模,小于临界体积根据统计数据随机建模,计算得到的拉伸试样的宏观模量为110 GPa,与实验得到的113 GPa误差2.7%,证明了此划分方法可以在保证精度的同时提高建模效率。在孔隙分级的基础上探讨了体积元选取和纤维束波纹比对模量的影响,发现单胞模型在保持计算精度的同时效率更高,而波纹比增大导致复合材料模量减小。

     

    Abstract: To facilitate more precise and rapid pore modeling, it is crucial to determine the critical volume that delineates between large and small pores. In this research, micro-CT technology and three-dimensional reconstruction technique were employed to extract and reconstruct the microstructure within 2D Cf/SiC composites. In terms of pore modeling, a novel approach was introduced to avoid pore overlap and fiber bundle obstruction, and established corresponding unit cell models using two classification criteria: pore volume and aspect ratio (length-to-width ratio). By utilizing finite element analysis, the volume threshold for large and small pores was defined. According to the volume classification, pores with volumes less than 0.04 mm3 exert a minimal influence on the mechanical properties of Cf/SiC unit cells. Furthermore, based on the aspect ratio classification, it is founded that the shape of pores with volumes less than 0.021 mm3 has a negligible impact on material properties. Taking 0.021 mm3 as the critical volume, larger than the critical volume is modelled accurately, and smaller than the critical volume is modelled randomly based on the statistical data, the macroscopic modulus of the tensile specimen is calculated to be 110 GPa, with an error of 2.7% from the experimentally obtained 113 GPa, which proves that this partitioning method can increase the efficiency of the modelling while maintaining the accuracy. The effects of volume element selection and fibre bundle corrugation ratio on the modulus are explored on the basis of pore classification, and it is found that the single-cell model is more efficient while maintaining the computational accuracy, whereas an increase in the corrugation ratio leads to a decrease in the modulus of the composite.

     

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