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1.江苏理工学院 材料工程学院,常州 213001
2.中国机械总院集团江苏分院有限公司,常州 213001
3.扬州平航航空动力技术有限公司,扬州 225200
赵金峰,男,2000年生,河南平顶山人,硕士研究生;主要研究方向为材料绿色成型工艺;E-mail:374148177@qq.com。
朱福先朱福先(通信作者),男,1979年生,江苏东台人,博士,副教授;主要研究方向为复合材料力学;E-mail:jxzfx@jsut.edu.cn。
收稿日期:2023-11-21,
修回日期:2023-12-30,
纸质出版日期:2025-06-15
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赵金峰,朱福先,庄百亮,等. 高体积分数比金属颗粒增强树脂基复合材料弹性模量预测[J]. 机械强度,2025,47(6):132-140.
ZHAO Jinfeng,ZHU Fuxian,ZHUANG Bailiang,et al. Elastic modulus prediction of high volume fraction metal particle reinforced resin matrix composite[J]. Journal of Mechanical Strength,2025,47(6):132-140.
赵金峰,朱福先,庄百亮,等. 高体积分数比金属颗粒增强树脂基复合材料弹性模量预测[J]. 机械强度,2025,47(6):132-140. DOI: 10.16579/j.issn.1001.9669.2025.06.016.
ZHAO Jinfeng,ZHU Fuxian,ZHUANG Bailiang,et al. Elastic modulus prediction of high volume fraction metal particle reinforced resin matrix composite[J]. Journal of Mechanical Strength,2025,47(6):132-140. DOI: 10.16579/j.issn.1001.9669.2025.06.016.
为研究高金属颗粒增强树脂基复合材料的力学性能,基于细观力学理论和细观有限元法预测了该复合材料的弹性模量。首先,制备了复合材料的标准试样,通过单轴拉伸试验测试了其宏观弹性模量,并观测了试样的微观特性。其次,采用基于细观力学理论的Voigt、Reuss、Mori-Tanaka和广义均值法预测了复合材料的弹性模量。然后,根据试样微观的粒径统计结果,采用高斯分布规律确定了金属颗粒粒径的级配及其数量,采用Python语言编写了颗粒随机投放程序,基于Abaqus平台构建了由颗粒、树脂基体以及界面组成的二维代表性体积单元(Representative Volume Element
RVE)有限元模型。最后,通过理论计算和有限元数值模拟预测了高金属颗粒增强树脂基复合材料的弹性模量。分析结果表明,广义均值模型和有限元模型预测的弹性模量与试验测试结果误差较小,复合材料弹性模量随金属颗粒的增大而增大。
In order to study the mechanical properties of high volume fraction ratio metal particle reinforced resin matrix composites
the elastic modulus of the composites was predicted based on the micromechanics theory and the meso-finite element method. Firstly
standard specimens of the composites were prepared
and their macroscopic elastic moduli were tested by uniaxial tensile experiments
and the microscopic properties were observed. Secondly
the elastic modulus of the composites was predicted by using Voigt
Reuss
Mori-Tanaka and Generalized means based on the micromechanics theory. Then
based on the microscopic particle size statistics of the specimens
the gradation of the metal particle size and its quantity were determined by using the Gaussian distribution law
and the random particle placement program was written by Python language to construct a two-dimensional representative volume element (RVE) finite element model consisting of the particles
the resin matrix
and the interface. Finally
the elastic modulus of resin matrix composites reinforced with high volume fraction metal particles was predicted by theoretical and finite element simulations. The analysis results show that the generalized means and finite element models predict the elastic modulus with less error from the experimental test results
and the elastic modulus of the composites increases with the increase of the volume fraction of the metal particles.
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