陈军

个人信息Personal Information

副教授

硕士生导师

性别:男

出生日期:1965-06-03

毕业院校:大连理工大学

学位:博士

所在单位:材料科学与工程学院

学科:材料无损检测与评价

办公地点:大连理工大学材料馆230房间

联系方式:0411-84707117

电子邮箱:chenjun@dlut.edu.cn

扫描关注

论文成果

当前位置: 中文主页 >> 科学研究 >> 论文成果

A novel random void model and its application in predicting void content of composites based on ultrasonic attenuation coefficient

点击次数:

论文类型:期刊论文

发表时间:2011-06-01

发表刊物:APPLIED PHYSICS A-MATERIALS SCIENCE & PROCESSING

收录刊物:Scopus、SCIE、EI

卷号:103

期号:4

页面范围:1153-1157

ISSN号:0947-8396

摘要:A novel two-dimensional random void model (RVM) based on random medium theory and a statistical method is proposed to describe random voids in composite materials. The spatial autocorrelation function and statistical parameters are used to describe the large-scale heterogeneity from the composite matrix and the small-scale heterogeneities of elastic fluctuations from random voids, the values of which are determined by statistical data from microscopic observations of void morphology. A RVM for CFRP (carbon fiber reinforced polymer) composite specimens with void content of 0.03-4.62% is presented. It is found that the geometric morphology of voids from the RVM presents good matches to the microscopic images. Calculations of ultrasonic attenuation coefficients from the RVM at 5 MHz are much closer to the experiments than those from the previous deterministic model. Furthermore, the RVM can also cover abnormal coefficients from unusually large voids, which unpredictably occur during the composite preparation and have a detrimental effect on the strength and mechanical properties of the components. The significant enhancements in description of void morphology and quantitative correlation between void content and ultrasonic attenuation coefficient make this method a good candidate for predicting void content of composite materials non-destructively.