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

Abstract

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.