Prediction method of compressive strength after impact for fiber reinforced plastic composite based on the fractal dimension of impact damage

doi:10.19936/j.cnki.2096-8000.20220428.031

Abstract

Abstract: The bearing capacity of fiber reinforced plastic (FRP) composite is very sensitive to low-speed impact damage, so the prediction model of compression after impact (CAI) for FRP composite is vital to its engineering application. Therefore, the residual compressive strength tests of three different kinds of carbon fiber reinforced plastic (CFRP)/5284RTM/U3160 laminates under BVID state were carried out in this paper. The C-scan was used to obtain the impact damage morphologies of different CFRP laminates before compression test, and the impact damage morphologies were studied by the fractal dimension. The results show that the larger the fractal dimension of impact damage morphology, the lower the compression after impact. Based on this discovery, a prediction method of compressive strength after low-speed impact for fiber reinforced plastic composite based on the fractal dimension of impact damage was proposed. In this method, the impact damage morphology was equivalent to the basic fractal geometry (Sierpinski carpet), the non-bearing area of CFRP laminate could be obtained by the fractal theory. Then the residual compressive strength can be calculated by the normalized non-bearing area. The impact energy was not used as input parameter in this method, and the prediction results of the method were in good agreement with the experimental results. Therefore, the CAI prediction method proposed in this paper is convenient for engineering application.

Key words: fiber reinforced plastic composite, low-speed impact, residual compressive strength, fractal dimension

CLC Number:

TB332

JIANG Wen, FAN Hongxing, YAO Weixing, CHEN Fang, MA Mingze. Prediction method of compressive strength after impact for fiber reinforced plastic composite based on the fractal dimension of impact damage[J]. COMPOSITES SCIENCE AND ENGINEERING, 2023, 0(3): 11-17.

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