Evaluation and Visualisation of Shape Factors in Dependence of the Void Content within CFRP by Means of X-ray Computed Tomography
B. Plank, G. Mayr, A. Reh, D. Kiefel, R. Stössel, J. Kastner - Evaluation and Visualisation of Shape Factors in Dependence of the Void Content within CFRP by Means of X-ray Computed Tomography - Proceedings of 11th European Conference on Non-Destructive Testing (ECNDT 2014), Prague, Tschechische Republik, 2014, pp. 9
For the material properties of carbon fibre reinforced polymers (CFRP), not only the porosity values (void content) are important, but also the shape and the distribution of voids. The state-of-the-art non-destructive testing (NDT) method for porosity detection in CFRP is ultrasonic testing (UT). Several publications proposed that the shapes of the voids have a strong influence on attenuation of an ultrasonic signal. In addition to UT, active thermography (IR) is a promising NDT method with potential for quantitative porosity determination and defect detection in future. But also with IR, the shapes of the voids have an influence on quantitative results.
In this study, X-ray computed tomography (XCT) was used to investigate CFRP test specimens made from 5, 10 and 20 plies of PREPREG in a plain-weave style. Due to different autoclave cycles, specimens between 0 vol. % and ~ 18 vol. % of porosity were manufactured. With a chosen resolution of ~ (10 µm)³ voxel size, quantitative values of porosity can be gained. In addition to porosity, XCT yield data on size, shape, orientation, and location of each void. Calculating the shape factors show that the mean shape of voids within a specimen changes with the degree of porosity. Below a certain porosity, voids are small and have more or less a circular cross-section. Above, the shape changes to a more elliptical (complex) shape. This work also shows that the thickness of the CFRP specimens correlates linearly to the porosity. Especially for specimens made of 10 and 20 plies, the shown diagrams could be used for a raw and very fast estimation of the void content.
Moreover, with advanced visualisation methods it is possible to visualise individual void properties in 3D. Using parallel coordinates for a classification of voids with a certain geometry and shape, e.g. macro-voids and needle-like micro-voids can be visualised. With further visualisation methods all voids within a specimen or a region-of-interest are clustered into a mean object (MObject). A MObject shows the visual change of the mean shape of voids in relation to the degree of porosity. The individual MObjects of each specimen can be easily compared to each other.
Furthermore XCT simulation results show no significant dependence on evaluated degree of porosity for parameter variations using a thresholding method (FHW) developed by University of Applied Sciences Upper Austria. With the chosen input geometries there is no strong effect of void sizes and void shapes on quantitative porosity evaluation.