The effect of manufacturing conditions on discontinuity population and fatigue fracture behavior in carbon/epoxy composites

Porosity Effects on Interlaminar Fracture Behavior in Carbon Fiber-Reinforced Polymer Composites

“…The increase in relative specific surface from high to moderate vacuum level is about the same for both orientations, indicating a random orientation of the additional defects. In contrast, the increase from moderate to poor vacuum level was much higher in horizontal orientation, indicating a preferred orientation of the further additional defects parallel to the fiber orientation [8].…”

“…× 100 µm pixel size. The laminographic scan was conducted and then a sequence of images was acquired and after the acquisition, this sequence of 2-D data set of images was reconstructed using a filtered back projection algorithm in order to create a 3-D data set containing depth information as Figure 9 reveals [8]. Figure 9 shows the resulting data set illustrated in three different planes.…”

“…This distortion has to be considered when quantifying indications for defects or zones with enhanced porosity. To quantify defects in the resulting data set, a histogram was created to characterize the area fraction of reduced density that might be related to porosity in each image and then the porosity volume fraction as the average of the porosity area fraction in all the layers of a specific sample following the same methodology used in serial sectioning [8].…”

“…The samples were scanned in a grid with step widths between Figure 9. Resulting 3D data set of laminographic scans [8].…”

“…From the acquired data, a topographic map of the relative specific surface was created and the average value determined. Figure 10 shows such a topographic map of three samples in vertical orientation: one sample of each vacuum level [8]. Figure 10 shows that poor vacuum samples have the highest amount of inner surfaces and the high vacuum samples have the lowest.…”