Characterization of Pultruded Glass-Fiber Reinforced Polymers with Two-Step Homogenization

Abstract

Abstract The aim of this work is to determine effective elastic properties of pultruded Glass Fiber Reinforced Polymer using micro-CT in conjunction with a two-step numerical homogenization technique. The two-step homogenization involves the segmentation of the material’s layers, which was made here by means of a machine learning approach. The segmentation was validated through the comparison between the phase’s volume fractions of samples obtained from the segmented images and laboratory tests. Further, a standard accuracy analysis in a 10-fold cross validation was performed. The samples’ effective axial Young’s modulus obtained by our numerical homogenization were compared to results obtained from experimental tests. For both the experimental tests and the image-based numerical analysis we considered samples extracted from the same profile. The two-step methodology allowed the homogenization of large volumes of the composite corresponding to the whole thickness of the profile, imaged with a high resolution. In addition to the axial effective Young’s modulus, our methodology was also able to successfully provide all the other elastic properties along the three orthogonal directions, even the ones that are arduous to be obtained in laboratory setups.

Keywords

• Glass Fiber Reinforced Polymer
• Numerical Homogenization
• Non-destructive testing
• Image Segmentation
• Finite Element Method
• Micro-CT