Abstract

Closed-cell bead foams with their hierarchical geometrical structure are a challenge for statistical reconstruction and finite element modelling. For the purpose of providing the fundamental micro- and meso-structural descriptors - wall thickness, cell as well as bead volume and sphericity - of expanded polypropylene bead foams of different density, 3D-images from X-ray computed tomography are analyzed. A detailed description of development and application of an image analysis methodology for the determination of feature distributions from CT-scans of different level of detail is provided. The methods are based on off-the-shelf algorithms provided by the open-source package distribution FIJI. It should be highlighted, that beside essential methods such as thresholding, euclidean distance and watershed transformation here the Trainable WEKA segmentation is applied for separating material phases in the images. Although the methods elaborated are generally very case sensitive, the reader benefits from the validation strategies applied, so that development of individual methods into the direction of reliability, repeatability and automation is supported.

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