Statistical analysis of the local strut thickness of open cell foams

Abstract

Open cell foams are formed by an interconnected network of struts whose thickness varies locally. These variations are known to have an impact on the elastic and thermal properties of the foam. In this paper we quantify the local strut thickness by means of micro computed tomography (μ CT) imaging. We develop a fully automatic algorithm to extract the foam's skeleton from a binary image and its topological decomposition into vertices and struts. This allows to estimate the thickness of individual strut segments by the Euclidean distance transform, where an appropriate correction for struts with nonspherical cross-sectional shape is applied. Conflating these estimates based on the strut lengths results in a strut thickness profile for the entire foam. Based on this profile we give a statistical justification that a strut thickness model should depend on the strut length. Furthermore, the investigation of polynomial models for the strut thickness profile by means of regression analysis leads to a new three-parameter strut thickness model.