- 2008 (2) (entfernen)
- Anisotropy analysis of pressed point processes (2008)
- This paper introduces methods for the detection of anisotropies which are caused by compression of regular three-dimensional point patterns. Isotropy tests based on directional summary statistics and estimators for the compression factor are developed. These allow not only for the detection of anisotropies but also for the estimation of their strength. Using simulated data the power of the methods and the dependence of the power on the intensity, the degree of regularity, and the compression strength are studied. The motivation of this paper is the investigation of anisotropies in the structure of polar ice. Therefore, our methods are applied to the point patterns of centres of air pores extracted from tomographic images of ice cores. This way the presence of anisotropies in the ice caused by the compression of the ice sheet as well as an increase of their strength with increasing depth are shown.
- Microstructural characterisation of open foams using 3d images (2008)
- Open cell foams are a promising and versatile class of porous materials. Open metal foams serve as crash absorbers and catalysts, metal and ceramic foams are used for filtering, and open polymer foams are hidden in every-day-life items like mattresses or chairs. Due to their high porosity, classical 2d quantitative analysis can give only very limited information about the microstructure of open foams. On the other hand, micro computed tomography (μCT) yields high quality 3d images of open foams. Thus 3d imaging is the method of choice for open cell foams. In this report we summarise a variety of methods for the analysis of the resulting volume images of open foam structures developed or refined and applied at the Fraunhofer ITWM over a course of nearly ten years: The model based determination of mean characteristics like the mean cell volume or the mean strut thickness demanding only a simple binarisation as well as the image analytic cell reconstruction yielding empirical distributions of cell characteristics.