·Home ·Table of Contents ·Materials Characterization and testing

3D Investigations of Metallic Foams by mikrotomography (µCT) E. Jasiūnienė, B. Illerhaus, J. Goebbels BAM, Berlin, Germany Contact

Introduction

Metallic foams have a very complex inner structure. The design process of such foams needs to be controlled as the parameters of production have to be set adequately for each part. Metallic foams are expected to be used with or without outer coating sheets in different markets [1]:
• in big quantities for mass market;
• to be foamed in form (of specific product) as bone-like structures;
• as metal structures which can be designed light weight but specifically to the needs of engineering (foam structures of varying, but defined size of bubbles).

Also the definition of underlying principles of foaming and of material strength, the generation of simple models, or the calculation of complex structures, needs the geometrical description of foams. No other method beside 3D-CT is able to give a complete test of the inner integrity of these objects.

3D-µCT

BAM has developed several 3D tomographs for industrial purposes [2, 3]. A variety of objects from 200 mm diameter (with minimum resolution of 0.1 mm) down to small parts with 1 mm diameter (with minimum resolution of 1.5 µm) can be investigated using 3D-CT (Fig. 1). To expand the measuring range to higher attenuating objects, at the end of the year a 320 kV microfocus X-ray tube will be installed.

Fig 1: 13D-CT for objects with diameter of up to 200 mm left and up to 20 mm right

The CT results shown here were obtained using a X-ray microfocus tube at 120 kV and 200 mA. A 0.5 mm copper filter was inserted. The voxel side length, used for the density calculations, was 250 µm, for the porosity calculations - 70 µm respectively. For the reconstruction of the 3D image of the investigated object from the collected data the Feldkamp algorithm [4] was used.

The investigation of metallic foams is very specific. Here on the one hand the highest possible resolution is required for the investigation of the formation of walls, their thickness and integrity. Especially the investigations on strength tested probes need high resolution to visualise the beginning of deformation within the probe in comparison to the undeformed probe. On the other hand a general characterisation of the metallic foam probe is needed: is there a conjunction between mean density and stiffness?

3D-µCT results

As an example of the structure of such materials in fig. 2 a vertical slice through a cube with 20 mm side length is shown. Here the voxel side length was 40 µm. The probe was used in a strength test series with subsequent pressing and CT-testing. Here the status of 5% decrease in length is shown. The buckling of walls is visible.

a	b
Fig 2: A vertical slice through the cube with 20 mm side length: a) before the compression;      b)after 5% compression

Density evaluation

The requirements for foams are most often described using the parameter of mean density in comparison to the bulk material. Inside the probe this mean value can be reached by different means and may be locally dependent. A foam with small bubbles and thin walls can have the same overall density as a foam with big bubbles and with only few walls. Furthermore some big bubbles included in the probe cannot be detected using simple radiography due to the overall structure of the foam.

For the density evaluation the probe has to be measured with the resolution which is high enough to visualise the walls. If the resolution is lower than the wall thickness, the calculated mean density will be lower (due to exponential attenuation) than the true one. But the comparison between similar probes will still be valid.

The tool to describe the homogeneity of probe on the basis of an idea by Kottar et al. [5] was developed. First the region has to be defined within which all points should be averaged. The averaging region is moved across the whole probe in 3D. The resulting image has the same size but allows to inspect density variations within the foam. By now the information is still in 3D, this means, all information is not visible at one glance. Therefore a software tool, which x-rays the data using the 'mean' operation, was used. The result is a two dimensional representation of the density distribution. Fig. 3 shows two cylindrical foam probes. The probe in fig.3, a) has an agglomeration of material at the top, whereas the density distribution in the probe in fig.3, b) is more homogenous.

a	b
Fig 3: Two dimensional representation of the density distribution of cylindrical foam probes: a) image had max grey value of 180, which was scaled to 255,      b)image had max grey value of 100, which was scaled to 255

If there would be a bigger bubble inside, this would not be clearly visible by now. So all areas with a too low density over a certain region where highlighted. At this point the size of the averaging region becomes important. It should be set to the same size as the maximum pore which is still tolerable. Highlighting of these regions before the X-ray process will show up both by now: the low and high density areas. In fig. 3 these low density areas (the big bubbles) are visible as a kind of fleck on the image. Due to the use of 'mean' filter the image is independent of the form of the object.

Pore size distribution

The discussion on the underlying features of metallic foams is still ongoing. To supply the theoretic calculations with the results to compare with, the objects which will be investigated by strength test have to be described in different ways. Beside the localised mean density, as discussed above, the pore size and pore size distribution are relevant. Starting from a high resolved 3D-CT image both features can be calculated.

To test the results of our measurements we used a special kind of porous material [6]. This porous material consisted of metallic spheres with a known diameter, which where sintered together under slight pressure.

In a first step all volume outside the probe and every volume which is inside the probe, but outside the spheres, and therefore connected to the outside, was marked. For that a search algorithm in 3D was used, which expands the marked area as long as voxels in a given range of grey values, adjacent to a marked voxel, are found. (For results see [7]).

As long as the spatial resolution is good enough, the border of a material is defined as half the grey value of bulk material. If some walls get thinner than the spatial resolution, their apparent grey level may be lowered. In these cases the true value can be regained by first setting a lower level for the binarisation of the image and then using a 3D erode algorithm. The level of eroding is determined by the point spread function of the source detector system.

In the next step a search algorithm is looking for non-marked voxels in a specified range, which should be smaller than the first to avoid picking up voxel outside the spheres. From this starting point it expands its field of search marking voxel as 'inside' as long as new voxels in the grey level range adjacent to the marked one are found. Each bubble is filled with a different colour, so it is possible to see which bubbles are interconnected one to another. The number of voxels in each bubble is counted and the coordinates are summed. When one bubble is filled, the radius of an ideal sphere with same volume and the centre of gravity is calculated. These data can be used for theoretical calculations. In fig. 4, a) an example of the program output is shown, and fig. 4, b) shows the pore size distribution.

a	b
Fig 4: a) an example of the program output; b) the pore size distribution

Literature

1. Metal Foams and Porous Metal Structures. Editors: J. Banhart, M. F. Ashby, N. A. Fleck. Verl. MIT Publ., (1999), ISBN 3-9805748-7-3
2. H. Riesemeier, J. Goebbels, B. Illerhaus, Y. Onel, P. Reimers, 3-D Mikrocomputertomograph für die Werkstoffentwicklung und Bauteilprüfung DGZfP Berichtsband 37 (1993) S. 280-287
3. B. Illerhaus, J. Goebbels, P. Reimers, H. Riesemeier, The principle of computerized tomography and its application in the reconstruction of hidden surfaces in objects of art 4th Int. Conf. NDT of Works of Art DGZFP, Berichtsband 45, 1 (1994) pp. 41-49
4. L. A. Feldkamp, L. C. Davis, J. W. Kress, Practical Cone-Beam Algorithm, J. Opt. Soc. Amer. A1, (1984), pp. 612-619
5. H. P. Degischer, A. Kottar, On the Non-Destructive Testing of Metal Foams, Metal Foams and Porous Metal Structures. Editors: J. Banhart, M. F. Ashby, N. A. Fleck. Verl. MIT Publ., (1999), ISBN 3-9805748-7-3 pp. 213-220
6. O. Andersen, U. Waag, L.Schneider, G. Stephani, B. Kieback, Novel metallic hollow sphere structures: processing and properties, Metal Foams and Porous Metal Structures. Editors: J. Banhart, M. F. Ashby, N. A. Fleck. Verl. MIT Publ., (1999), ISBN 3-9805748-7-3 pp. 183-188
7. B. Illerhaus, J. L. Thompson, Calculating CT data from matched geometries DGZfP Berichtsband BB67 (CD), Computertomographie und Bildverarbeitung, Berlin, 1999

© AIPnD , created by NDT.net

|Home|    |Top|