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In this work, which is part of a larger research program, a framework called “virtual data fusion“ was developed to provide an automated and consistent crack detection method that allows for the cross-comparison of results from large quantities of X-ray Computed Tomography (CT) data. A partial implementation of this method in a custom program was developed for use in research focused on crack quantification in Alkali-Silica Reaction (ASR)-sensitive concrete aggregates. During the CT image processing, a series of image analyses tailored for detecting specific, individual crack-like characteristics were completed. The results of these analyses were then “fused” in order to identify crack-like objects within the images with much higher accuracy than that yielded by any individual image analysis procedure. The results of this strategy demonstrated the success of the program in effectively identifying crack-like structures and quantifying characteristics, such as surface area and volume. The results demonstrated that the source of aggregate has a very significant impact on the amount of internal cracking, even when the mineralogical characteristics remain very similar. River gravels, for instance, were found to contain significantly higher levels of internal cracking than quarried stone aggregates of the same mineralogical type.
Intensified Alkali-Silica Reaction (ASR) damage has occurred on German roadways in recent years, leading to requirements for compulsory pre-construction investigation of aggregate alkali sensitivity using concrete tests with external alkali supply. However, since these tests are time-consuming and cost-intensive, there is interest in replacing them with a solubility test on pure aggregate in 0.1 M KOH solution at 80°C with a defined NaCl content (1wt.-%). In this context, the influence of aggregate pore structure on SiO2 and Al2O3 solubility was investigated in this project. This paper compares the results of porosity studies with X-ray Computed Tomography (3D-CT) and the Brunauer-Emmett-Teller (BET) method on individual quarried and river gravel granules of both rhyolite and greywacke. For visualization and quantification of both externally accessible and fully enclosed surfaces of granules using X-ray 3D-CT, special software tools were developed. The results demonstrated that the river gravel granules had significantly larger externally accessible surfaces than the quarried granules. BET measurements on individual stones showed, as expected, that measured surfaces were about three orders of magnitude larger than those from the X-ray 3D-CT analyses due to the higher spatial resolution of BET. There was no apparent correlation between the X-ray 3D-CT and BET surface areas. Mercury porosimetry measurements indicate that this may be due to the presence of significant porosity below the spatial resolution of the X-ray 3D-CT. A comparison of SiO2 and Al2O3 solubility measurements with the X-ray 3D-CT and BET surface area data resulted only in weak, inconclusive correlations, indicating the need for further experimental investigation.
Durch den großflächigen Einsatz der Computertomographie (CT) in unterschiedlichen Industriebereichen steigen auch die Anforderungen an die quantitative Bildanalyse. Subjektive Bildwahrnehmung muss durch objektive Algorithmen ersetzt werden. In diesem Artikel stellt die Bundesanstalt für Materialforschung und -prüfung (BAM), die seit den 1980er Jahren an der Entwicklung der industriellen CT beteiligt ist, anhand ausgewählter Beispiele den aktuellen Stand ihrer Analysemethoden an verschiedenen Anwendungsbeispielen der CT vor.