Analytische Chemie
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- Crack Detection (2) (entfernen)
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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.
This poster provides an overview of ultrasonic investigations of an engineered test barrier at ERAM Morsleben, which were completed as part of contractual work with the Bundesgesellschaft für Endlagerung mbH (BGE). This includes both experiments with the Large Aperture Ultrasound System (LAUS) and the ultrasonic borehole array. Also included in the poster is a description of the planned BAM thematic project “SealWasteSafe”. In particular, the proposed geopolymer materials are described and future research requirements are detailed.