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- Concrete (3)
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- 3D computer tomography (CT) imaging (1)
- A. Laminates (1)
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Organisationseinheit der BAM
In civil engineering, the corrosion of steel reinforcements in structural elements of concrete bares a risk of stability-reduction, mainly caused by the exposure to chlorides. 3D computed tomography (CT) reveals the inner structure of concrete and allows one to investigate the corrosion with non-destructive testing methods. To carry out such investigations, specimens with a large artificial crack and an embedded steel rebar have been manufactured. 3D CT images of those specimens were acquired in the original state. Subsequently three cycles of electrochemical pre-damaging together with CT imaging were applied. These time series have been evaluated by means of image processing algorithms to segment and quantify the corrosion products. Visualization of the results supports the understanding of how corrosion propagates into cracks and pores. Furthermore, pitting of structural elements can be seen without dismantling. In this work, several image processing and visualization techniques are presented that have turned out to be particularly effective for the visualization and segmentation of corrosion products. Their combination to a workflow for corrosion analysis is the main contribution of this work.
Die Dauerhaftigkeit von Fahrbahndeckenbetonen wird maßgebend von ihrer Mikrostruktur bestimmt. Diese erfährt durch die äußeren Einwirkungen durch Klima und Verkehr über die Nutzungsdauer eine signifikante Veränderung. Im Kontext der in den letzten Jahren verstärkt auftretenden Schadensfälle infolge der Alkali-Kieselsäure-Reaktion (AKR) im deutschen Bundesautobahnnetz stellt sich die Frage, in welchem Maße die ermüdungsinduzierte Betondegradation den Stofftransport und damit die AKR-induzierte Rissbildung begünstigt. Dabei kommt der hochauflösenden räumlichen Quantifizierung der Rissbildung eine zentrale Bedeutung zu und bildet die Basis für die Modellierung der sich überlagernden Schädigungsprozesse.
Gegenstand dieses Beitrags ist die Darstellung der Leistungsfähigkeit der 3DComputertomographie (3D-CT) bei der quantitativen Rissanalyse in Betonen ohne und mit Ermüdungsbeanspruchung. Die Untersuchungen erfolgten dabei exemplarisch an Bohrkernen, die einem großformatigen Schwingbalken entnommen wurden. Zur Erreichung einer hinreichenden Ortsauflösung gelangte dabei die Region of Interest – Technik (ROI) zum Einsatz. Die Rissauswertung erfolgte mit einem gemeinsam vom ZIB und der BAM entwickelten Softwaretool für die automatisierte Risserkennung. So erlaubt dieses eine quantitative statistische Auswertung von Rissparametern, wie z.B. Risslänge, -breite und -orientierung. Die Notwendigkeit der automatisierten Rissauswertung beruht darauf, dass die Größe des CT-Datensatzes (mehrere GB) eine vollständige manuelle Segmentierung der Risse im 3D-Raum einen unverhältnismäßigen hohen Aufwand erfordert. Eine automatische Risserkennung liefert darüber hinaus noch weitere Daten, die eine nachträgliche Bearbeitung und Analyse der Risse erst möglich macht. Rissveränderungen über der Zeit können ebenfalls visualisiert und statistisch aufbereitet werden.
During the last decades, X-ray (micro-)computed tomography has gained increasing attention for the description of porous skeletal and shell structures of various organism groups. However, their quantitative analysis is often hampered by the difficulty to discriminate cavities and pores within the object from the surrounding region. Herein, we test the ambient occlusion (AO) algorithm and newly implemented optimisations for the segmentation of cavities (implemented in the software Amira). The segmentation accuracy is evaluated as a function of (i) changes in the ray length input variable, and (ii) the usage of AO (scalar) field and other AO-derived (scalar) fields. The results clearly indicate that the AO field itself outperforms all other AO-derived fields in terms of segmentation accuracy and robustness against variations in the ray length input variable. The newly implemented optimisations improved the AO field-based segmentation only slightly, while the segmentations based on the AOderived fields improved considerably.
Additionally, we evaluated the potential of the AO field and AO-derived fields for the separation and classification of cavities as well as skeletal structures by comparing them with commonly used distance-map-based segmentations. For this, we tested the zooid separation within a bryozoan colony, the stereom classification of an ophiuroid tooth, the separation of bioerosion traces within a marble block and the calice (central cavity)-pore separation within a dendrophyllid coral. The obtained results clearly indicate that the ideal input field depends on the three-dimensional morphology of the object of interest. The segmentations based on the AO-derived fields often provided cavity separations and skeleton classifications that were superior to or impossible to obtain with commonly used distance-map-based segmentations. The combined usage of various AO-derived fields by supervised or unsupervised segmentation algorithms might provide a promising target for future research to further improve the results for this kind of high-end data segmentation and classification. Furthermore, the application of the developed segmentation algorithm is not restricted to X-ray (micro-)computed tomographic data but may potentially be useful for the segmentation of 3D volume data from other sources.
Analyzing damages at concrete structures due to physical, chemical, and mechanical exposures need the application of innovative non-destructive testing methods that are able to trace spatial changes of microstructures. Here, the utility of three different crack detection methods for the analysis of computed tomograms of various cementitious building materials is evaluated. Due to the lack of reference samples and standardized image quality evaluation procedures, the results are compared with manually segmented reference data sets. A specific question is how automatic crack detection can be used for the quantitative characterization of damage processes, such as crack length and volume. The crack detection methods have been integrated into a scientific visualization system that allows displaying the tomography images as well as presenting the results.
The combination of tomographic, microstructural data with other experimental techniques and with modeling is paramount, if we want to extract the maximum amount of information on material and component properties. In particular, quantitative image analysis, statistical approaches, direct discretization of tomographic reconstructions represent concrete possibilities to extend the power of the tomographic 3D representation to insights into the material and component performance. This logic thread holds equally for industrial and academic research, and valorizes expensive experiments such as those carried out at synchrotron sources, which cannot be daily repeated. We shall show a few examples of possible use of X-ray tomographic data for quantitative assessment of damage evolution and microstructural properties, as well as for non-destructive testing. We will also show how X-ray refraction computed tomography (CT) can be highly complementary to classic absorption CT, being sensitive to internal interfaces.
In order to extend the lifetime of buildings and constructions at the macro scale it is necessary to understand the damage processes of building materials at the micro scale. In particular, durability of reinforced concrete structures is one of the most important equirements for construction planning and restoration of buildings. Therefore degradation mechanisms were reproduced on laboratory specimens.
CT (Computed Tomography) is commonly used for non-destructive microstructural defect analysis for recurring tests on concrete specimens. In this work a few examples of CT applications on cementitious materials (including cement paste, mortar and concrete specimens) will be presented.
Firstly, in order to quantify the degradation processes, specimens analysed were damaged by corrosion due to carbonation and due to chloride ingress. Particular focus has been set to the analysis of cracks.
An automated crack detection tool, developed by Zuse Institut Berlin (ZIB) and BAM in ZIBAmira, has been applied for quantitative analysis of crack parameters and 3D visualization of cracks.
Furthermore the distribution of corrosion products has been evaluated inside the cement matrix and visualized in 3D data sets.
Another important factor for the ageing stability of concrete is the interfacial transition zone (ITZ). The ITZ consists of a layer of cement paste (20 to 40 μm) over every aggregate where porosity is generally increased in comparison with the bulk. This zone could be a preferential zone for transfer of aggressive species. To visualize the ITZ, a small sample of mortar with a diameter of 10mm has been prepared and scanned using the industrial μCT setup at BAM with a spatial resolution of 5μm voxel size. In addition the extracted surface of aggregates could be used for load simulations. We finally show how CT examination of drilled samples taken from building materials in conjunction with laboratory experiments is helpful for further evaluations of damage processes in concrete.
Active thermography is an efficient non-destructive testing method for investigating the internal structure of larger carbon fiber reinforced plastic (CFRP) components as well as smaller CFRP components in mass customization. The method can be applied contactless and automated. This study contains systematic investigations of CFRP structures with typical defects and inhomogeneities occurring during production by means of flash thermography in reflection and transmission configuration and by computed tomography (CT). The latter one was used as a reference method, since also very small defects at larger depth can be visualized with high spatial resolution. The CFRP structures consist of plates which contain metallic and non-metallic inclusions, contaminations with glue or wax rests, areas with inhomogeneous re-injection of dry parts, fiber misalignments, and fiber damages. Further on, two specimens have been glued together with different artificial inhomogeneities of the four glue beads. The results of the applied methods are compared and the advantages and disadvantages of each configuration are discussed based on the detectability of the inhomogeneities. It is shown that although CT has led to best contrasts and spatial resolutions in displaying the inhomogeneities and inclusions, flash thermography is very well suited to detect most of these structures. Considering that flash thermography can be applied on-site and has a high potential for automation and for a fast and efficient testing, it can be highly recommended for quality assurance during and after production of CFRP structures.
This poster presentation gives an overview of the great potential of X-ray micro computed tomography (CT) to cast light on the evolution of the microstructure in construction materials. Prevention of damage is of major economic and social importance in the development of suitable construction materials such as concrete and asphalt. Therefore a non-destructive testing method such as CT is an appropriate tool for visualization of the inner structure. Its combination with other test methods allows understanding the damage processes such as crack propagation or corrosion. We show examples of internal structure analyses on a wide range of materials: Automatic 3D crack detection and the visualization of corrosion products inside of steel reinforced concrete, pore and shape analysis of lightweight aggregates and the visualization of deformation of high-pressure loaded aerated concrete specimens, distribution of aggregates inside concrete, and determination of the surface of porous asphalt core samples. Segmented structures serve, e.g., as input data for simulation of transport phenomena or virtual load tests.
Durch die Alkalität des Betons wird Betonstahl dauerhaft vor Korrosion geschützt. Infolge von Chlorideintrag kann dieser Schutz nicht länger aufrechterhalten werden und führt zu Lochkorrosion. Die zerstörungsfreie Prüfung von Stahlbetonproben mit 3D-CT bietet die Möglichkeit, eine Probe mehrfach gezielt vorzuschädigen und den Korrosionsfortschritt zu untersuchen. Zur Quanti-fizierung des Schädigungsgrades müssen die bei dieser Untersuchung anfallenden großen Bilddaten mit Bildverarbeitungsmethoden ausgewertet werden. Ein wesent-licher Schritt dabei ist die Segmentierung der Bilddaten, bei der zwischen Kor-rosionsprodukt (Rost), Betonstahl (BSt), Beton, Rissen, Poren und Umgebung unterschieden werden muss. Diese Segmentierung bildet die Grundlage für sta-tistische Untersuchungen des Schädigungsfortschritts. Hierbei sind die Änderung der BSt-Geometrie, die Zunahme von Korrosionsprodukten und deren Veränderung über die Zeit sowie ihrer räumlichen Verteilung in der Probe von Interesse. Auf-grund der Größe der CT-Bilddaten ist eine manuelle Segmentierung nicht durch-führbar, so dass automatische Verfahren unabdingbar sind. Dabei ist insbesondere die Segmentierung der Korrosionsprodukte in den Bilddaten ein schwieriges Problem. Allein aufgrund der Grauwerte ist eine Zuordnung nahezu unmöglich, denn die Grauwerte von Beton und Korrosionsprodukt unterscheiden sich kaum. Eine formbasierte Suche ist nicht offensichtlich, da die Korrosionsprodukte in Beton diffuse Formen haben.
Allerdings lässt sich Vorwissen über die Ausbreitung der Korrosionsprodukte nutzen. Sie bilden sich in räumlicher Nähe des BSt (in Bereichen vorheriger Volumenabnahme des BSt), entlang von Rissen sowie in Porenräumen, die direkt am BSt und in dessen Nahbereich liegen. Davon ausgehend wird vor der Korrosionsprodukterkennung zunächst eine BSt-Volumen-, Riss- und Porenerken-nung durchgeführt. Dieser in der Arbeit näher beschriebene Schritt erlaubt es, halb-automatisch Startpunkte (Seed Points) für die Korrosionsprodukterkennung zu finden. Weiterhin werden verschiedene in der Bildverarbeitung bekannte Algorithmen auf ihre Eignung untersucht werden.