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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.
Water migration in one-side heated concrete: 4D in-situ CT monitoring of the moisture-clog-effect
(2019)
Explosive spalling due to fire exposure in concrete structures can lead severe damage and, in the worst case, to premature component failure. For this reason, an in situ investigation of water Migration in concrete due to surface heating was undertaken.
During these experiments, a miniaturized concrete specimen within a confining and insulating double-hull was subjected to surface heating during simultaneous X-ray computed tomography (CT) scanning. Through the use of subtraction-based Image analysis techniques, it was possible to observe and quantify not only drying within areas of the concrete matrix close to the heated surface, but also the migration of moisture to both pore and matrix regions deeper within the specimen. It was also discovered that the correction of CT images for specimen deformation using DVC and variable detector performance using calibrated image filters significantly improved the quality of the results. This clearly demonstrates the potential of X-ray CT for evaluation of other rapid-density-change phenomena in concrete and other building materials.
This paper focuses on the experimental evaluation of one of the key microstructural Parameters of a short-fiber reinforced composite – the orientation distribution of fibers. It is shown that computed tomography (CT) produces results suitable for reconstruction of the orientation distribution function. This function is used for calculation of the effective elastic properties of polymer-fiber reinforced concrete. Explicit formulas are derived for overall elastic moduli accounting for orientation distribution in the frameworks of the noninteraction approximation, the Mori–Tanaka–Benveniste scheme, and the Maxwell scheme.
The approach illustrated can be applied to any kind of composite material.
Simulating fiber-reinforced concrete mechanical performance using CT-based fiber orientation data
(2019)
The main hindrance to realistic models of fiber-reinforced concrete (FRC) is the local materials property variation, which does not yet reliably allow simulations at the structural level. The idea presented in this paper makes use of an existing constitutive model, but resolves the problem of localized material variation through X-ray computed tomography (CT)-based pre-processing. First, a three-point bending test of a notched beam is considered, where pre-test fiber orientations are measured using CT. A numerical model is then built with the zone subjected to progressive damage, modeled using an orthotropic damage model. To each of the finite elements within this zone, a local coordinate system is assigned, with its longitudinal direction defined by local fiber orientations. Second, the parameters of the constitutive damage model are determined through inverse analysis using load-displacement data obtained from the test. These parameters are considered to clearly explain the material behavior for any arbitrary external action and fiber orientation, for the same geometrical properties and volumetric ratio of fibers. Third, the effectiveness of the resulting model is demonstrated using a second, “control” experiment. The results of the “control” experiment analyzed in this research compare well with the model results. The ultimate strength was predicted with an error of about 6%, while the work-of-load was predicted within 4%. It demonstrates the potential of this method for accurately predicting the mechanical performance of FRC components.