Ingenieurwissenschaften und zugeordnete Tätigkeiten
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- Fiber-reinforced concrete (2) (entfernen)
Organisationseinheit der BAM
Fiber-reinforced concretes (FRCs) offer significant improvements in tensile strength and durability compared to most other concrete mixes.
However, for safe and efficient use of FRC in large structures, anisotropy of fiber orientation needs to be understood and properly controlled. In this project, both cored samples extracted from a FRC slab and FRC samples cast individually in molds were assessed using X-ray computed tomography (CT) and measurements of fiber orientation were extracted from the resulting CT images. These results showed that fibers within the slab were highly anisotropic in orientation while fibers in individually cast samples showed a much more heterogeneous distribution of orientations.
This indicates that fiber orientation is highly dependent on the casting process and suggests that FRC can only be safely and efficiently utilized if anisotropic fiber orientation is properly accounted for during design and optimized casting methods are used during construction.
The reinforcement of concrete with polymer fibers provides resistance to crack formation. The orientation distribution of these fibers has a significant influence on the mechanical behavior of the material. To optimize material performance, micromechanical models that are capable of making accurate predictions of the mechanical behavior of composite materials are needed. These models must be calibrated using experimental results from microstructural characterization. For the fiber orientation distribution analysis in the present study, computed tomography (CT) data were used to evaluate the properties of a fiber-reinforced cement mortar. The results have indicated that the fibers in this material have highly anisotropic orientation characteristics and that there is a clear tendency for the polymer fibers to agglomerate during mixing and casting. The incorporation of this experimental data into micromechanical models will increase the accuracy of those models for material simulation and optimization.