Mechanical characterization of textile reinforced cementitious composites under impact tensile loading using the split Hopkinson tension bar

Strain-hardening cement-based composites (SHCC) reinforced additionally with continuous textile reinforcement exhibit a high tensile strength, ductility and low crack width up to failure localization, being suitable as strengthening layers on structural elements subject to impact loading. The quasi-static tensile properties of such composites are usually derived on long, planar specimens, as dictated by the geometry of the textile reinforcement and by the necessity of sufficient yarn anchorage. However, with regard to high strain rate testing in split Hopkinson bar systems, both the length and the planar shape of the textile reinforced specimen represent major drawbacks. This explains the lack of comprehensive investigations on the mechanical performance of textile reinforced cement-based composites from the perspective of material characterization. This paper presents two new configurations of a gravity-driven split Hopkinson tension bar (SHTB) purposefully developed for investigating the tensile behavior of such composites under strain/displacement rates in the range of impact loading. The first configuration is designed for uniaxial tension tests on planar textile reinforced composites. The planer specimens are attached to the input and output bars using special aluminum adapters. The influence of the adapters and of specimen geometry on wave propagation and dynamic stress equilibrium is discussed in detail based on the results of experimental and numerical investigation. Corresponding amendments to the traditional wave analysis and suitable evaluation methods are proposed for an accurate assessment of the material response. Additionally, a novel testing configuration for single-yarn pullout experiments is presented. This setup allows for a detailed description of the rate effects on the bond between textile yarns and cementitious matrix.

» Author: Ali A. Heravi, Alexander Fuchs, Ting Gong, Iurie Curosu, Michael Kaliske, Viktor Mechtcherine

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This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement Nº 737882.



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