Article of RILEM TC 292-MCC: bond behaviour of textile-reinforced concrete—a review

Textile-reinforced concrete (TRC) has gained a lot of attraction in recent years. Adequate bond between the phases in this system allows to transfer high loadings, thus enabling high performance. The terminus textile reinforcement, however, comprises many different types of fabrics, which differ in...

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Bibliographic Details
Published in:Materials and structures Vol. 57; no. 4
Main Authors: Preinstorfer, Philipp, El Kadi, Michael, Dittel, Gözdem, Ghiassi, Bahman, Müller, Steffen, Mansur de Castro Silva, Rebecca, Mobasher, Barzin, de Andrade Silva, Flavio, Peled, Alva
Format: Journal Article
Language:English
Published: Dordrecht Springer Netherlands 01-05-2024
Springer Nature B.V
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Summary:Textile-reinforced concrete (TRC) has gained a lot of attraction in recent years. Adequate bond between the phases in this system allows to transfer high loadings, thus enabling high performance. The terminus textile reinforcement, however, comprises many different types of fabrics, which differ in their chemical composition, geometry, surface properties etc., and thus exhibit substantially different bond properties. In the course of RILEM’s Technical Committee 292 work on TRC it was found that a comprehensive understanding of the complex interactions between individual parameters is still lacking. This is amplified by the fact that different types of textile reinforcement are preferably used in different regions of the world. This paper therefore attempts to compile findings from literature on the bond in TRC. The database used was created in the course of the TC work. Additional papers of relevance were identified by scanning scientific web databases. The different influencing parameters are given in this paper in a hierarchical order, starting from the level of the individual constituents (filament and matrix) to impregnated fabrics and the influence of textile manufacturing and architecture on the bond. Finally, by mapping all the cited literature used in this paper based on grouped keywords the complex intercorrelations are visualised.
ISSN:1359-5997
1871-6873
DOI:10.1617/s11527-024-02339-5