4.7 Article

Comparison between different tensile test set-ups for the mechanical characterization of inorganic-matrix composites

Journal

CONSTRUCTION AND BUILDING MATERIALS
Volume 171, Issue -, Pages 140-151

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.conbuildmat.2018.03.041

Keywords

Inorganic-matrix composites; FRCM; TRM; Digital image correlation; Tensile tests

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Inorganic-matrix composite materials can be effectively employed to strengthen and retrofit existing reinforced concrete and masonry structures. These composite materials comprise high-strength fiber textiles embedded within inorganic matrices. Different textile layouts and types of matrix and fibers can be employed resulting in a multitude of different composite materials and mechanical behavior thereof. As in most composite materials, the mechanical characterization of the single constituents (matrix and fiber) does not provide indications on the behavior of the composite material. Therefore, the mechanical characterization of the entire composite material is of fundamental importance to understand the interaction (i.e. composite action) between the fiber textile and the embedding matrix. Although different tensile test set-ups were proposed In the literature, a shared standard testing method for the mechanical characterization of inorganic-matrix composites is not yet available. In this paper, the mechanical properties of four different inorganic-matrix composites comprising carbon, glass, basalt, and steel fibers embedded within cement- and lime-based matrices are investigated using two different tensile test set-ups. Analog LVDTs and digital image correlation (DIC) measurements are employed to study the specimen longitudinal strain behavior. Two criteria to assess the reliability of results of tensile tests are proposed. Comparison between results described in this paper shows the strong influence of the test set-up on the tensile behavior of inorganic-matrix composites and helps to shed light on the reliability of the mechanical parameters obtained. (C) 2018 Elsevier Ltd. All rights reserved.

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