FraMCoS 7 2010 Jeju, South Korea

Crack bridging behaviour of AR glass multifilament yarns embedded in cement based matrix Modelling of ageing effects

In this research project age-dependent changes in the crack-bridging behaviour of AR-glass multifilament yarns embedded in cementitious matrix were investigated at the meso and micro levels. Two cementitious matrices were considered where the binder contained Portland cement clinker. Mechanical char-…

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Year 2010
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Abstract

In this research project age-dependent changes in the crack-bridging behaviour of AR-glass multifilament yarns embedded in cementitious matrix were investigated at the meso and micro levels. Two cementitious matrices were considered where the binder contained Portland cement clinker. Mechanical char- acteristics of the bond between matrix and multifilament yarns after accelerated ageing were measured by means of double-sided yarn pullout tests. In these tests the multifilament yarns bridged a single crack in the matrix arising in a notched area of the specimen. Losses in crack-bridging performance with increasing age of composite were observed. The essential cause of such losses was discovered to be the microscopic densifica- tion of the fibre-to-matrix interface. This led to increased bond intensity and restricted slip-ability of the fila- ments. A phenomenonological bond model was developed to relate these structural phenomena at the micro- scopic level to the mesoscopic material behavior. This cross-linkage model describes the crack-bridging effect of the entire multifilament yarn at the single filament level. According to the model, each filament pos- sesses a specific deformation length depending on its position in the cross-section of the yarn. This deforma- tion length depends on bond characteristics between single filament and cementitious matrix, which vary with age. Characteristic values of the model were computed from load-crack width curves obtained from the yarn pullout tests. The changes in the microstructure were represented by the characteristic values of the model.