Statistical analysis of the bonding properties of the fabric-reinforced cementitious matrix for strengthening masonry structures

Document Type

Journal Article

Publication Title

Advances in Structural Engineering

Publisher

SAGE

School

School of Engineering

RAS ID

39656

Funders

China University of Mining and Technology Postgraduate Research & Practice Innovation Program of Jiangsu Province the Six Talent Peaks Project in Jiangsu Province

Comments

Jing, L., Yin, S., Aslani, F., & Liu, S. (2021). Statistical analysis of the bonding properties of the fabric-reinforced cementitious matrix for strengthening masonry structures. Advances in Structural Engineering, 24(13), 3057-3069. https://doi.org/10.1177/13694332211017994

Abstract

The fabric-reinforced cementitious matrix (FRCM) has been extensively studied and applied for the strengthening of masonry structures. Special attention needs to be given to the bonding properties between the FRCM and masonry substrate for strengthening applications. This paper presents a statistical analysis of the bonding properties based on the available literature. First, the collected test results were discussed in terms of the interfacial failure mode. Second, the factors influencing the ultimate bond load were analysed based on the different failure modes, and a corresponding prediction formula was further determined via regression analysis for interfacial debonding and slippage failures. Then, the characteristic values of the ultimate bond load were determined via a probabilistic method. Finally, the fracture energy for the slippage failure at the fabric-matrix interface was analysed, and a corresponding prediction formula was obtained via regression analysis. Additionally, some of the collected test results present higher dispersion due to the large variability of the FRCM material properties and the differences in the testing procedures used by different institutions. More studies are needed to improve the reliability of the proposed procedure.

DOI

10.1177/13694332211017994

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