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Preliminary communication

https://doi.org/10.14256/JCE.3894.2023

Numerical modelling of masonry structural joint repointing: finite element analysis based on experimental investigations

Sergey Churilov
Elena Dumova-Jovanoska


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Full text: english pdf 2.230 Kb

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Abstract

This study investigated the efficacy of joint repointing as a strengthening technique for unreinforced masonry (URM) structures via experimental data combined with advanced numerical modelling. The numerical simulations demonstrated remarkable alignment with the experimental data, validating the efficacy of the proposed modelling approach. The finite element analysis results were consistent with the experimentally observed stress–strain relationships, failure modes, and ultimate capacities of the masonry panels. The calibrated model successfully replicated the enhanced performance of the strengthened specimens, particularly in terms of increased compressive and shear strengths. Although parametric studies were not performed directly in this study, the validated numerical model provides a solid foundation for future investigations. The accurate reproduction of experimental results through finite element modelling facilitates the potential for extensive parametric analyses, which could explore various strengthening configurations and material properties without the need for costly and time-consuming physical experiments—particularly valuable for assessing and optimising retrofitting strategies for existing URM buildings, particularly in seismic-prone regions. This research contributes significantly to the field of structural engineering by demonstrating the potential of simplified micromodelling techniques to capture the intricacies of masonry behaviour at the meso-level.

Keywords

simplified micro-modelling; unreinforced masonry; joint repointing strengthening; nonlinear finite element analysis; masonry interface modelling

Hrčak ID:

321020

URI

https://hrcak.srce.hr/321020

Publication date:

30.9.2024.

Article data in other languages: croatian

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