Giulio Castori, Antonio Borri, Marco Corradi and Righetti Luca
Giulio Castori, Researcher, Dept. of Engineering, Perugia University, Via Duranti, 92 06125 Perugia, Italy giulio.castori@unipg.it
Antonio Borri, Professor, Dept. of Engineering, Perugia University, Via Duranti, 92 06125 Perugia, Italy antonio.borri@unipg.it
Marco Corradi, Associate Professor, Dept. of Mechanical & Construction Engineering, Northumbria University, Wynne-Jones Building, NE1 8ST Newcastle Upon Tyne, United Kingdom, marco.corradi@northumbria.ac.uk, and Dept. of Engineering, Perugia University, Via Duranti, 92 06125 Perugia, Italy marco.corradi@unipg.it
Righetti Luca, PhD candidate, Dept. of Mechanical & Construction Engineering, Northumbria University, Wynne-Jones Building, NE1 8ST Newcastle Upon Tyne, United Kingdom, luca.righetti@northumbria.ac.uk
ABSTRACT
Over the last fifteen years, new techniques and materials have been used to retrofit masonry structures for improved seismic performance as well as a variety of other strengthening applications. The global behavior of a stone masonry wall is often governed by the level of connection between masonry leaves and the overall quality of the masonry material (mortar, block and arrangement). This paper presents the results of an investigation carried out on multi leaf stone masonry panels retrofitted using stainless steel rod inserted in a grouted fabric sleeve. The paper also reports the results of a non-linear numerical investigation calibrated using laboratory tests. Several wall panels were assembled in the laboratory using solid calcareous stones and weak mortar and the effectiveness of the connectors was tested in shear and compression on both virgin and damaged wall panels. Experimental results show that a substantial improvement of the panels’ mechanical behavior can be achieved by applying transverse connectors. The feasibility of using the 3-Dimensional (3D) finite element model to analyze multi-leaf walls reinforced with transverse connectors is examined by comparing the model to experimental data.
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