A detailed micro-modelling approach for the structural analysis of masonry assemblages. (15th August 2018) - Sarhosis, V.; Lemos, J.V.
Highlights: A detailed micro-modelling approach to represent the micro-structure of masonry assemblages proposed. Masonry considered as an assemblage of densely packed discrete irregular particles. A fair to good agreement between the experimental and the numerical results was obtained. Cracking allowed to occur either at the brick, mortar and/or brick/mortar interface. Approach can be used as a tool to understanding of the processes related to the brittle failure of masonry. Abstract: Over the last 50 years, a significant amount of effort has been taken to develop numerical approaches and tools for the structural analysis of masonry. These range from considering masonry as an anisotropic continuum (macro-models) to the more detailed ones considering masonry as an assemblage of units and joints (micro-models). In this paper, a detailed micro-modelling approach for the analysis of masonry couplets and prisms is proposed. The approach represents masonry units and mortar joints as an assemblage of densely packed discrete irregular deformable particles bonded together by zero thickness interface laws. The mechanical properties (here referred to as micro-properties) of irregular particles and contacts are responsible for the mechanical behaviour of masonry. In addition, the approach allows failure to occur either at the brick, mortar and/or brick/mortar interface. A series of computational models were developed and their results are compared against small-scale experimental findings. A good agreement between the experimental and the numerical results was obtained which demonstrates the huge potential of the modelling approach proposed. The significant advantage of this approach is to model cracking as a real discontinuity among particles and not as a modification in the material properties. In addition, reliable prediction of masonry strength can allow one to reduce the costly and timely experimental testing and avoid the reliance on conservative empirical formulas.