A numerical model based on the heuristic molecule (HM) concept is proposed to evaluate the in-plane and Coulomb-like shear behavior of masonry panels. The model extends the well-established Rigid-Body-Spring Model (RBSM), which demonstrated good effectiveness in the seismic analysis of masonry structures. The proposed advancement introduces two diagonal bond-springs specifically designed to improve the representation of shear damage mechanisms. The performance of this enhanced formulation was assessed through numerical simulations of small-scale shear panel tests experimentally tested in the literature under varying levels of pre-compression, for which dedicated nonlinear stress–strain laws for axial, shear, and diagonal bond-springs were implemented. The results indicate that the proposed model provides an accurate description of the observed behavior while maintaining a limited number of degrees of freedom, thus ensuring computational efficiency. These promising outcomes highlight the model’s potential for future applications, including large-scale dynamic analyses.
Modeling the In-Plane Shear Behavior of Periodic Masonry Arrangements by Means of a Heuristic Molecule Approach
Casolo, Siro
2026-01-01
Abstract
A numerical model based on the heuristic molecule (HM) concept is proposed to evaluate the in-plane and Coulomb-like shear behavior of masonry panels. The model extends the well-established Rigid-Body-Spring Model (RBSM), which demonstrated good effectiveness in the seismic analysis of masonry structures. The proposed advancement introduces two diagonal bond-springs specifically designed to improve the representation of shear damage mechanisms. The performance of this enhanced formulation was assessed through numerical simulations of small-scale shear panel tests experimentally tested in the literature under varying levels of pre-compression, for which dedicated nonlinear stress–strain laws for axial, shear, and diagonal bond-springs were implemented. The results indicate that the proposed model provides an accurate description of the observed behavior while maintaining a limited number of degrees of freedom, thus ensuring computational efficiency. These promising outcomes highlight the model’s potential for future applications, including large-scale dynamic analyses.| File | Dimensione | Formato | |
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