An existing interface material model for quasi-brittle fracture, originally developed within the Discrete Element Method framework, is implemented and enhanced for use in implicit Finite Element analyses of unreinforced masonry structures. The model captures mixed-mode fracture in tension-shear and combines cohesion with Coulomb friction in compression-shear. To address convergence issues arising when loading–unloading takes place, due to a discontinuity in the traction–separation relation, a regularization of the frictional contribution is proposed. A new model parameter is introduced and a calibration procedure to ensure numerical robustness and objectivity is presented. Furthermore, the consistent tangent stiffness matrix is derived to improve convergence in full-scale simulations. The improved model is applied within a simplified micromodelling approach to simulate the in-plane cyclic response of 2D masonry structures, including a shear wall and a spandrel subjected to a combination of horizontal and vertical actions. The results demonstrate that the model accurately reproduces key aspects of masonry behaviour, including stiffness degradation, energy dissipation, and crack patterns, while maintaining robustness and efficiency in complex cyclic loading scenarios.

Different analytical models exist to predict the shear strength of reinforced concrete members. Generally, each of these shear strength models consists of a formulation based on certain underlying theory and fitted model coefficients. The model fitting parameters are usually established from the comparison with test data. Hence, the predictive value of a shear strength model depends, to some extent, on the quality and representativeness of the used test data. This work investigates the predictive capability of several shear strength models for reinforced concrete beams without shear reinforcement. Particular attention is given to the application domain of relatively low reinforced and high depth concrete beams where limited shear test data is available. The predictive capability of the models for this area of interest is analyzed with Bayesian Inference. This probabilistic technique calculates the posterior distributions of uncertain parameters, given a set of measured test data and some prior knowledge. The predictive capability of each shear strength model is quantified by means of a calculated model uncertainty. Furthermore, the influence of the uncertainty in model parameter values on the calculated model uncertainties is evaluated. Bayesian Inference is also used to estimate the model evidences conditionally on the used data.