Refining the masonry shear modulus in masonry towers via Bayesian model updating

The assessment of the structural behavior of masonry towers often involves developing and identifying computational models to be used to perform static and/or time-history nonlinear analyses. Such models are frequently developed assuming isotropic masonry behavior, with model identification carried out - based on available experimental data - through deterministic tuning of a limited set of representative parameters. However, masonry exhibits complex structural textures that often deviate significantly from the commonly made assumption of isotropic behaviour. This paper investigates the effects of this assumption by focusing on the masonry shear modulus. A two-dimensional rigid body–spring model is adopted as computational approach, as its fully discrete formulation allows overcoming the limitations of the Cauchy continuum while maintaining a reduced computational cost. A Bayesian updating framework based on dynamic experimental data is employed to account for multiple sources of uncertainty, including parameter uncertainty, model inadequacy, and observation errors. Three masonry towers with different slenderness ratios are considered as representative case studies. The adopted Bayesian model updating approach allows for the estimation of their shear modulus while accounting for uncertainties, and the results show that the common assumption of isotropic behaviour in masonry numerical modelling does not hold. Using a fully discrete computational approach in combination with experimental frequency data, this behaviour has been observed for squat masonry towers.