Mathematical micromodeling of infilled frames: State of the art

Anisotropic Failure Criterion for Britle Materials Using Artificial Neural Networks

“…However there have not been many attempts to apply a Neural Network (NN) for the prediction of masonry behavior in general. In the present paper, following and expanding a previous work by the authors [10] which focused on biaxial compressive stress only, the use of Neural Networks is proposed to approximate the failure surface of masonry materials in a dimensionless form for any quadrant of stress state.…”

“…Detailed and in-depth state-of-the-art reports can be found in [6][7][8][9][10][11]. The successful implementation of these advanced models requires reliable analytical constitutive rules such as constitutive equation models of masonry material failure.…”

Inelastic Response of Masonry Infilled Reinforced Concrete Structures

“…A significant bracing action, affecting both the strength and stiffness, originates by this mechanism, as demonstrated by a large number of experimental investigations [1][2][3][4][5][6][7][8][9][10][11][12][13] and analytical-numerical studies [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32]. However, despite several modelling strategies available in the literature, going from pinned equivalent struts macromodeling to FE micromodeling [33][34][35][36][37][38], masonry infills are generally not accounted for in models because of the large amount of uncertainties arising during their structural identification.…”

Lateral Response Evaluation of Steel Frame Structures With Masonry Infills

“…Even though multi-strut models are more accurate than single ones, they are also less intuitive and require much more parameters to be properly setup. Detailed and in-depth state-of-the art works can be found in Asteris et al 2011Asteris et al & 2013, and Mohyeddin et al 2017 [11].…”