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In this study, the bending behavior of Slim-Floor beams was analyzed using FE models developed in the ABAQUS software. The validity of these models was demonstrated by comparing the numerical results obtained with experimental data found in the literature. Through parametric evaluations, the following findings were verified: (i) the connection mechanisms adopted (concrete dowels, reinforcing steel bars, and adherence) were able to activate the composite behavior between steel and concrete; (ii) the spacing between the openings, the number of openings, and the diameter of the reinforcing steel bars determine the behavior of the connection; (iii) adherence contributes little to the strength of the connection, and therefore, its contribution can be neglected; (iv) the connection mechanisms adopted in this study can promote the ductile behavior of the Slim-Floor beams.

Recently, castellated columns have been increasingly used in buildings because of their flexibility, easy compatibility and potential savings due to less steel consumption. However, there is a lack of research related to the subject. In view of that, this work evaluates the influence of the opening type and size on the resistant capacity of the column, considering a nonlinear plastic analysis by the finite element method (792 simulations). For this, columns without openings were modeled to validate the methodology proposed. After validation, a nonlinear buckling analysis of castellated columns was performed. In this study, different cut patterns of the beam web are evaluated, as well as residual stresses, material and geometric imperfections, based on a statistical design. The loads obtained by castellated columns and columns without web are compared. Also, the resistance reduction factors associated with global buckling (χ) for castellated profiles are compared to the values proposed by ABNR NBR 8800 (2008). Furthermore, statistically, there are no differences between the opening types evaluated. Finally, in order to contribute to the design of castellated columns, equations based on regression models were found to predict the load capacity of these elements.