MECHANICAL PRORERTIES OF EXPOSED COLUMN BASE CONNECTIONS FOR L-SHAPED COLUMNS FABRICATED USING CONCRETE-FILLED STEEL TUBES

The response of exposed column base connections for L-shaped column is investigated through finite element analysis (FEA) in this paper which is affected by complex interactions among different components. Three finite element models are constructed to simulate the response of these connections under axial and cyclic horizontal loading, which interrogate a range of variables including anchor rod strength, base plate size and thickness. The results of the simulations provide insights into internal stress distributions which have not been measured directly through experiments. The key findings indicate that thicker base plates tend to shift the stresses to the toe of the base plate, while thinner plates concentrate the stresses under the column flange. Base on the analytical results, a hysteretic model is proposed to describe the cyclic moment-rotation response of exposed column base connections. The core parameters used to define the backbone curve of the hysteretic model are calibrated through configurational details. The comparison between the simulation and the calculated values indicates that the hysteretic model is suitable to characterize the key aspects of the physical response, including pinching, recentering and flag-shaped hysteresis phenomenon. Limitations of the model are outlined.

Formulation of Performance Levels and Relevant Limitations for Clay Brick Masonry Infills in Seismic Analysis of R/C Frame Structures

Observation of damage caused by recent earthquakes highlights, once again, that the presence of infills significantly affects the seismic response of reinforced concrete (R.C.) frame buildings. Therefore, in spite of the fact that infills are non-structural elements, and thus they are normally not considered in structural analyses, in many cases their contribution should not be neglected. Based on these observations, the study proposed in this paper consists in the evaluation of the seismic response of infills in time-history finite element analyses of R.C. frame structures by means of a two-element model, constituted by two diagonal nonlinear beams. A “concrete”-type hysteretic model predicts the in-plane state of infills, through a force-displacement backbone curve expressly generated, and scanned in terms of performance limits, to this aim. This model is demonstratively applied to a real case study, i.e. a R.C. frame building including various types of brick masonry perimeter infills and internal partitions, damaged by the 30 October 2016 Central Italy earthquake. The time-histories seismic analyses carried out on it allows checking the influence of infills on the response of the structure, as well the effectiveness of the proposed model in reproducing the observed real damage on the masonry panels.

Data-driven seismic response prediction of structural components

Lateral stiffness of structural components, such as reinforced concrete (RC) columns, plays an important role in resisting the lateral earthquake loads. The lateral stiffness relates the lateral force to the lateral deformation, having a critical effect on the accuracy of the lateral seismic response predictions. The classical methods (e.g. fiber beam–column model) to estimate the lateral stiffness require calculations from section, element, and structural levels, which is time-consuming. Moreover, the shear deformation and bond-slip effect may also need to be included to more accurately calculate the lateral stiffness, which further increases the modeling difficulties and the computational cost. To reduce the computational time and enhance the accuracy of the predictions, this article proposes a novel data-driven method to predict the laterally seismic response based on the estimated lateral stiffness. The proposed method integrates the machine learning (ML) approach with the hysteretic model, where ML is used to compute the parameters that govern the nonlinear properties of the lateral response of target structural components directly from a training set composed of experimental data (i.e. data-driven procedure) and the hysteretic model is used to directly output the lateral stiffness based on the computed parameters and then to perform the seismic analysis. We apply the proposed method to predict the lateral seismic response of various types of RC columns subjected to cyclic loading and ground motions. We present the detailed model formulation for the application, including the developments of a modified hysteretic model, a hybrid optimization algorithm, and two data-driven seismic response solvers. The results predicted by the proposed method are compared with those obtained by classical methods with the experimental data serving as the ground truth, showing that the proposed method significantly outperforms the classical methods in both generalized prediction capabilities and computational efficiency.