Abstract
This study explores the possibility of using an ANN-based model for the rapid numerical simulation and seismic performance prediction of reinforced concrete (RC) columns. The artificial neural network (ANN) method is implemented to model the relationship between the input features of RC columns and the critical parameters of the commonly used lumped plasticity (LP) model: The strength and the yielding, capping and ultimate deformation capacity. Cyclic test data of 1163 column specimens obtained from the PEER and NEEShub database and other sources are collected and divided into the training set, test set and validation set for the ANN model. The effectiveness of the proposed ANN model is validated by comparing it with existing explicit formulas and experimental results. Results indicated that the developed model can effectively predict the strength and deformation capacities of RC columns. Furthermore, the response of two RC frame structures under static force and strong ground motion were simulated by the ANN-based, bi-linear and tri-linear LP model method. The good agreement between the proposed model and test results validated that the ANN-based method can provide sufficiently accurate model parameters for modeling the seismic response of RC columns using the LP model.
Highlights
Reinforced concrete (RC) columns are fundamental structural components that are widely used in civil infrastructures such as buildings and bridges
863 specimens the specimens and the corresponding test results on the strength and drift capacities were normalized as database were randomly selected as the training set
Since there are currently no explicit formula for the estimation of capping drift corresponding to the maximum strength, Figure 10 only shows the comparison of the experimental results of the capping drift of the column and the predicted results from the artificial neural network (ANN) model, with the mean absolute error of 0.0794 and 0.1071, goodness of fit of 0.8001 and 0.8345, for the training set and the test and (a) Shear-failed specimens (b) Flexural-dominated specimens
Summary
Reinforced concrete (RC) columns are fundamental structural components that are widely used in civil infrastructures such as buildings and bridges. In seismic-prone regions, the seismic performance of such structural components significantly affects structural safety in seismic events. Due to the nonlinearity of structural materials and the uncertainty of earthquake excitations, there are still some difficulties exists for researchers and engineers in some fields, e.g., the rapid seismic evaluation of a regional transport network, including a number of bridges [1]. It is still necessary to develop a rapid and reliable model for the main components of structures, e.g., RC columns and piers. Researchers and engineers in seismic engineering have conducted many laboratory experiments, including pseudo-static and shaking table tests, to investigate the mechanical properties of RC columns. Several explicit formulas have been established, founded upon a
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