Prediction on seismic performance levels of reinforced concrete beams by considering crack development

Abstract

The plastic rotation angle or deflection is typically used as the indicator to evaluate the earthquake-induced damage and classify the seismic performance levels of reinforced concrete (RC) beams. Herein, one of the most important issues is to determine the seismic performance level limits of RC beams. Whereas, different countries provided their specific method to determine the limit values by considering the loading-carrying capacity of RC beams, which could not be used to describe the earthquake-induced seepage of structures, especially for underground structures. Therefore, in this study, the seismic performance level limits of RC beams were predicted by using the machine learning methods and considering the development of cracks. Firstly, the seismic performance level limits of RC beams were presented after discussing the methods in different codes and the development of cracks. Then an earthquake performance test database of RC beams was established after collecting 452 test results of RC beams, and Pearson correlation analysis was conducted for feature selection to determine the input mechanical parameters and dimensional parameters for machine learning. Meanwhile, the correlation between the inputs and limit values was analyzed using the mutual information method. Regression models of seven machine learning methods were then established to predict the performance level limits of RC beams, and the hyperparameters of the machine learning models were optimized with the TPE optimization algorithm and cross-validation. The generalization ability of the prediction models was evaluated and the accuracy of predicted results by different methods was analyzed. Finally, the predicted seismic performance level limits of RC beams could be used to evaluate the earthquake-induced damage of RC beams by combining them with the seismic behavior of RC beams.