Predicting the Hysteretic Cycles of 3D-Reinforced Concrete Frames by ANN

FATIH, BAHADIR and FATIH, SULEYMAN BALIK (2014) Predicting the Hysteretic Cycles of 3D-Reinforced Concrete Frames by ANN. In: Second International Conference on Advances In Civil, Structural and Environmental Engineering- ACSEE 2014, 25 - 26 October 2014, Zurich, Switzerland.

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Abstract

In this study, artificial neural network (ANN) method is used to predict displacement data of 3D-reinforced concrete frames and compared with the experimental results of a testing series. Three reinforced concrete frames were produced two storey and 3D in 1/6 geometric scales which contained the deficiencies commonly observed problems in residential buildings in Turkey were tested under reverse-cyclic lateral loading as well as constant vertical loading until failure. These experimental studies are 3-D and having different window opening in brick wall. This study is concerned with the problem of estimation of displacement data when the LVDT of 103 numbers are corrupted and some data of hysteretic cycles are missed. As a result, the values are very closer to the experimental results obtained from training and testing for artificial neural networks model. RMSE, R2 and MAE statistical values that calculated for comparing experimental results with artificial neural networks model results have shown this situation.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: 3D-Reinforced Concrete, ANN, Hysteretic Cycles, Displacement
Depositing User: Mr. John Steve
Date Deposited: 30 May 2019 09:02
Last Modified: 30 May 2019 09:02
URI: http://publications.theired.org/id/eprint/3054

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