Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/902
Title: Determination of moment, shear and ductility capacities of spiral columns using an artificial neural network
Authors: Koçer, Mustafa
Öztürk, Murat
Arslan, M. Hakan
Keywords: Algorithm
Reinforced Concrete
Spiral Column
Artificial Neural Networks
Capacities
Compressive Strength
Prediction
Beams
Design
Publisher: ELSEVIER
Abstract: Intelligent systems are frequently used to solve difficult and complex problems in today's world. Especially in the discipline of civil engineering, much research has been conducted with the help of intelligent systems. The objective of this study is to identify the moment and shear force capacities of reinforced concrete spiral columns and their displacement ductility values by using an algorithm based on an Artificial Neural Network (ANN). In the study, 86 different spiral column experiments tested in the literature were compiled, and the moment and shear force capacities obtained through the experiments were arranged at a certain level. In addition, the ductility values of the tested columns were calculated using graphical experimental data. The output layer consists of four neural network models, which are ANN(1) (with three output neurons), ANN(2), ANN(3), and ANN(4) (with one output neuron), and moment, shear force capacity, and displacement ductility parameters were obtained, respectively. According to results of this study, it was observed that moment and shear force capacities of spiral columns could be particularly well estimated using ANN. However, it was found that the estimation success of ANN for displacement ductility was not sufficient.
URI: https://doi.org/10.1016/j.jobe.2019.100878
https://hdl.handle.net/20.500.13091/902
ISSN: 2352-7102
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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