Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Real-time Seismic Damage Detection of Concrete Shear Walls Using Artificial Neural Networks
Concrete shear walls are widely employed in buildings as a main resistance system against lateral loads. Early identification of seismic damage to concrete shear walls is vital for deciding post-earthquake occupancy in these structures. In this article, a method based on artificial neural networks for real-time identification of seismic damage to concrete shear walls was proposed. Inter-story drifts and plastic hinge rotation of concrete walls were used as the inputs and outputs of a MLP neural network. Modal Pushover Analysis was employed to prepare well-distributed data sets for training the neural network. The proposed method was applied to a five-story concrete shear wall building. The results from the network were compared with those obtained from Nonlinear Time History Analysis. It was observed that the trained neural network successfully detected damage to concrete shear walls and accurately estimated the severity of seismic-induced damage.
Real-time Seismic Damage Detection of Concrete Shear Walls Using Artificial Neural Networks
Concrete shear walls are widely employed in buildings as a main resistance system against lateral loads. Early identification of seismic damage to concrete shear walls is vital for deciding post-earthquake occupancy in these structures. In this article, a method based on artificial neural networks for real-time identification of seismic damage to concrete shear walls was proposed. Inter-story drifts and plastic hinge rotation of concrete walls were used as the inputs and outputs of a MLP neural network. Modal Pushover Analysis was employed to prepare well-distributed data sets for training the neural network. The proposed method was applied to a five-story concrete shear wall building. The results from the network were compared with those obtained from Nonlinear Time History Analysis. It was observed that the trained neural network successfully detected damage to concrete shear walls and accurately estimated the severity of seismic-induced damage.
Real-time Seismic Damage Detection of Concrete Shear Walls Using Artificial Neural Networks
Vafaei, Mohammadreza (Autor:in) / Adnan, Azlan bin (Autor:in) / Abd. Rahman, Ahmad Baharuddin (Autor:in)
Journal of Earthquake Engineering ; 17 ; 137-154
01.01.2013
18 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Real-time Seismic Damage Detection of Concrete Shear Walls Using Artificial Neural Networks
| Online Contents | 2013
Seismic behaviour of concrete shear walls
| NTIS | 1989
Damage Detection of Reinforced Concrete Shear Walls Using Mathematical Transformations
| DOAJ | 2017
Seismic behavior of reinforced concrete shear walls
| NTIS | 1989
Failure Mode Detection of Reinforced Concrete Shear Walls Using Ensemble Deep Neural Networks
| Springer Verlag | 2022