CRACK PATTERN PREDICTION OF LATERALLY LOADED PANELS WITH OPENINGS BASED ON ANN METHOD
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Title CRACK PATTERN PREDICTION OF LATERALLY LOADED PANELS WITH OPENINGS BASED ON ANN METHOD
Creator YONGFEI WANG, YU ZHANG
Contributor Didem Ozevin, Hossein Ataei, Mehdi Modares, Asli Pelin Gurgun, Siamak Yazdani, Amarjit Singh
Publisher ISEC PRESS
Publication Year 2562
Keyword Cellular automata, Digitalization, Weakness, Fragility coefficient, Backpropagation neural network
Abstract In this paper a Back Propagation Neural Network (BPNN) is used to predict crack pattern for masonry panels with opening subjected to lateral loading. The cellular automata method is used to digitalize the panels, including two steps----dividing a panel into a certain number of cells and calculating cell state values by Von Neumann neighborhood model. These digitalized values are used as input data of NN model respectively. All the experimental data is collected, including panel's configuration, material property, opening ratio and location, state values, crack pattern. The NN model is trained repeatedly, taking part of the data as a training set, to determine parameters. And the rest data is taken to check the model. Well-trained NN model can predict the crack pattern of any other panel. The results show that NN method is suitable for prediction of crack pattern. Comparing the two ways of prediction, the Fragility Coefficient Method gets a more precise pattern. The predicted cracks are distributed successively in some specific areas, especially in high similarity, compared with experimental crack pattern.
ISBN 978-0-9960437-6-2
Language English
URL Website https://www.isec-society.org/
Website title ISEC Society
International Struct Eng and Constructn Society

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