IAHR, founded in 1935, is a worldwide independent member-based organisation of engineers and water specialists working in fields related to the hydro-environmental sciences and their practical application. Activities range from river and maritime hydraulics to water resources development and eco-hydraulics, through to ice engineering, hydroinformatics, and hydraulic machinery.
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You are here : eLibrary : IAHR World Congress Proceedings : 36th Congress - The Hague (2015) FULL PAPERS : THEME 4- WATER ENGINEERING : ARTIFICIAL NEURAL NETWORK MODELING TO PREDICT COMPLEX BRIDGE PIER SCOUR DEPTH
ARTIFICIAL NEURAL NETWORK MODELING TO PREDICT COMPLEX BRIDGE PIER SCOUR DEPTH
Author : HABIBEH GHODSI1, MOHAMMAD J. KHANJANI2, ALI A. BEHESHTI3
Flow mechanism around a bridge pier is complicated and difficult to present a general model to provide a good prediction of scour depth. Geotechnical and economical parameters govern design of complex bridge pier design. The interaction between flow parameters and complex bridge pier is necessary to study to accurately predict the performance of system. In this study, an artificial neural network (ANN) has been developed to predict scour depth around complex bridge pier. ANN model, feed forward back propagation, FFBP, was utilized to estimate the depth of scour hole. 82 experiments have been carried out to collect experimental data. The training and testing experimental data on local scour depth around complex piers are selected from several references. Three categories of input data were used for network training: the first input combination includes cases that pile cap was above the original bed; the second combinations refers to semi buried pile cap, both combinations
File Size : 1,605,502 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 36th Congress - The Hague (2015) FULL PAPERS
Article : THEME 4- WATER ENGINEERING
Date Published : 19/04/2016
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