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You are here : eLibrary : IAHR World Congress Proceedings : 36th Congress - The Hague (2015) ALL CONTENT : 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
contains 15 dimensional parameters; and the third combination consists of cases that pile cap
was below the original bed level which contains 8 dimensional parameters. ANN results have
been compared with the results of empirical methods. Sensitivity analysis showed that pile
spacing width, longitudinal extension of pile group from column, and column length have the
least influence on scour depth. While the number of piles in line with flow, transversal
extension of pile cap from column, and pile cap length are the most effective parameters on
complex pier scour in each combination respectively. Based upon an errors and sensitivity
analyses it may be said, the collected data and method of analysis could be reliable to use.
File Size : 499,902 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 36th Congress - The Hague (2015) ALL CONTENT
Article : Water engineering
Date Published : 28/08/2015
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