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Estimation of current-induced pile groups scour using a rule-based method
Author(s) -
Negin Ghaemi,
Amir EtemadShahidi,
Behzad AtaieAshtiani
Publication year - 2012
Publication title -
journal of hydroinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.654
H-Index - 50
eISSN - 1465-1734
pISSN - 1464-7141
DOI - 10.2166/hydro.2012.175
Subject(s) - pile , soft computing , adaptive neuro fuzzy inference system , artificial neural network , current (fluid) , seabed , engineering , computer science , fuzzy logic , stability (learning theory) , fuzzy inference system , estimation , geotechnical engineering , artificial intelligence , machine learning , geology , fuzzy control system , oceanography , electrical engineering , systems engineering
Scour phenomenon around piles could endanger the stability of the structures placed on them. Therefore, an accurate estimation of the scour depth around piles is very important for engineers. Due to the complexity of the interaction between the current, seabed and pile group; prediction of the scour depth is a difficult task and the available empirical formulas have limited accuracy. Recently, soft computing methods such as Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) have been used for the prediction of the scour depth. However, these methods do not give enough insight into the generated models and are not as easy to use as the empirical formulas. In this study, new formulas are given that are compact, accurate and physically sound. In comparison with the other soft computing methods, this approach is more transparent and robust. Comparison between the developed formulas and previous empirical formulas showed the superiority of the developed ones in terms of accuracy. In addition, the given formulas can be easily used by engineers to estimate the scour depth around pile groups. Moreover, in this study, design factors are given for different levels of acceptable risks, which can be useful for design purposes.Full Tex

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