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Amen, K., M. R, Y. (2009). PREDICTION OF SCOUR DEPTH AROUND BRIDGE PILES USING ARTIFICIAL NEURAL NETWORKS. JES. Journal of Engineering Sciences, 37(No 2), 257-268. doi: 10.21608/jesaun.2009.121211
K. A. Amen; Yasser M. R. "PREDICTION OF SCOUR DEPTH AROUND BRIDGE PILES USING ARTIFICIAL NEURAL NETWORKS". JES. Journal of Engineering Sciences, 37, No 2, 2009, 257-268. doi: 10.21608/jesaun.2009.121211
Amen, K., M. R, Y. (2009). 'PREDICTION OF SCOUR DEPTH AROUND BRIDGE PILES USING ARTIFICIAL NEURAL NETWORKS', JES. Journal of Engineering Sciences, 37(No 2), pp. 257-268. doi: 10.21608/jesaun.2009.121211
Amen, K., M. R, Y. PREDICTION OF SCOUR DEPTH AROUND BRIDGE PILES USING ARTIFICIAL NEURAL NETWORKS. JES. Journal of Engineering Sciences, 2009; 37(No 2): 257-268. doi: 10.21608/jesaun.2009.121211

PREDICTION OF SCOUR DEPTH AROUND BRIDGE PILES USING ARTIFICIAL NEURAL NETWORKS

Article 1, Volume 37, No 2, March and April 2009, Page 257-268  XML PDF (685.56 K)
Document Type: Research Paper
DOI: 10.21608/jesaun.2009.121211
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Authors
K. A. Amen; Yasser M. R
Lecturer of irrigation, water construction, and water resources, Civil Engineering Dept, Assiut university, Assiut, Egypt
Abstract
The safe and economical design of bridge piles requires prediction of the maximum expected depths of scour of the stream bed around them. Scour at bridge piles may be defined as a local lowering in the bed elevation around the piles. A study of the local scour at bridge piles groups was experimentally and mathematically investigated. The case of six piles having the same diameter aligned with the flow direction in two rows altering the separation distance between the centerline of the three piles was established. The aim of this study is the investigation of the preferable separation distance between three piles to reduce scour around them to its minimum value. Artificial Neural Network (ANN) prediction models are more efficient in predictions models once they are trained from examples or patterns. These types of ANN models need large amount of data which should be at hand before thinking to develop such models. In this paper, the capability of ANN model to predict the maximum scour depth around bridge piles is investigated.
Main Subjects
Civil Engineering: structural, Geotechnical, reinforced concrete and steel structures, Surveying, Road and traffic engineering, water resources, Irrigation structures, Environmental and sanitary engineering, Hydraulic, Railway, construction Management.
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