EVALUATION OF SEDIMENT TRANSPORT IN SEWER USING ARTIFICIAL NEURAL NETWORK

被引:105
作者
Ebtehaj, Isa [1 ]
Bonakdari, Hossein [1 ]
机构
[1] Razi Univ, Dept Civil Engn, Kermanshah, Iran
关键词
self-cleansing; sediment; ANN; sewer; bed-load; SUSPENDED SEDIMENT; PREDICTION; FUZZY; RUNOFF; RIVER; FIELD;
D O I
10.1080/19942060.2013.11015479
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Sedimentation in sewers occurs regularly according to the alternating natural flow. The long term deposit of material in the sewerage systems increases the risk of changes in the sediments and their consolidation and cementation. In particular under low flow conditions, permanent settlement similar to that on the sewer bed alters the nature of velocity and distribution of the boundary shear stress. Consequently, it affects the capacity of sediment transport and the hydraulic resistance of the sewer. The article reviews the application of Artificial Neural Network (ANN) in predicting the sediment transport using the concept of self-cleansing of sewer systems. In comparison with existing methods, the ANN showed acceptable results.
引用
收藏
页码:382 / 392
页数:11
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