Sediment transport modeling in deposited bed sewers: unified form of May's equations using the particle swarm optimization algorithm.

May proposed two dimensionless parameters of transport (η) and mobility (Fs) for self-cleansing design of sewers with deposited bed condition. The relationships between those two parameters were introduced in conditional form for specific ranges of Fs, which makes it difficult to use as a practical tool for sewer design. In this study, using the same experimental data used by May and employing the particle swarm optimization algorithm, a unified equation is recommended based on η and Fs. The developed model is compared with original May relationships as well as corresponding models available in the literature. A large amount of data taken from the literature is used for the models' evaluation. The results demonstrate that the developed model in this study is superior to May and other existing models in the literature. Due to the fact that in May's dimensionless parameters more effective variables in the sediment transport process in sewers with deposited bed condition are considered, it is concluded that the revised May equation proposed in this study is a reliable model for sewer design.

[1]  B. Djebedjian,et al.  Integer Discrete Particle Swarm Optimization of Water Distribution Networks , 2014 .

[2]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[3]  Aminuddin Ab. Ghani,et al.  Sediment transport over deposited beds in sewers , 1994 .

[4]  Aminuddin Ab. Ghani Sediment transport in sewers , 1993 .

[5]  Mukand S. Babel,et al.  Non-deposition design criteria for sewers with part-full flow , 2010 .

[6]  Gustavo Perrusquía An experimental study from flume to stream traction in pipe channels , 1993 .

[7]  C. Nalluri,et al.  Sediment transport over fixed deposited beds in sewers — An appraisal of existing models , 1997 .

[8]  Mirali Mohammadi,et al.  On the effect of cross sectional shape on incipient motion and deposition of sediments in fixed bed channels , 2014 .

[9]  Surender Dahiya,et al.  An Efficient Particle Swarm Optimization with Time Varying Acceleration Coefficients to Solve Economic Dispatch Problem with Valve Point Loading , 2012 .

[10]  Idel Montalvo,et al.  Multi-objective particle swarm optimization applied to water distribution systems design: An approach with human interaction , 2010, Math. Comput. Model..

[11]  H. Aksoy,et al.  Artificial neural network and regression models for flow velocity at sediment incipient deposition , 2016 .

[12]  Idel Montalvo,et al.  Particle Swarm Optimization applied to the design of water supply systems , 2008, Comput. Math. Appl..

[13]  Aminuddin Ab. Ghani,et al.  Design options for self-cleansing storm sewers , 1996 .

[14]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[15]  J J Ota,et al.  Particle velocity and sediment transport at the limit of deposition in sewers. , 2013, Water science and technology : a journal of the International Association on Water Pollution Research.

[16]  Hafzullah Aksoy,et al.  Incipient deposition of sediment in rigid boundary open channels , 2015, Environmental Fluid Mechanics.

[17]  Hafzullah Aksoy,et al.  Non-deposition self-cleansing design criteria for drainage systems , 2017 .

[18]  Richard May,et al.  Self-Cleansing Sewer Design Based on Sediment Transport Principles , 2003 .

[19]  Idel Montalvo,et al.  Optimization in water systems: a PSO approach , 2008, SpringSim '08.

[20]  A. Shields,et al.  Application of similarity principles and turbulence research to bed-load movement , 1936 .

[21]  Richard May,et al.  Development of design methodology for self-cleansing sewers , 1996 .