<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml">Incipient motion is the critical condition at which bed particles begin to move. Existing relationships for incipient motion prediction do not consider the effect of seepage. Incipient motion design of an alluvial channel affected from seepage requires the information about five basic parameters, i.e., particle size <italic>d</italic>, water depth <italic>y</italic>, energy slope <italic>Sf</italic>, seepage velocity <italic>vs</italic> and average velocity <italic>u.</italic> As the process is extremely complex, getting deterministic or analytical form of process phenomena is too difficult. Data mining technique, which is particularly useful in modeling processes about which adequate knowledge of the physics is limited, is presented here as a tool complimentary to model the incipient motion condition of alluvial channel at seepage. This article describes the radial basis function (RBF) network to predict the seepage velocity vs and average velocity <italic>u</italic> based on experimental data of incipient condition. The prediction capability of model has been found satisfactory and methodology to use the model is also presented. It has been found that model predicts the phenomena very well. With the help of the RBF network, design curves have been presented for designing the alluvial channel when it is affected by seepage.</abstract>

Incipient motion is the critical condition at which bed particles begin to move. Existing relationships for incipient motion prediction do not consider the effect of seepage. Incipient motion design of an alluvial channel affected from seepage requires the information about five basic parameters, i.e., particle size d, water depth y, energy slope Sf, seepage velocity vs and average velocity u. As the process is extremely complex, getting deterministic or analytical form of process phenomena is too difficult. Data mining technique, which is particularly useful in modeling processes about which adequate knowledge of the physics is limited, is presented here as a tool complimentary to model the incipient motion condition of alluvial channel at seepage. This article describes the radial basis function (RBF) network to predict the seepage velocity vs and average velocity u based on experimental data of incipient condition. The prediction capability of model has been found satisfactory and methodology to use the model is also presented. It has been found that model predicts the phenomena very well. With the help of the RBF network, design curves have been presented for designing the alluvial channel when it is affected by seepage.

Radial Basis Function Network Based Design of Incipient Motion Condition of Alluvial Channels with Seepage

Department of Civil Engineering, Indian Institute of Technology, Guwahati, India

Department of Civil Engineering, Indian Institute of Science, Bangalore, India

Journal of Hydrology and Hydromechanics

Incipient motion is the critical condition at which bed particles begin to move. Existing relationships for incipient motion prediction do not consider the...

Radial Basis Function Network Based Design of Incipient Motion Condition of Alluvial Channels with Seepage

Published Online: Jun 25, 2010

Page range: 102 - 113

DOI: https://doi.org/10.2478/v10098-010-0010-4

Keywords
začínajúci pohyb, RBF, transport sedimentov, Shieldsov diagram

This content is open access.

Radial Basis Function Network Based Design of Incipient Motion Condition of Alluvial Channels with Seepage

Published Online: Jun 25, 2010

Page range: 102 - 113

DOI: https://doi.org/10.2478/v10098-010-0010-4

Keywordszačínajúci pohyb, RBF, transport sedimentov, Shieldsov diagram

This content is open access.

Keywords
začínajúci pohyb, RBF, transport sedimentov, Shieldsov diagram