Vishwakarma, Bharat Kumar (2018) *Modelling of Kinetic Energy and Momentum Correction Coefficients in Straight, Meandering and Braided Channel.* MTech thesis.

PDF Restricted to Repository staff only 2828Kb |

## Abstract

The study of meandering channel is quite different from simple straight channels. In simple straight channel pressure distribution for entire length of channel is straight forward, but in meandering channel the additional pressure is introduce due to centrifugal forces on the water particles. Due to which the velocity coefficients (Kinetic energy correction coefficient and momentum correction coefficient) affected by the centrifugal force.

The study performed for a meandering channel with sinuosity 4.1 and 110 and straight channel with similar cross-section for different discharges and channel conditions e.g. smooth and rough. The Length of the channel is divided into 13 sections with equal angle of 18.33 degree from one bend-apex section to next bend-apex. In meandering channel study at single section is not sufficient to define the channel characteristics because at every section radius of curvature is changed and due to centrifugal action of force the addition force on water particle is variable.In this research work velocity distribution, depth averaged velocity distribution and the velocity coefficients are changed in the lateral direction along the channel length for meandering channel and an artificial neural network (ANN) model is developed for validation of results for meandering channel.The variation of velocity coefficients in lateral direction is given also the comparison in those coefficients for smooth and rough channel is discussed.For the modelling of these coefficients some non-dimensional geometricand flow parameters are used (Aspect ratio, radius of curvature to top width ratio, angle of divergence, Reynolds’s number and Froude number).

Item Type: | Thesis (MTech) |
---|---|

Uncontrolled Keywords: | Kinetic Energy and Momentum Correction coefficients; Straight Channel; Meandering channel; Artificial neural network |

Subjects: | Engineering and Technology > Civil Engineering > Water Resources Engineering |

Divisions: | Engineering and Technology > Department of Civil Engineering |

ID Code: | 9562 |

Deposited By: | IR Staff BPCL |

Deposited On: | 01 Apr 2019 18:03 |

Last Modified: | 01 Apr 2019 18:03 |

Supervisor(s): | Khatua, K. K. |

Repository Staff Only: item control page