Abstract

For transition of a supercritical flow into a subcritical flow in an open channel, a hydraulic jump phenomenon is used. Different shaped channels are used as useful tools in the extra energy dissipation of the hydraulic jump. Accurate prediction of relative energy dissipation is important in designing hydraulic structures. The aim of this paper is to assess the capability of a Kernel extreme Learning Machine (KELM) meta-model approach in predicting the energy dissipation in different shaped channels (i.e., rectangular and trapezoidal channels). Different experimental data series were used to develop the models. The obtained results approved the capability of the KELM model in predicting the energy dissipation. Results showed that the rectangular channel led to better outcomes. Based on the results obtained for the rectangular and trapezoidal channels, the combination of Fr1, (y2-y1)/y1, and W/Z parameters performed more successfully. Also, comparison between KELM and the Artificial Neural Networks (ANN) approach showed that KELM is more successful in the predicting process.

Highlights

  • For transition of a supercritical flow into a subcritical flow in an open channel, a hydraulic jump phenomenon is used

  • Was applied for different models based on flow conditions and geometry of channels and rough elements

  • It was observed that Z/y1 and W/Z parameters increased the models’ efficiency; it could be stated that the height and space of applied elements were important factors in the energy dissipation prediction

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Summary

Introduction

For transition of a supercritical flow into a subcritical flow in an open channel, a hydraulic jump phenomenon is used. Hydraulic jumps can occur downstream of hydraulic structures, such as normal weirs, gates, and ogee spillways. It is considered as rapidly varying flow, and this type of flow regime transformation is associated with severe turbulence and flow energy dissipation [1]. Modeling hydraulic jump characteristics is of great importance since it plays an important role in designing hydraulic structures. Various studies have been done to explain the complex phenomenon of the hydraulic jump and to estimate its characteristics. Finnemore et al stated that the Froude number has significant impact on the characteristics of the hydraulic jump [3].

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