Classification of Hydraulic Jump in Rough Beds

Ghorban Mahtabi,Mahesh Pal,Hazi Mohammad Azamathulla,Barkha Chaplot

doi:10.3390/w12082249

Abstract

This paper presents a classification using a decision tree algorithm of hydraulic jump over rough beds based on the approach Froude number, Fr1. Specifically, 581 datasets, from literature, were analyzed. Of these, 280 datasets were for natural rough beds and 301 were for artificial rough beds. The said dataset was divided into four classes based on the energy losses. To compare the performance of the decision tree classifier (J48), a multi-layer neural network (NN) was used. The results suggest an improved performance in terms of classification accuracy by the J48 algorithm in comparison to the NN classifier. Furthermore, the classifier model had only four leaves and achieved an accuracy of 91.56%. Furthermore, classification results showed that the first class (A) of hydraulic jump over the rough beds is approximately similar to that for the smooth bed. Moreover, in the next three classes (B, C, and D), upper values of Fr1 decreased with respect to the smooth bed classes. Lastly, in class D, the upper value of Fr1 reduced to 7.45, which indicates that the shear stress (i.e., the energy loss) grows sharply with increasing Fr1. Put simply, bed roughness effectively increases the energy dissipation with an increase in the Fr1.

Highlights

The hydraulic jump is a natural phenomenon caused by an abrupt change in the open channel flow regime from a supercritical to a subcritical condition
Results indicate that the J48 algorithm provides accurate classification as well as an neural network (NN) classifier with all three datasets
The classification results indicate that two classifiers have produced good classification performance for the overall rough beds

Summary

Introduction

The hydraulic jump is a natural phenomenon caused by an abrupt change in the open channel flow regime from a supercritical to a subcritical condition. This phenomenon is used for energy dissipation that reduces the excess kinetic energy of high velocity flow. Stilling basin is an effective energy dissipator for reducing the exit velocity in the downstream of hydraulic structures such as spillways, drops, and sluice gates [1]. The hydraulic jump formed in a stilling basin (with a smooth bed) has been widely investigated by many researchers and their results have been reported. A jump occurred in a horizontal, rectangular, and smooth channel, which is classified based on the incoming. Four different types of jumps are generally defined, which includes weak jump (1.7 < Fr1 ≤ 2.5), transition or oscillating jump (2.5 < Fr1 ≤ 4.5), steady jump (4.5 < Fr1 ≤ 9), and strong or choppy jump (Fr1 > 9) [2]

Objectives

Methods

Results

Conclusion