A Novel Equation for Predicting Hydraulic Jump Depth in Converging Channels: Experimental and ANNs-Based Validation

Subject Areas : New Approches in Environmental and Applied Ecology

Iman Rostami Ravari ¹ , Reza Mohammadpour ²

1 -
2 - Department of civil engineering, Es.C., Islamic Azad University, Estahban,

Received: 2025-09-17 Published : 2025-10-26

Keywords: Converging hydraulic jump, Sequent depth ratio, Artificial intelligence, Energy dissipation, ANNs validation,

Abstract :

Hydraulic jump, a critical phenomenon transitioning flow from supercritical to subcritical regimes, plays a pivotal role in energy dissipation and the design of hydraulic structures. This study presents a comprehensive investigation into the characteristics of hydraulic jumps in rectangular converging channels—an area often overlooked due to the complexities of turbulent flow behavior. By extending the classical momentum equation to include the effects of channel convergence and incorporating key geometric parameters, a novel analytical equation is proposed for predicting the sequent depth. The developed model was validated using both experimental data and artificial neural network (ANN)-based predictive modeling. The AI-driven validation confirms the high accuracy of the proposed relationship, aligning well with observed and calculated depth ratios. The findings highlight that the new equation not only improves the understanding of non-uniform flow dynamics but also serves as a reliable tool for optimizing stilling basin design in converging channels. This research bridges analytical modeling and machine learning, marking a significant step forward in modern hydraulic analysis.

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