June 22, 2024
Abbas Rezaei

Abbas Rezaei

Academic rank: Assistant professor
Address:
Education: Ph.D in Electrical engineering
Phone: 083-38305001
Faculty: Faculty ofٍٍ Electrical Engineering

Research

Title
Dam break flow solution using artificial neural network
Type Article
Keywords
Artificial neural network Dam break flow Shock waves Shock dominated flow Saint-Venant equations
Researchers Omid Seyedashraf، Abbas Rezaei، Ali Akbar Akhtari

Abstract

The ability of a mathematical model to simulate the dam break shock-wave and rarefaction wave propagation is beneficial in the context of modeling shock dominated engineering problems. In this study, a novel technique based on artificial neural network (ANN) along with an equation is proposed and detailed for the solution of the one-dimensional dam break problems without source terms. The research is motivated by the fact that the classic numerical models show severe oscillations in the results, besides; all the existing analytical solutions are complex piecewise functions. Accordingly, a quick solution with a single equation and smooth results can be helpful for analyzing the problem. The model is developed with five parameters consisting the channel length, upstream and downstream water depths, time, and the distance factors as the input data, while the water depths and flow velocities are considered as the outputs. The model is well validated against several numerical and analytical solutions. Findings indicate that the ANN is capable of simulating the dam break flow problem satisfactorily and that the proposed model has outperformed the classical numerical results while its CPU time is one-third that of the numerical scheme