The Development of Explicit Equations for Estimating Settling Velocity Based on Artificial Neural Networks Procedure

Abstract

This study proposes seven equations to predict the settling velocity of sediment particles with variations in grain size (d), particle shape factor (SF), and water temperature (T) based on the artificial neural network procedure. The data used to develop the equations were obtained from digitizing charts provided by the U.S. Interagency Committee on Water Resources (U.S-ICWR) and compiled from the measurement data of settling velocity from several sources. The equations are compared to three existing equations available in the literature and then analyzed using graphical and statistical analysis. The simulation results show the proposed equations produce satisfactory results. The proposed equations can predict the settling velocity of natural particle sediments, with diameters ranging between 0.05 mm and 10 mm in water with temperatures between 0 °C and 40 °C, and shape factor SF ranging between 0.5 and 0.95.