Sediment transport prediction in sewer pipes during flushing operation

Abstract

This paper presents a novel model for predicting the sediment transport rate during flushing operation in sewers. The model was developed using the Evolutionary Polynomial Regression Multi-Objective Genetic Algorithm (EPR-MOGA) methodology applied to new experimental data collected. Using the new model, a series of design charts were developed to predict the sediment transport rate and the required flushing operation time for several pipe diameters. Accurate results (i.e. sediment transport rates) were obtained when applied to a case study in a combined sewer pipe in Marseille, as reported in the literature. The novelty of the model is the inclusion of the pipe slope, the inflow "dam break" hydrograph, and the sediment properties as explanatory parameters. The new model can be used to predict flushing efficiency and design new flushing cleaning schedules in sewer systems.