Artificial Neural Networks for the prediction of the trapping efficiency of a new sewer overflow screening device

Abstract

Some of the major concerns regarding sewer overflows to receiving water bodies include serious environmental, aesthetic and public health problems. Water management authorities are increasingly receiving public complaints that have led engineers to focus on means of retaining the entrained sewer solids within the sewer system during overflow events. During wet weather conditions, sewer overflows to receiving water bodies raise serious concern to environmental and community health concerns. To address these problems, different types of screening devices are used. Moreover, floatable control is preferred by most of the proposed and existing environmental regulations. This requirement triggers the need to research the different types of screening devices and screenings handling systems to select the most appropriate for a particular installation especially at unmanned locations.