Open AccessAn experimental and numerical model for performance evaluation of the new galley design filter bucket for storm networks
Author(s) -
Basim K. Nile,
Waqed H. Hassan,
Karrar A Mohsen
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1067/1/012045
Subject(s) - storm , filter (signal processing) , stormwater , intensity (physics) , sediment , environmental science , geotechnical engineering , hydrology (agriculture) , environmental engineering , soil science , geology , meteorology , engineering , surface runoff , geomorphology , geography , ecology , physics , quantum mechanics , electrical engineering , biology
Storm networks are a major item of civil infrastructure and a significant element of community life. One of the most significant problems facing storm networks is the blockage of pipes, frequently caused by sediments in the sewage system. This study was undertaken to offer a performance evaluation of a new design of gravel filter bucket for storm networks that offers the separation of sediments at different intensities of rainfall and street slopes based on the development of an experimental model. Stormwater with different sediment loads was simulated and samples of filtrate examined with regard to removal efficiency for these particles. A flow-3D numerical model was also developed to investigate the removal efficiency of the gravel filter. The predicted removal efficiency was then validated using experimental data. Assuming proper model validation, numerical models of this type can yield evaluation data with respect to filter removal efficiency for other dimensions and particle sizes of sediment. The results in this case indicated that the efficiency of the gravel filter increased with increases in slope, intensity, and duration. The gravel filter efficiency was 61% at a low intensity of rainfall and 90% at a high intensity of rainfall, while the results also showed 88% and 63% efficiency for the maximum and minimum diameter sediments, respectively. In terms of validation, the numerical model was compared with a statistical equation to calculate the filter efficiency ( E f ), with the use of an SPSS model to estimate the R 2 value, which was 0.88.