Non-deposition self-cleansing models for large sewer pipes

Abstract

Multiple models from the literature and experimental datasets have been developed and collected to predict sediment transport in sewers. However, all these models were developed for smaller sewer pipes, i.e. using experimental data collected on pipes with diameters smaller than 500 mm. To address this issue, new experimental data were collected on a larger, 595 mm pipe located in a laboratory at the University of los Andes. Two new self-cleansing models were developed using this dataset. Both models predict the sewer self-cleansing velocity for the cases of non-deposition with and without deposited bed. The newly developed and existing models were then evaluated and compared on the basis of the most recently collected and previously published datasets. Models were compared in terms of prediction accuracy measured by the root mean squared error and mean absolute percentage error. The results obtained show that in the existing literature, self-cleansing models tend to be overfitted, i.e. have a rather high prediction accuracy when applied to the data collected by the authors, but this accuracy deteriorates quickly when applied to the datasets collected by other authors. The newly developed models can be used for designing both small and large sewer pipes with and without deposited bed condition.

Sediment transport modeling in non-deposition with clean bed condition using different tree-based algorithms

“…The performances of two tree-based algorithms, M5RT and M5RGT, are compared by means of the different statistical error measurement criteria of R 2 , VAF, RMSE, NASH and a10-index in Table 5. Performance of M5RT and M5RGT models recommended in this study are examined in comparison to four empirical equations of [2,12,16,17,34]. [12 and 16] equations are selected due to their credibility as reported in [39].…”

“…[12 and 16] equations are selected due to their credibility as reported in [39]. Furthermore, recently reported equations of [2,17,34] are used for model performance evaluation. The results showed that M5RGT is slightly superior to M5RT, in terms of different statistical performance criteria.…”

“…Thus, the use of data from [18] makes this study more reliable in obtaining experimental data with a variety of cross-sectional shapes, with experiments performed in trapezoidal, circular, U-shape, rectangular and V-shape bottom channels. Also [17], who used a large-diameter (595 mm) circular cross-sectional channel, makes this study more reliable than the models in the literature. The ranges of data sources are given in Table 2.…”

“…In the case of regression equations, a significant scatter has been seen, showing their deficiency in accurate sediment transport prediction. The equations of [12,16,17] generate considerable overestimation, while the equation of [2] shows a slight underestimation.…”

“…[16] examined the Camp approach to sewer design and showed that the flow velocity was greatly overestimated. Experiments were carried out in a large pipe, and new self-cleansing models were recommended by [17]. [2] utilized [18] experimental data conducted in five different cross-section channels of rectangular, trapezoidal, V-bottom and Ushape and developed a self-cleansing model considering channel cross-section shape.…”