Nature-inspired algorithms in sanitary engineering: modelling sediment transport in sewer pipes

2021 ◽  
Author(s):  
Mohammad Zounemat-Kermani ◽  
Amin Mahdavi-Meymand ◽  
Reinhard Hinkelmann
Keyword(s):  
Sediment Transport ◽  
Sewer Pipes ◽  
Nature Inspired Algorithms

scholarly journals Decision tree (DT), generalized regression neural network (GR) and multivariate adaptive regression splines (MARS) models for sediment transport in sewer pipes

2019 ◽  
Vol 79 (6) ◽  
pp. 1113-1122 ◽  
Author(s):  
Mir Jafar Sadegh Safari
Keyword(s):  
Sediment Transport ◽  
Regression Models ◽  
Multivariate Adaptive Regression Splines ◽  
Generalized Regression Neural Network ◽  
Deposition Condition ◽  
Regression Splines ◽  
Sewer Pipes ◽  
Adaptive Regression ◽  
Adaptive Regression Splines ◽  
Conventional Regression

Abstract Sediment deposition in sewers and urban drainage systems has great effect on the hydraulic capacity of the channel. In this respect, the self-cleansing concept has been widely used for sewers and urban drainage systems design. This study investigates the bed load sediment transport in sewer pipes with particular reference to the non-deposition condition in clean bed channels. Four data sets available in the literature covering wide ranges of pipe size, sediment size and sediment volumetric concentration have been utilized through applying decision tree (DT), generalized regression neural network (GR) and multivariate adaptive regression splines (MARS) techniques for modeling. The developed models have been compared with conventional regression models available in the literature. The model performance indicators, showed that DT, GR and MARS models outperform conventional regression models. Result shows that GR and MARS models are comparable in terms of calculating particle Froude number and performing better than DT. It is concluded that conventional regression models generally overestimate particle Froude number for the non-deposition condition of sediment transport, while DT, GR and MARS outputs are close to their measured counterparts.

scholarly journals CFD-DEM modelling of sediment transport in sewer systems under steady and unsteady flow conditions

2019 ◽  
Vol 80 (11) ◽  
pp. 2141-2147 ◽  
Author(s):  
Maryam Alihosseini ◽  
Sveinung Sægrov ◽  
Paul Uwe Thamsen
Keyword(s):  
Sediment Transport ◽  
Laboratory Experiments ◽  
Transport Processes ◽  
Experimental Investigations ◽  
Flow Conditions ◽  
Ansys Fluent ◽  
Sewer Pipes ◽  
Rough Bed ◽  
New Methodologies ◽  
Sand And Gravel

Abstract Numerical and experimental investigations were undertaken to study sediment transport under steady flow conditions and under flush waves in sewer pipes. Experiments were carried out with sand and gravel of different size distributions under smooth and rough bed conditions. Moreover, different hydraulic boundary conditions were investigated for flush waves. The numerical part of this study was carried out in the computational fluid dynamics (CFD) software ANSYS Fluent, which is two-way coupled to the Discrete Element Method (DEM) software EDEM. The main focus of this study is to determine if the CFD-DEM coupled method could reasonably predict the behaviour of sediments in sewers and thus be used for studying various features of sediment transport that are not easy to determine in laboratory experiments or in-situ measurements. Furthermore, it is important to replace the traditional empirical approaches developed for fluvial conditions with new methodologies, which are able to consider the high number of variables involved in sediment transport in sewers. The numerical model was validated with laboratory experiments and used to study details of sediment transport processes in sewers.

Sediment transport prediction in sewer pipes during flushing operation

2021 ◽  
pp. 1-14
Author(s):  
Carlos Montes ◽  
Hachly Ortiz ◽  
Sergio Vanegas ◽  
Zoran Kapelan ◽  
Luigi Berardi ◽  
...  
Keyword(s):  
Sediment Transport ◽  
Sewer Pipes ◽  
Transport Prediction

scholarly journals Non-deposition self-cleansing models for large sewer pipes

2020 ◽  
Vol 81 (3) ◽  
pp. 606-621 ◽  
Author(s):  
Carlos Montes ◽  
Sergio Vanegas ◽  
Zoran Kapelan ◽  
Luigi Berardi ◽  
Juan Saldarriaga
Keyword(s):  
Experimental Data ◽  
Sediment Transport ◽  
Prediction Accuracy ◽  
Mean Squared Error ◽  
Percentage Error ◽  
Multiple Models ◽  
Sewer Pipes ◽  
Squared Error ◽  
High Prediction ◽  
The University

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.

Assessment of sediment behaviour in a cunette-shaped sewer section

1996 ◽  
Vol 33 (9) ◽  
pp. 49-59 ◽  
Author(s):  
Michel A. Verbanck
Keyword(s):  
Sediment Transport ◽  
Cross Section ◽  
Theoretical Description ◽  
Design Parameters ◽  
Physical Factors ◽  
Sewer Pipes ◽  
Hydraulic Roughness ◽  
Transport Behaviour ◽  
Shear Turbulence ◽  
Full Knowledge

The accumulation of deposits in sewers causes widespread concerns of either operational or environmental nature. It is believed that a number of sediment-related nuisances can substantially be controlled in adapting the characteristics of sewer pipes as a function of local constraints and circumstances. In particular, key design parameters such as cross-section shape or hydraulic roughness of inner walls are currently selected basing more on empiricism and intuition than on full knowledge of the sediment transport driving processes. A valid track for optimization of these parameters is to run mathematical simulations of the sediment transport behaviour under varying design scenarios. This option, however, supposes that a robust mathematical procedure to compute sediment transport capacity in sewers is available, embracing all primary physical factors of influence. Starting from a theoretical description of shear turbulence suggested by Bagnold (1966), a suspension formula is developed dedicated to the specific sewer flow properties. Applying this formula to the case of a main sewer presenting a composite cross-section allows to illustrate how geometrical discontinuities influence sediment transport characteristics in real conduits.

Predicting non-deposition sediment transport in sewer pipes using Random forest

2021 ◽  
Vol 189 ◽  
pp. 116639
Author(s):  
Carlos Montes ◽  
Zoran Kapelan ◽  
Juan Saldarriaga
Keyword(s):  
Sediment Transport ◽  
Random Forest ◽  
Sewer Pipes

Combination of sensitivity and uncertainty analyses for sediment transport modeling in sewer pipes

2020 ◽  
Vol 35 (2) ◽  
pp. 157-170 ◽  
Author(s):  
Isa Ebtehaj ◽  
Hossein Bonakdari ◽  
Mir Jafar Sadegh Safari ◽  
Bahram Gharabaghi ◽  
Amir Hossein Zaji ◽  
...  
Keyword(s):  
Sediment Transport ◽  
Transport Modeling ◽  
Sewer Pipes ◽  
Uncertainty Analyses

scholarly journals Prediction of non-cohesive sediment transport in circular channels in deposition and limit of deposition states using SVM

2016 ◽  
Vol 17 (2) ◽  
pp. 537-551 ◽  
Author(s):  
Kiyoumars Roushangar ◽  
Roghayeh Ghasempour
Keyword(s):  
Sediment Transport ◽  
Negative Impact ◽  
Dominant Role ◽  
Bedload Transport ◽  
Support Vector ◽  
Complex Nature ◽  
Governing Equations ◽  
Sewer Pipes ◽  
Cohesive Sediment Transport ◽  
Model Approach

Sedimentation in sewer pipes has a negative impact on the performance of sewerage systems. However, due to the complex nature of sedimentation, determining the governing equations is difficult and the results of the available classic models for computing bedload transport rate often differ from each other. This paper focuses on the capability of a support vector machine (SVM) as a meta-model approach for predicting bedload transport in pipes. The method was applied for the deposition and limit of deposition states of sediment transport. Two different scenarios were proposed: in Scenario 1, the input combinations were prepared using only hydraulic characteristics, on the other hand, Scenario 2 was built using both hydraulic and sediment characteristics as model inputs of bedload transport. A comparison between the SVM and the employed classic approaches in predicting sediment transport indicated the supreme performance of the SVM, in which more accurate results were obtained. Also it was found that for estimation of bedload transport in pipes, Scenario 2 led to a more valid outcome than Scenario 1. Based on the sensitivity analysis, parameters Frm and d50/y in the limit of deposition state and Frm in the deposition state had the more dominant role in prediction of bedload discharge in pipes than other parameters.

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