Design options for self-cleansing storm sewers

Nalluri, C.; Ghani, Aminuddin Ab

doi:10.2166/wst.1996.0214

Cited by 31 publications

(12 citation statements)

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“…(, ), May (), Alvarez (), El‐Zaemey (), Perrusquía (1992a), Perrusquía (1992b), Perrusquía (), Ab Ghani (), Nalluri, Ab Ghani, and El‐Zaemey (), Nalluri et al. (), Nalluri and Ab Ghani (), Ackers et al. (), Butler, May, and Ackers (), Butler et al.…”

Section: Self‐cleansing Design Based On Small Deposit Criterionunclassified

Self‐cleansing design of sewers: Definition of the optimum deposited bed thickness

Safari

Shirzad

2019

Water Environment Research

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Sediment deposits may influence the performance of the sewer systems. Sediments are the main store of pollutants which causes sewer systems overflows. In order to prevent the deposition of sediment in sewer systems, self‐cleansing design criteria are used. Among various criteria, “self‐cleansing with deposited bed” criterion is found appropriate for designing of large sewers. Allowing small thickness of deposited bed in large sewers decreases the required channel bed slope and construction costs. This study presents a bed load self‐cleansing model established on wide ranges of experimental data. Comparison of developed model with the existing models in the literature shows its higher performance on variety of data sources. Examples for the application of the model are presented, and design graphs and charts for different pipe sizes are proposed. As a result, the optimum deposited bed thickness is found 1%–5% of the pipe diameter; however, 1% is recommended for sewer pipes design. Practitioner points Nondeposition sediment transport condition with a bed deposit criterion is found appropriate for large sewer pipe design. The precision of a model is linked to the ranges of experimental data and parameters used for the models development. The optimum range of deposited bed thickness can be adopted in the range of 1% to 5% of the pipe diameter.

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Section: Self‐cleansing Design Based On Small Deposit Criterionunclassified

Self‐cleansing design of sewers: Definition of the optimum deposited bed thickness

Safari

Shirzad

2019

Water Environment Research

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“…It should be emphasized that this occurs only in part full pipe, because in designing the part full flow, the increase in the integrity of bed roughness and the reduction in the discharge capacity can become a problem, although an added hydraulic gradient can be applied. Nalluri and Ghani (1996) showed that the presence of a sediment deposit at limited depth on the bed of the sewer reduces the slope needed to design for all diameters of the used pipes. The limited depth of the deposit considers the amount of the sediment and the specifications of the flow, and shows the actual conditions of the flow in the wastewater conduit.…”

Section: Design Criteria For Limited Deposit Sediment Transportmentioning

confidence: 99%

“…The use of this limited depth criterion requires an accurate performance and strict maintenance of the system, as the condition is quite close to critical. Nalluri and Ghani (1996) suggested further that if wastewater systems of 1 m deep or greater were to be designed as a deposited bed, they could be designed in an efficient manner, so for the sediment transport in pipes of over 1 m or more in diameter they used the equations (Ghani, 1993) …”

Section: Design Criteria For Limited Deposit Sediment Transportmentioning

confidence: 99%

Design criteria for sediment transport in sewers based on self-cleansing concept

Ebtehaj

Bonakdari

Sharifi

2014

J. Zhejiang Univ. Sci. A

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This study of bed-load transport was undertaken on the basis of laboratory data in two states, i.e., limit of deposition and deposited bed, by using new design criteria, whereby, compared to earlier similar studies, fewer parameters were considered, yet with almost the same or in some cases an even greater level of accuracy. The modified criterion in the new design for transport in the limit of deposition was using only three dimensionless parameters, i.e., Froude number, volumetric concentration of sediment, and relative size of the grain. But the new design criterion applied to the deposited bed case used four dimensionless parameters, i.e., three parameters used for the preliminary case besides the relative thickness of sedimentation. Compared with other known relationships in sediment transport, the produced equations introduced here yield better results than previous studies. With the lessened number of parameters, the results are much easier to obtain.

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“…Numerous experimental and analytical studies have been done to identify which parameters influence sediment transport (Mayerle et al 1991;Nalluri and Ab Ghani 1996;May 2003;Banasiak 2008;Vongvisessomjai et al 2010;Almedeij 2012;Bonakdari and Ebtehaj 2014a). These studies yielded various equations for determining the limiting velocity.…”

Section: Introductionmentioning

confidence: 99%

Design of a fuzzy differential evolution algorithm to predict non-deposition sediment transport

Ebtehaj

Bonakdari

2017

Appl Water Sci

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Since the flow entering a sewer contains solid matter, deposition at the bottom of the channel is inevitable. It is difficult to understand the complex, three-dimensional mechanism of sediment transport in sewer pipelines. Therefore, a method to estimate the limiting velocity is necessary for optimal designs. Due to the inability of gradient-based algorithms to train Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for non-deposition sediment transport prediction, a new hybrid ANFIS method based on a differential evolutionary algorithm (ANFIS-DE) is developed. The training and testing performance of ANFIS-DE is evaluated using a wide range of dimensionless parameters gathered from the literature. The input combination used to estimate the densimetric Froude number (Fr) parameters includes the volumetric sediment concentration (C V ), ratio of median particle diameter to hydraulic radius (d/R), ratio of median particle diameter to pipe diameter (d/D) and overall friction factor of sediment (k s ). The testing results are compared with the ANFIS model and regression-based equation results. The ANFIS-DE technique predicted sediment transport at limit of deposition with lower root mean square error (RMSE = 0.323) and mean absolute percentage of error (MAPE = 0.065) and higher accuracy (R 2 = 0.965) than the ANFIS model and regression-based equations.

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Design options for self-cleansing storm sewers

Cited by 31 publications

References 0 publications

Self‐cleansing design of sewers: Definition of the optimum deposited bed thickness

Self‐cleansing design of sewers: Definition of the optimum deposited bed thickness

Design criteria for sediment transport in sewers based on self-cleansing concept

Design of a fuzzy differential evolution algorithm to predict non-deposition sediment transport

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