Wastewater Collection Systems

Vallabhaneni, Srinivas

doi:10.2175/106143017x15023776270205

Cited by 2 publications

(2 citation statements)

References 3 publications

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“…Due to expansion of urbanization, sewer networks have become essential components of these infrastructures. Therefore, different sewer system collections have been designed (Vallabhaneni, 2017). However, the construction and operation of sewer networks involve huge cost in which it acts as a limiting factor for construction of these networks.…”

Section: Introductionmentioning

confidence: 99%

Hybridizing ant colony optimization algorithm with nonlinear programming method for effective optimal design of sewer networks

Moeini

Afshar

2019

Water Environment Research

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The ant colony optimization algorithm (ACOA) is hybridized with nonlinear programming (NLP) for the optimal design of sewer networks. The resulting problem is a highly constrained mixed integer nonlinear problem (MINLP) presenting a challenge even to the modern heuristic search methods. In the proposed hybrid method, The ACOA is used to determine pipe diameters while the NLP is used to determine the pipe slopes of the network by proposing two different formulations. In the first formulation, named ACOA‐NLP1, a penalty method is used to satisfy the problem constraints while in the second one, named ACOA‐NLP2, the velocity and flow depth constraints are expressed in terms of the slope constraints which are easily satisfied as box constraint of the NLP solver leading to a considerable reduction of the search space size. In addition, the assumption of minimum cover depth at the network inlets is used to calculate the nodal cover depths and the pump and drop heights at the network nodes, if required, leading to a complete solution. The total cost of the constructed solution is used as the objective function of the ACOA, guiding the ant toward minimum cost solutions. Proposed hybrid methods are used to solve three test examples, and the results are presented and compared with those produced by a conventional application of ACOA. The results indicate the effectiveness and efficiency of the proposed formulations and in particular the ACOA‐NLP2 to optimally solve the sewer network design optimization problems. Practitioner points ACOA is hybridized with NLP for the effective optimal design of sewer networks. Here, ACOA is used to determine pipe diameters and NLP is used to determine the network pipe slopes with predefined pipe diameters. In ACOA‐NLP1, a penalty method is used to enforce the problem constraints. In ACOA‐NLP2, velocity and flow depth constrains are expressed in terms of slope constraint.

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Section: Introductionmentioning

confidence: 99%

Hybridizing ant colony optimization algorithm with nonlinear programming method for effective optimal design of sewer networks

Moeini

Afshar

2019

Water Environment Research

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“…Sewer system design has several aspects to be considered (Vallabhaneni, 2017(Vallabhaneni, , 2018) that among those, cost optimization of sewer system design (Brand & Ostfeld, 2011;Rep, Kompare, Rosˇ, & Kravanja, 2008) and sedimentation (Camp, 1946;Walski, Edwards, Helfer, & Whitman, 2009) have attracted interest of many researchers. Self-cleansing design of sewer systems is a reliable way for solving the sedimentation problems.…”

Section: Introductionmentioning

confidence: 99%

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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Wastewater Collection Systems

Cited by 2 publications

References 3 publications

Hybridizing ant colony optimization algorithm with nonlinear programming method for effective optimal design of sewer networks

Hybridizing ant colony optimization algorithm with nonlinear programming method for effective optimal design of sewer networks

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

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