Optimization design method for urban sewage collection pipe networks

Tian, Jiandong; He, Gang

doi:10.2166/wst.2020.200

Cited by 3 publications

(4 citation statements)

References 7 publications

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“…The process of urban rainwater confluence is surface–pipe network–discharge–river channel [ 50 ]. In this study, the target region was comprised of medium-sized, economically developed coastal cities in southeast China with reasonably good pipeline network infrastructures [ 51 , 52 ]. Before entering the pipeline network, runoff from rainfall is blocked by green spaces and other low-impact development facilities, thus delaying its entry.…”

Section: Discussionmentioning

confidence: 99%

Response Model for Urban Area Source Pollution and Water Environmental Quality in a River Network Region

Lai

Jie

et al. 2022

IJERPH

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With the development of cities, urban area source pollution has become more severe and a significant source of water pollution. To study the relationship between urban area source pollution and water environmental quality in a river network, this study uses a city in the Yangtze River Delta, China, as an example. The Storm Water Management Model (SWMM) model and the MIKE11 model were combined into a unified modeling framework and used to simulate dynamic changes in the water quality of a river network under light rain, moderate rain, and heavy rain. In the study period, the annual urban area source input loads of potassium permanganate (CODMn), total phosphorus (TP), and ammonia nitrogen were 29.8, 0.9, and 4.8 t, respectively. The influence of light rain on the water quality of the river network was lagging and temporary, and rainfall area pollution was the primary contributor. Under the scenario of moderate rain, overflow from a pipeline network compounded rainfall runoff, resulting in a longer duration of impact on the water quality in the river. Additionally, the water quality in the river course was worse under moderate rain than under light or heavy rain. Under the scenario of heavy rain, rain mainly served a dilutive function. This research can provide support for urban area source pollution control and management.

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Section: Discussionmentioning

confidence: 99%

Response Model for Urban Area Source Pollution and Water Environmental Quality in a River Network Region

Lai

Jie

et al. 2022

IJERPH

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“…At the same time, pump control algorithms are developed with the use of optimisation algorithms, which define the criteria for minimising energy consumption and the operating costs of the water network [ 21 , 22 , 23 ], the number of switching on and off of individual pumps in multi-pump stations to extend their service life [ 24 , 25 , 26 ], and the speed of changes in pump operation to avoid hydraulic impacts in the network, which may cause failures [ 27 ]. It should be noted that similar pump control tasks using optimisation algorithms are also solved in other key facilities of water supply companies, i.e., sewage networks and sewage treatment plants [ 28 , 29 ].…”

Section: Control Of Pumps Of the Water Supply Networkmentioning

confidence: 99%

Control of Pumps of Water Supply Network under Hydraulic and Energy Optimisation Using Artificial Intelligence

Studziński

Ziółkowski

2020

Entropy

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This article presents several algorithms for controlling water supply system pumps. The aim of having control is the hydraulic optimisation of the network, i.e., ensuring the desired pressure in its recipient nodes, and minimising energy costs of network operation. These two tasks belong to the key issues related to the management and operation of water supply networks, apart from the reduction in water losses caused by network failures and ensuring proper water quality. The presented algorithms have been implemented in an Information and Communications Technology (ICT) system developed at the Systems Research Institute of the Polish Academy of Sciences (IBS PAN) and implemented in the waterworks GPW S.A. in Katowice/Poland.

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“…The results prove that the GA-HP is more optimized and effective in designing large sewerage networks compared with the results of the previous studies. Other optimization methods such as cellular automata (CA), iterative mathematical optimization technique, and decomposition-dynamic programming aggregation technique are used to get the minimum total network sewerage network (Zaheri et al 2020;Duque et al 2020;Tian and He 2020). The sewer-storm network design problem was addressed in the previous studies.…”

Section: Introductionmentioning

confidence: 99%

“…So, the speed of GA becomes more serious when the number of variables and constraints increases. To obtain the optimal design for a storm-sewer network, various techniques such as cellular automata (CA), heuristic models, heuristic harmony search optimization algorithm, and large-system secondary decomposition-dynamic programming aggregation methods are employed (Guo et al 2007;Steele et al 2016;Tan et al 2019;Tian and He 2020).…”

Section: Introductionmentioning

confidence: 99%

Hydraulic-based optimization algorithm for the design of stormwater drainage networks

Anwer,

Soliman,

Radwan

2024

Appl Water Sci

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Stormwater drainage networks are designed to reduce the risk of rainwater damage to the served area. The purpose of optimizing a stormwater drainage system is to reduce overall construction costs and to meet hydraulic design requirements. Currently, designs that rely on software or manual calculations are limited by the available time and the designer’s capabilities. In fact, manual optimization for large networks consumes a lot of time and effort, and there is no guarantee that the optimal design is reached, also it is subject to human errors. In recent years, several researchers have focused on creating optimization design algorithms specifically for sewer and storm networks, such as genetic algorithm (GA), linear programming (LP), heuristic programming (HP),…etc. However, these studies were limited to covering one or two design parameters and constraints. Additionally, in some studies, the hydraulic performance of the designed network was not treated in a proper way, especially the water surface profile effects. So, the main objective of the study is to develop an effective hydraulic-based optimization algorithm (HBOA) that can dynamically get the optimal design with minimum total cost for a given storm network layout and meet all hydraulic requirements. To achieve this, a MATLAB code is created and coupled with SewerGEMS software that automatically simulates all expected optimization scenarios based on network hydraulic performance. The HBOA is validated economically and hydraulically using two benchmark examples from the literature. According to the economic validation, the total network cost generated by HBOA was the lowest when compared to the optimization methods found in the literature. During the hydraulic evaluation, it was observed that the optimization algorithm (GA-HP) used in the literature for the benchmark examples does not meet the hydraulic requirements where the networks are flooded, whereas HBOA meets the hydraulic requirements with minimal overall network cost. Also, the HBOA is applied to four real stormwater drainage networks that were already designed, constructed, and optimized manually. The four redesigned real cases using HBOA revealed a cost reduction of about 15% compared to the original designs, while consuming a few hours for the design and optimization processes. Finally, the developed HBOA is a robust, time-efficient, and cost-effective optimization and hydraulic design tool which could be used in the design of stormwater drainage networks with different design constraints with minimal human interference.

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Optimization design method for urban sewage collection pipe networks

Cited by 3 publications

References 7 publications

Response Model for Urban Area Source Pollution and Water Environmental Quality in a River Network Region

Response Model for Urban Area Source Pollution and Water Environmental Quality in a River Network Region

Control of Pumps of Water Supply Network under Hydraulic and Energy Optimisation Using Artificial Intelligence

Hydraulic-based optimization algorithm for the design of stormwater drainage networks

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