Optimal Size and Placement of Water Hammer Protective Devices in Water Conveyance Pipelines

Yazdi, Jafar; Hokmabadi, A.; Ghazizadeh, Mohammadreza Jalili

doi:10.1007/s11269-018-2120-4

Cited by 24 publications

(9 citation statements)

References 24 publications

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“…There are many textbooks and scientific papers in the literature that provide a detailed description of GPR [22], SVM [23,24], neural networks, and their variants [25] in terms of both theory and application. Hence, in this paper, only a brief description of the applied techniques is given.…”

Section: Methodsmentioning

confidence: 99%

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Assessment of Machine Learning Techniques for Monthly Flow Prediction

Alizadeh

Yazdi

Kim

et al. 2018

Water

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Monthly flow predictions provide an essential basis for efficient decision-making regarding water resource allocation. In this paper, the performance of different popular data-driven models for monthly flow prediction is assessed to detect the appropriate model. The considered methods include feedforward neural networks (FFNNs), time delay neural networks (TDNNs), radial basis neural networks (RBFNNs), recurrent neural network (RNN), a grasshopper optimization algorithm (GOA)-based support vector machine (SVM) and K-nearest neighbors (KNN) model. For this purpose, the performance of each model is evaluated in terms of several residual metrics using a monthly flow time series for two real case studies with different flow regimes. The results show that the KNN outperforms the different neural network configurations for the first case study, whereas RBFNN model has better performance for the second case study in terms of the correlation coefficient. According to the accuracy of the results, in the first case study with more input features, the KNN model is recommended for short-term predictions and for the second case with a smaller number of input features, but more training observations, the RBFNN model is suitable.

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Section: Methodsmentioning

confidence: 99%

“…The main steps of this algorithm are briefly described in the following section. The details of the SVR algorithm can be found in [23,24].…”

Section: Svrmentioning

confidence: 99%

Assessment of Machine Learning Techniques for Monthly Flow Prediction

Alizadeh

Yazdi

Kim

et al. 2018

Water

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“…According to the studies on water transmission pipelines, designers typically use pressure control equipment like air valves and surge tanks (Triki 2017;Karney and McInnis 1992;Vereide et al 2016). The optimal location of the protective equipment of the transmission pipeline and water supply network was investigated by Yazdi et al (2019). More specifically, Zhang et al (2014) and Wan & Zhang (2018) conducted some studies on the risk assessment of long water transmission pipelines based on modern methods of controlling pressure surges using surge tanks.…”

Section: Introductionmentioning

confidence: 99%

Numerical modeling of water hammer in long water transmission pipeline

2021

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In the present study, a water transmission pipeline under steady conditions is modeled followed by examining the transient flow created by the failure of pumps in the pipeline. This pipeline is 31 km from the water transmission pipeline of Kerman, Iran. The software analysis results were compared with those of a numerical model for a laboratory test to validate transient flow modeling. While transient flows are created by pump failure, various areas of the water transmission pipelines will be affected by the transient waves produced. Long water transmission pipelines, usually large in diameter and flow rate, will pose problems in the negative pressure phase. The negative pressure causes threatening problems like water column separation and cavitation. The results indicated that using equipment like air valves when the pumps fail alone does not have the appropriate efficiency in eliminating the hazards in the water transmission pipelines. More examination showed that installing equipment like water flow feed and hydropneumatic tanks along the pipeline length in the right places prevents the negative pressure created and the pipeline risk significantly reduces.

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“…The pipeline system and pump units can be seriously damaged when the separated columns rejoin (Simpson & Bergant 1994;Kim et al 2014). To date, surge tanks, oneway surge tanks, air valves and air vessels have been used to relieve these problems (Duan et al 2010;Chaudhry 2014;Sun et al 2016;Yazdi et al 2019). However, the setting of surge tanks and one-way surge tanks is restricted by terrain conditions.…”

Section: Introductionmentioning

confidence: 99%

Optimal volume selection of air vessels in long-distance water supply systems

Shi

Zhang

et al. 2021

Journal of Water Supply: Research and Technology-Aqua

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The use of air vessels is an effective measure to control water hammers, and its volume selection has a certain blindness. This paper aims to reveal the surge wave characteristics and provide design guidelines for air vessels in long-distance water supply systems. First, the analytical formulas of water-level oscillations in the air vessel are derived based on the Krylov–Bogoliubov–Mitropolsky method. Then, an optimization model is constructed for selecting the optimal volume of the air vessels. Finally, the validation of the analytical formulas and the optimization of the model are conducted through two actual projects. The results show that the calculation error of the analytical formulas can be controlled within a very small range, and the process of selecting air vessel volume can be simplified with the provided model. In addition, increasing the air chamber height within its range can reduce the volume of air vessels with the same protection requirements. The optimization analysis results of the air vessel can provide guidance and reference for the design of actual projects.

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Optimal Size and Placement of Water Hammer Protective Devices in Water Conveyance Pipelines

Cited by 24 publications

References 24 publications

Assessment of Machine Learning Techniques for Monthly Flow Prediction

Assessment of Machine Learning Techniques for Monthly Flow Prediction

Numerical modeling of water hammer in long water transmission pipeline

Optimal volume selection of air vessels in long-distance water supply systems

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