جستجوی مقالات مرتبط با کلیدواژه « water distribution networks » در نشریات گروه « آب و خاک »

Water distribution network analysis is traditionally done under the assumption that the demand requirements are met at all the nodes. In reality, a network could be met with various abnormal and uncertain conditions, resulting in variations at the demand nodes. Softwares such as EPANET 2 analyze a network using demand dependent analysis (DDA). Under pressure deficient conditions, DDA will not give satisfactory results. In such cases pressure-dependent or pressure driven analysis called as node flow analysis (NFA) is required, where outflows at the demand nodes are treated as functions of pressure using node head-flow relationships. Fuzzy analysis helps in understanding how the uncertainty in various independent parameters of water distribution network such as, nodal demands, pipe roughness values, reservoir heads, pipe diameters and so forth will affect the dependent parameters such as pipe velocities, discharges and nodal pressures. The membership functions of dependent parameters are obtained by considering membership functions of uncertain independent parameters. The Impact Table method from literature suggests a repetitive analysis by considering the monotonous relationship between dependent and independent parameters. The Impact Table method was also employed for carrying out fuzzy analysis under pressure deficient condition to obtain fuzzy membership function of nodal outflows. Optimization based methods of fuzzy analysis are more useful when relationship between dependent and independent parameters are non-monotonous.

Optimization based methods of fuzzy analysis are more useful when relationship between dependent and independent parameters are non-monotonous. Genetic algorithm is used in this study for performing fuzzy analysis on three networks by pressure dependent approach. The objective functions which are evaluated are (1) nodal pressures and (2) the actual demand at the nodes under the uncertain conditions. The membership function considered is triangular. The analysis is performed by setting up hydraulic model in the software EPANET and linking it with the MATLAB for performing optimization through an EPANET-MATLAB toolkit. Fuzzy NFA incorporates nodal outflows as additional dependent parameters. The outflows at pressure-deficient nodes are also observed to change monotonically as a result of changing the nodal demands and pipe roughness coefficients. Using this observation of monotonic change, the fuzzy analysis methodology of Gupta and Bhave (2007) is extended to obtain a membership function of available nodal flows under pressure-deficient conditions.The fuzzy NFA procedure has the following steps:Step 1. Carry out a NFA of the network considering normal values of uncertain parameters.Step 2. Change an uncertain parameter to its maximum value keeping other uncertain parameters at their normal value; and obtain the values of dependent parameter. Note the impact of changing an uncertain parameter on the dependent parameter, i.e. whether increasing, decreasing or none. Step 2 is to be repeated for all uncertain parameters.Step 3. To determine the maximum (or minimum) value of the dependent parameters, take an appropriate extreme value of an uncertain parameter based on its impact and carry out the analysis. Step 3 can be repeated for all dependent parameters and for different α-cuts.For validation, two networks were selected from previous researches, and the networks were analyzed with the developed model and WaterNetGen software, and finally the results were compared. Then paid to hydraulic analysis of the water distribution network of Jangal city under uncertain conditions and lack of pressure as a case study.

Fuzzy analysis is the approach adopted in this study to quantify thevagueness of a water distribution network. An optimization model is employed to find out theextremities in the responses of the system, as the relationship between independent and dependentvariable are not necessarily monotonous. The hydraulic system is analyzed by node flow analysis totake care of the head-demand relationships under pressure deficient conditions. As most of the hydraulic simulation software perform analysis considering that demands are met at all the nodes, the results will vary when there is a pressure deficiency in the network. This assessment of network can be incorporated into the better designing of a WDN. The obtained results showed that the proposed model can perform hydraulic simulation well in the condition of lack of pressure. This study has considered only the uncertainties in the nodal demands, but it can be further extended to any input parameter just by considering them as variables in the algorithm and extreme responses can be obtained.

Water distribution networks are critical infrastructure that should be protected against deliberate and accidental attacks. The quality of water is investigated in the treatment plant; however, it can be significantly changed during transmission from the treatment plant to consumers. The contamination entry place is unpredictable and contamination can be entered from several locations simultaneously. Water quality sensors and the pollution warning system can detect the contamination. The alarm system function is depends on the number of sensors installed on the network and their location. In this research, contamination is entered in one or two nodes and the number of sensors installed in the network is one to four. In addition, four objective functions were considered to optimize the locations and the number of sensors. The network was analyzed dynamically. For each sensor placement, the consumed contamination water and the contaminated area are evaluated.  The method was able to identify the best location for the different objective function.

Optimization of water distribution networks, regardless of uncertainties of effective variables in design of network is unrealistic. Therefore, developing method based on uncertainties variables in water distribution network design is necessary. In this research, a model based on simulation-optimization approach (combination of genetic algorithm and EPANET software) with fuzzy variables has been developed. Also, water distribution networks without causing disruption in their Performance with level-1 redundant have been optimized. In this model, fuzzy nodal demands and fuzzy available nodal heads are characterised by triangular membership functions. Furthermore, desirable nodal heads are also considered as fuzzy and relationship between fuzzy available nodal heads and fuzzy desirable nodal heads is used to convert fuzzy constraints to crisp constraints. For validation of model, the program has been implemented for optimization of level-1 redundant water distribution single network with fuzzy demands then paid to the optimization Jangal water distribution network with fuzzy demands (under one pipe failure condition) as a case study. The result of this model shows the cost of optimal design of Level-1 redundant water distribution networks model with fuzzy demands regard of scale of network 30% to 70% is increases due to providing nodal heads to offset the one pipe failure condition from network.

A hydraulic model of water distribution network is successful and reliable if it can simulate real condition by high accuracy. In this paper introduces a new web-based system which called optimal management system of water distribution networks with the goal of calibration of water distribution network based on simple modified particle swarm optimization (SMPSO) in a simple and user friendly way for the experts of the water and wastewater companies. The calibration process in this web-based system is aimed to minimize Mean Absolute Percentage Error criterion (MAPE) between simulated and observed pressures with the Hazen- Williams roughness coefficients as the decision variables. To achieve this purpose, firstly the SMPSO method is investigated to calibrate a benchmark network which the results showed MAPE average has reduced to 0.425, 2.857 and 0.306 percent in the maximum, minimum and fire demand conditions respectively and has increased 0.186 percent just in the normal condition. It is verify that the SMPSO algorithm performs better than the GA. Then the system is used to calculate a real case water network in the normal, maximum, minimum and different demand conditions during the 24 hours which in these condition MAPE values have decreased 5.82,6.20,5.21 and 5.95 respectively, when compared with calibration obtained by consulting company.

A water distribution network (WDN) may not be able to satisfy all required demands when it’s in the pressure deficit mode or under over-loaded demand conditions. Analysis of the network in this mode requires pressure dependent analysis (PDA). Unlike demand driven analysis (DDA), PDA needs an extra equation for every node to relate the nodal demand and the nodal pressure; so it should be solved with the other network’s equations simultaneously. In this paper, based on the Particle Swarm Optimization (PSO) algorithm, a decision support system has been developed by using MATLAB and EPANET for PDA simulation in WDNs. A four-loop network selected from the literature was analyzed using different scenarios and different pressure dependent functions presented by the previous investigations. The results showed that the proposed model (PSO-PDA) was as accurate as the previous ones and provided better convergence. The results of the nodes’ pressure and discharge also indicated minor differences obtained by different PDA functions. However, the differences between the results of PDA and DDA were considerable.

The water supply networks have always been of significance to researchers as a hydraulic system of transferring and distributing water. The pressure gradient is the main reason of water transfer in networks, and in case of non-standard pressure increase, the undesirable phenomenon of leakage occurs in the network. Leakage in urban water distribution networks causes water waste and enormous financial losses. Therefore, there exists the need to manage and minimize the amount of leakage. In this study, a water distribution network is modeled using the potentialities of hydraulic analysis model, the EPANET 2.0, and, by presenting a new model, the leakage location is recognized. In order to do this, we, firstly, entered all the network parameters into the software. Then, the network was analyzed supposing the non-occurrence of leakage, and the amounts of nodal pressures were measured. Moreover, the nodal pressures were estimated by creating a hypothetical leakage in one of the network node and analyzing the network. Finally, the position of laekage was determined by defining the leakage index and comparing it in various nodes. The results show that the suggested method is efficiently capable of predicting the laeakage position in the network so it could safely replace other methods, especially destructive methods used in recognizing the leakage position in the network.

Traditional water distribution system models, which are referred to as demand-driven analysis are normally analyzed under the assumption that water demands at nodes are known and always satisfied, i.e., they are equal to nodal outflows, regardless of the pressure at nodes. Such analysis is valid under normal design conditions. However, in many critical situations such as pipe burst or breakage and fire-fighting demand on demand nodes, the nodal outflows affected by low pressure will decrease. Therefore, network simulation under deficient pressure conditions using conventional demand-driven analysis can cause large deviation from actual situations. In this study, the combination of three pressure-dependent demand (PDD) methods with WaterGems hydraulic model has been used to simulate deficient-network performance. Assessing the performance of three methods proposed was done using two base network and part of the Ilam water distribution network. The results showed that the results of PDD and Abdy Sayyed et al. (2014) methods are close and preferred to very long and Time-consuming relations proposed by researchers, and they yield results just by one-step simulation. These methods respectively provide 82.83 and 82.07 percent of total network demand at the time of breakage in one of the pipes in Ilam water distribution network considering desired pressure equal to 15meters.