جستجوی مقالات مرتبط با کلیدواژه "واسنجی" در نشریات گروه "عمران"

Water distribution systems (WDS) are the crucial component of urban infrastructure that play a critical role in delivering sufficient water to users with acceptable pressure, volume and quality. Occurrence of a pipe failure may interrupt service, undermine system performance and ultimately lead to consumer dissatisfaction. More serious condition occurs when several pipes in the system fail simultaneously. Nowadays, the threat of accidental or man-made disruptions motivates water utilities to plan risk mitigation works and to improve the preparedness for extreme events. Pipe breaks increase with aging infrastructure, natural disasters such as earthquakes and man-made disruptions. Three criteria; reliability, resiliency and vulnerability have been used to assess the performance of the water distribution system (Hashimoto, Stedinger, and Loucks 1982). The resilience capacities are absorptive, adaptive and restorative that a system needs to be able to respond to perceived or real shocks (Francis and Bekera 2014). Butler et al. (2017) defined the resilience in WDSs as “the degree to which the system minimizes level of service failure magnitude over its design life when subject to exceptional conditions”. Failure modes in WDSs can be broadly categorized into structural failure and functional failure (Mugume et al. 2015). Response to pipe failure can indicate system resilience to loss of structural connectivity (Butler et al. 2014). Todini (2000) proposed a technique based upon the definition of resilience index that emulate both reducing the cost and preserving a capability of the system to overcome failures while still satisfying demand and pressure at each node. Diao et al. (2016) proposed the Global Resilience Analysis (GRA) as a methodology that focusses on the response to system failure modes. Using GRA, the whole range of performance strains resulting from any stress magnitude can be evaluated.In GRA, the model of pipe failure mode (stress on the system) is modified by changing the pipe status to closed for three hours during peak consumption (Diao et al., 2016). In this paper, the numerical code of the GRA method for NET3 network is evaluated and the resilience of water distribution network is examined separately from the main transmission lines. Then, the pressure-based algorithm for the above method is assessed. then the resilience of the real water distribution network in Iran is examined. Based on the inquiry from the water and wastewater company, and considering the diameter of the network pipes, the failure time of the pipes in the consumption peak (12-18) is considered to be an average of 6 hours. Finally, the critical network pipes are identified and the resilience analysis of the network is examined if these pipes are protected. - Methodology In this paper, the GRA approach is adopted to evaluate the system resilience under different pipe failure modes (Diao et al. 2016). The possible failure modes were modelled with increasing the stress magnitude and estimating the corresponding strains (Johansson 2007). Different combinations of pipe failure are considered as stress magnitude and ratio of unsupplied demand to total demand is defined as strain magnitude. Due to huge number of possible combinations (a system with N component and m simultaneous failures has ∑n!/m!(n-m)! potential failure scenarios), it is not possible to model every conceivable scenario for each system failure magnitude (Sweetapple et al. 2018). For any given stress magnitude, an appropriate affordable number of failure scenarios must be determined. Where the total number of scenarios (TNS) is determined as follows (Diao et al. 2016). EPANET2 hydraulic solver is used to determine the hydraulic and water quality conditions in a pressurized WDS (Pathirana 2010). As a demand-driven model, EPANET2 determines the nodal pressures by considering the specified demand at nodal points (Rossman 2000). To illustrate actual supplied water to customers in abnormal conditions, the available nodal demand is expressed as a function (Eq. 2) of nodal pressure head (Wagner, Shamir, and Marks 1988). - Results and discussion Figure 4 shows the calibration of code with results (Diao et al. 2016) for the Net3 distribution network. The results of the code above 95% correspond to the results (Diao et al. 2016). In figure 5 the resilience of Net3 for two approaches (i.e., whole network (WN), and network without CRP (NWCRP)) are compared. The GRA showed that Net3 encountered complete failure due to simultaneous failure of the four main CRPs. Whereas excluding these pipes caused the failure of 12 pipes lead to the same results. The maximum and average network supply shortage were 36% and 12% higher than the whole network model. The supply shortage for all combinations of CRP failures in the peak demand period (18-20 pm) is presented in figure 7. In figure 8 the resilience of real water distribution network for three approaches (i.e., network without CRP1 (NWCRP1), and network without CRP2 (NWCRP2)) are compared. If the resilience of the main transmission lines is examined separately from the total distribution network, the resilience of the network will increase in three modes of maximum, average, and minimum by 72, 23, and 14%, respectively. The results showed that if ten critical pipes were protected, network resilience would increase by an average of 20 percent.(fig.9) - Conclusion Resilience analysis is critical to the presentation of emergency schemes in distribution networks before a crisis occurs. Based on resilience analysis, the distribution network can be fully identified and the critical elements of the network can be identified. One of the network components that is considered in resilience analysis is the failure of part or all of the different pipe combinations. In this study, after testing the resilience analysis model in the NET3 study network, the model was implemented for a real water network in Iran. Accordingly, by reinforcement of the main lines, the efficiency of the real network will increase by a maximum of 72%. Because this network has the only major source , with a single failure of the pipes, it reaches 100% of the water supply. The resilience analysis of other network pipes also shows that if the network's ten critical pipes are protected, the network's resilience will increase by an average of 20%.

Leakage in water distribution system is a crucial issue because of problems such as water loss, water pollution, and land subsidence. Current leakage detection methods are usually costly and time-consuming, therefore new methods have been developed based on water networks simulation. In this paper, a new method for identifying the location and amount of leakage in water distribution system based on a two-step Algorithm is introduced. The first (Stepped Algorithm) and second (Firefly Algorithm) steps for determination of leak location and amount of leakage are respectively used which is applicable for even two simultaneous leaks. The proposed method is based on the comparison of the network hydraulic simulation results and some field network data (pressure or flow or their combination). The obtained results for six examples in a looped-water network are presented. The results show that the proposed algorithm is able to locate either one leak or two simultaneous leaks and their leakage values with less than 8% error. The proposed method developed in this paper can be utilized by operators of water supply networks for identifying the position and amount of leaks.

Partial differential equations of continuity and momentum govern the transient flows in pressurized pipes. These equations are numerically analyzed using the method of characteristics that consists of some important uncertainties such as friction loss modeling and wave speed. This work introduces a calibration methodology to estimate precisely the uncertain parameters and, consequently, the numerical modeling results. For this purpose, a transient state is generated by closing the downstream end valve. A numerical model for transient analysis in the pipe is also developed. In that model, four correction coefficients are considered to be calibrated including; pipe roughness, local and convective accelerations in the unsteady friction loss model and wave speed. Afterward, a non linear programming is developed in which the correction coefficients are decision variables. The objective function is defined as the summation of squares of differences of the observed and calculated pressures at the valve location. The problem is then solved using a simple genetic algorithm, and the uncertainties are finally calibrated to the best conditions. The capability of the method is investigated by solving a well-known experimental pipeline. The approach is found easy to use and results are satisfactory.