5 resultados para DRAIN-LEAKAGE GIDL

em CUNY Academic Works


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The article reviews the modelling of District Metered Areas (DMAs) with relatively high leakage rate. As a generally recognised approach in modelling of leakage does not exist, modelling of leakage by enginners and other researchers usually takes place by dividing the whole leakage rate evenly to all available nodes of the model. In this article, a new methodology is proposed to determine the nodal leakage by using a hydraulic model. The proposed methodology takes into consideration the IWA water balance methodology, the Minimum Night Flow (MNF) analysis, the number of connections related to each node and the marerial of pipes. In addition, the model is illustrated by a real case study, as it was applied in Kalipoli’s DMA. Results show that the proposed model gives reliable results.

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When an accurate hydraulic network model is available, direct modeling techniques are very straightforward and reliable for on-line leakage detection and localization applied to large class of water distribution networks. In general, this type of techniques based on analytical models can be seen as an application of the well-known fault detection and isolation theory for complex industrial systems. Nonetheless, the assumption of single leak scenarios is usually made considering a certain leak size pattern which may not hold in real applications. Upgrading a leak detection and localization method based on a direct modeling approach to handle multiple-leak scenarios can be, on one hand, quite straightforward but, on the other hand, highly computational demanding for large class of water distribution networks given the huge number of potential water loss hotspots. This paper presents a leakage detection and localization method suitable for multiple-leak scenarios and large class of water distribution networks. This method can be seen as an upgrade of the above mentioned method based on a direct modeling approach in which a global search method based on genetic algorithms has been integrated in order to estimate those network water loss hotspots and the size of the leaks. This is an inverse / direct modeling method which tries to take benefit from both approaches: on one hand, the exploration capability of genetic algorithms to estimate network water loss hotspots and the size of the leaks and on the other hand, the straightforwardness and reliability offered by the availability of an accurate hydraulic model to assess those close network areas around the estimated hotspots. The application of the resulting method in a DMA of the Barcelona water distribution network is provided and discussed. The obtained results show that leakage detection and localization under multiple-leak scenarios may be performed efficiently following an easy procedure.

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In the UK, urban river basins are particularly vulnerable to flash floods due to short and intense rainfall. This paper presents potential flood resilience approaches for the highly urbanised Wortley Beck river basin, south west of the Leeds city centre. The reach of Wortley Beck is approximately 6km long with contributing catchment area of 30km2 that drain into the River Aire. Lower Wortley has experienced regular flooding over the last few years from a range of sources, including Wortley Beck and surface and ground water, that affects properties both upstream and downstream of Farnley Lake as well as Wortley Ring Road. This has serious implications for society, the environment and economy activity in the City of Leeds. The first stage of the study involves systematically incorporating Wortley Beck’s land scape features on an Arc-GIS platform to identify existing green features in the region. This process also enables the exploration of potential blue green features: green spaces, green roofs, water retention ponds and swales at appropriate locations and connect them with existing green corridors to maximize their productivity. The next stage is involved in developing a detailed 2D urban flood inundation model for the Wortley Beck region using the CityCat model. CityCat is capable to model the effects of permeable/impermeable ground surfaces and buildings/roofs to generate flood depth and velocity maps at 1m caused by design storm events. The final stage of the study is involved in simulation of range of rainfall and flood event scenarios through CityCat model with different blue green features. Installation of other hard engineering individual property protection measures through water butts and flood walls are also incorporated in the CityCat model. This enables an integrated sustainable flood resilience strategy for this region.

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Demands are one of the most uncertain parameters in a water distribution network model. A good calibration of the model demands leads to better solutions when using the model for any purpose. A demand pattern calibration methodology that uses a priori information has been developed for calibrating the behaviour of demand groups. Generally, the behaviours of demands in cities are mixed all over the network, contrary to smaller villages where demands are clearly sectorised in residential neighbourhoods, commercial zones and industrial sectors. Demand pattern calibration has a final use for leakage detection and isolation. Detecting a leakage in a pattern that covers nodes spread all over the network makes the isolation unfeasible. Besides, demands in the same zone may be more similar due to the common pressure of the area rather than for the type of contract. For this reason, the demand pattern calibration methodology is applied to a real network with synthetic non-geographic demands for calibrating geographic demand patterns. The results are compared with a previous work where the calibrated patterns were also non-geographic.

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Most of water distribution systems (WDS) need rehabilitation due to aging infrastructure leading to decreasing capacity, increasing leakage and consequently low performance of the WDS. However an appropriate strategy including location and time of pipeline rehabilitation in a WDS with respect to a limited budget is the main challenge which has been addressed frequently by researchers and practitioners. On the other hand, selection of appropriate rehabilitation technique and material types is another main issue which has yet to address properly. The latter can affect the environmental impacts of a rehabilitation strategy meeting the challenges of global warming mitigation and consequent climate change. This paper presents a multi-objective optimization model for rehabilitation strategy in WDS addressing the abovementioned criteria mainly focused on greenhouse gas (GHG) emissions either directly from fossil fuel and electricity or indirectly from embodied energy of materials. Thus, the objective functions are to minimise: (1) the total cost of rehabilitation including capital and operational costs; (2) the leakage amount; (3) GHG emissions. The Pareto optimal front containing optimal solutions is determined using Non-dominated Sorting Genetic Algorithm NSGA-II. Decision variables in this optimisation problem are classified into a number of groups as: (1) percentage proportion of each rehabilitation technique each year; (2) material types of new pipeline for rehabilitation each year. Rehabilitation techniques used here includes replacement, rehabilitation and lining, cleaning, pipe duplication. The developed model is demonstrated through its application to a Mahalat WDS located in central part of Iran. The rehabilitation strategy is analysed for a 40 year planning horizon. A number of conventional techniques for selecting pipes for rehabilitation are analysed in this study. The results show that the optimal rehabilitation strategy considering GHG emissions is able to successfully save the total expenses, efficiently decrease the leakage amount from the WDS whilst meeting environmental criteria.