1,720,977 research outputs found
Optimal positioning of water quality sensors in water distribution networks: comparison of numerical and experimental results
Full text linkIn the water distribution networks, a deliberate or accidental contamination causes loss of water
quality; the implementation of a real-time sensor network is essential to promptly detect the event of
contamination. To achieve the optimum positioning of the probes, to reduce the cost of the
instrumentation and maintenance, and obtaining, at the same time, a reliable monitoring of the
system, optimization techniques are widely applied.
In the present study, a numerical optimisation approach was compared with the results of an
experimental campaign. The optimization problem is formulated in accordance with literature stateof-
the-art, using the genetic algorithm NSGA-II coupled with a hydraulic simulator. The results
were tested and verified using a looped laboratory distribution network, equipped with a real-time
monitoring water quality system, which allows to run contamination experiments in a controlled
environment
Urban Water Networks Modelling and Monitoring, Volume II
No full textInnovation in information and communication technologies has greatly impacted the production of goods and service provision [...
Improving the Performance of Bayesian Decision Networks for Water Quality Sensor Deployment in UDNs through a Reduced Search Domain
No full textThe contamination of urban drainage systems (UDNs) represents a serious threat to the environment and public health. Treatment plants are often inefficient in their removal, making timely identification and isolation interventions necessary. In this regard, various monitoring strategies have been proposed, among which the Bayesian decision network (BDN) approach has proven to be very effective, although also very complex. To reduce their level of complexity, it is usual to optimize them using approaches based on preconditioning. The present work fits into this framework by proposing a two-phase strategy aimed at identifying an optimal monitoring system for UDNs. The first phase involves reducing the search domain of the system using a complex network theory (CNT) topological metric adapted to infrastructure systems; the second phase implements the Bayesian approach to the new search space to optimize the position of the sensors in the network. The results are promising and reveal that the strategy could be valuable to water utilities
LCA Methodology for the Quantification of the Carbon Footprint of the Integrated Urban Water System
No full textIn integrated urban water systems, energy consumption, and consequently the amount of produced CO2, depends on many environmental, infrastructural, and management factors such as supply water quality, on which treatment complexity depends, urban area orography, water systems efficiency, and maintenance levels. An important factor is related to the presence of significant water losses, which result in an increase in the supply volume and therefore a higher energy consumption for treatment and pumping, without effectively supplying users. The current European environmental strategy is committed to sustainable development by generating action plans to improve the environmental performance of products and services. The analysis of carbon footprints is considered one such improvement, allowing for the evaluation of the environmental impact of single production phases. Using this framework, the aim of the study is to apply a Life Cycle Assessment (LCA) methodology to quantify the carbon footprint of an overall integrated urban water system referring to ISO/TS 14067 (2013). This methodology uses an approach known as “cradle to grave” and presumes to conduct an objective assessment of product units, balancing energy, and matter flows along the production process. The methodology was applied to a real case study, i.e., the integrated urban water system of the Palermo metropolitan area in Sicily (Italy). Each process in the system was characterized and globally evaluated from the point of view of water loss, energy consumption, and CO2 production, and some mitigation strategies are proposed and evaluated to reduce the energy consumption and, consequently, the environmental impact of the system.</jats:p
Strategies for Improving Optimal Positioning of Quality Sensors in Urban Drainage Systems for Non-Conservative Contaminants
No full textIn the urban drainage sector, the problem of polluting discharges in sewers may act on the proper functioning of the sewer system, on the wastewater treatment plant reliability and on the receiving water body preservation. Therefore, the implementation of a chemical monitoring network is necessary to promptly detect and contain the event of contamination. Sensor location is usually an optimization exercise that is based on probabilistic or black-box methods and their efficiency is usually dependent on the initial assumption made on possible eligibility of nodes to become a monitoring point. It is a common practice to establish an initial non-informative assumption by considering all network nodes to have equal possibilities to allocate a sensor. In the present study, such a common approach is compared with different initial strategies to pre-screen eligible nodes as a function of topological and hydraulic information, and non-formal ‘grey’ information on the most probable locations of the contamination source. Such strategies were previously compared for conservative xenobiotic contaminations and now they are compared for a more difficult identification exercise: the detection of nonconservative immanent contaminants. The strategies are applied to a Bayesian optimization approach that demonstrated to be efficient in contamination source location. The case study is the literature network of the Storm Water Management Model (SWMM) manual, Example 8. The results show that the pre-screening and ‘grey’ information are able to reduce the computational effort needed to obtain the optimal solution or, with equal computational effort, to improve location efficiency. The nature of the contamination is highly relevant, affecting monitoring efficiency, sensor location and computational efforts to reach optimality
Optimal Deployment of the Water Quality Sensors in Urban Drainage Systems
No full textIn the water sector, the problem of pollution-source identification was mainly investigated regarding pressurized distribution networks, with respect to sewers. Even if the Water Framework Directive 2000/60/EC and equivalent law-making bodies in many countries introduce the principle that the polluter pays, it is asking the water manager to detect the most pollutant discharges in sewers. In previous studies, a probabilistic approach to positioning water quality sensors in urban drainage networks shows the progressive increase in identification probability obtained through the Bayesian approach. Following previous literature, the present work aims to improve it by inserting new information beyond network topology. The methodology is applied to the real test case represented by the sub-catchment of the sewer system Palermo (Italy)
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