Search

A valve-enclosed segment is the basic unit of water distribution networks (WDNs) in reliability analysis and optimal design. Based on the theory of the transitive closure of graphs, this paper presents a new method for identifying the whole segments in large WDNs in a single run. The method clones real valves as fictitious valves, uses valve pairs to simulate valve on-off status, and improves the Warshall algorithm to compute node transitive closure sets to identify all segments at a time. Additionally, redundant valves, endpoint valves, leaf segments, orphan segments, and regular segments are analyzed. One-way valves are considered in an unintended segment analysis. The method is described and discussed in detail by using a small sample network, then applied to a large real network containing 69,815 valves to prove its capability and efficiency. [ABSTRACT FROM AUTHOR]

Planned (e.g., regular maintenance) and unplanned (e.g. pipe burst) interruptions occur regularly in water distribution systems leading to their reduced performance. This paper presents an extended period simulation model capable of assessing system’s performance under these conditions. The extended period simulation model is based on the recently developed steady-state pressure driven hydraulic model and is capable of calculating pressures, flows, and hence actual water demands delivered under modified network topology conditions (caused by the use of isolation valves). The model is accompanied by several reliability indicators which can be used to assess system’s performance under interruptions. The above-mentioned methodology is demonstrated on a real-life case study in Italy. The role of isolation valve design and uncertainty in valve operability is analyzed and discussed. The case study results obtained demonstrate that the least cost design/rehabilitation of water distribution systems is likely to result in unreliable systems if the actual network configurations obtained by closing isolation valves in abnormal working conditions are not taken into account. [ABSTRACT FROM AUTHOR]

This paper introduces a simple topological approach to systematize the isolation of contaminated areas within the pressure zones of drinking water distribution systems (DWDSs). Assuming optimal location of contaminant detectors and known flow conditions, a heuristic procedure delineates the area to be isolated and identifies the valves to be closed by response teams sent in the field, taking into account a response delay from the time of first detection. As a first step leading to the development of a more comprehensive algorithmic application, the approach was elaborated and validated from a pragmatic perspective using two real-world DWDSs. Depending on each network’s design, configuration, and assumed flow conditions, application of the isolation procedure will result in different isolation strategies (extent of isolated areas, number of required isolation valves). The current approach is based on a set of simplifying assumptions, and needs to be further validated with other networks. The proposed methodology can be used to assess the required emergency response capabilities and even possible network design improvements. [ABSTRACT FROM AUTHOR]

The optimization of looped water distribution networks (WDN) implies achieving the best tradeoff between reliability and cost. Many works have dealt with minimizing the cost, but few have considered both cost and reliability. This paper aims to evaluate the performance of several multiobjective metaheuristics (MOMHs) to optimize the design of looped water distribution networks, taking into consideration two objective functions: Minimizing costs and maximizing the resilience index. The MOMHs used are: Strength Pareto Evolutionary Algorithm 2 (SPEA2), Pareto Archived Evolution Strategy, Pareto Envelope-based Selection Algorithm, Pareto Simulated Annealing, and Multiobjective Simulated Annealing and Tabu Search. These algorithms are tested and compared by applying them to two case studies: The first is a small well-known benchmark network (Hanoi), whereas the second one is a larger looped irrigation network (Balerma). Results of this work show that SPEA2 outperforms the remaining methods in terms of Pareto dominance. [ABSTRACT FROM AUTHOR]

Developed and demonstrated in this paper is an ant colony methodology extending previous work on ant colony optimization for least-cost design of gravitational water distribution systems with a single loading case, to the conjunctive least-cost design and operation of multiple loading pumping water distribution systems. Ant colony optimization is a relatively new meta-heuristic stochastic combinatorial computational discipline inspired by the behavior of ant colonies: ants deposit a certain amount of pheromone while moving, with each ant probabilistically following a direction rich in pheromone. This behavior has been used to explain how ants can find the shortest path between their nest and a food source, and inspired the development of ant colony optimization. The optimization problem solved herein is through linking an ant colony scheme with EPANET for the minimization of the systems design and operation costs, while delivering the consumers required water quantities at acceptable pressures. The decision variables for the design are the pipe diameters, the pumping stations maximum power, and the tanks storage, while for the operation—the pumping stations pressure heads and the water levels at the tanks for each of the loadings. The constraints are domain pressures at the consumer nodes, maximum allowable amounts of water withdrawals from the sources, and tanks storage closure. The proposed scheme is explored through base runs and sensitivity analysis using two pumping water distribution systems examples. [ABSTRACT FROM AUTHOR]

The efficient and effective search for the optimum design solution of a water distribution network using genetic algorithms (GAs) is governed by several factors such as representation scheme, population size, hydraulic simulation model, fitness function, penalty method, GA operators, number of generations, and more importantly the size of the search space. This paper proposes a modified GA that uses basic operators along with their derivatives randomly. Further, a methodology based on critical path method is suggested to reduce the search space. A software tool, GA-WAT, based on the proposed methodology is developed and first tested and verified for its efficiency and effectiveness on two previously published single source networks. Later, it is applied to the optimal design of a larger, two-source hypothetical network. The results obtained indicate that the modified GA with reduction in search space proposed herein is more effective, especially for large practical networks. [ABSTRACT FROM AUTHOR]

In this paper, the authors propose a new approach, the simulation–optimization method, to solve a nonlinear contaminant-source and release-history identification problem for a complex water distribution system. This approach is based on optimization analysis, using the EPANET water distribution system model as a simulator. In this approach, EPANET is used to generate concentrations at arbitrarily selected monitoring locations by specifying release histories of potential contaminant sources that are arbitrarily located within the water distribution system. This information is used in a continuous optimal predictor–corrector algorithm to identify the sources and their release histories. Throughout the simulation sequence, the water distribution system being studied is assumed to operate under known hydraulic operational patterns. The optimization model that is used as a corrector to estimate the release histories of the contaminant sources is designed to identify the similarity between the simulation response and measured data at monitoring locations. This information exchange is developed as a closed-loop system resulting in a convergent algorithm. Three scenarios, derived from the publicly documented Dover Township (Toms River), N.J., water-distribution system are tested using the proposed approach. Results show that the approach is effective, efficient, and robust in identifying locations and release histories of contaminant sources. [ABSTRACT FROM AUTHOR]

This paper develops a multicommodity flow model to optimize water distribution and water quality in a regional water supply system. Waters from different sources with different qualities are considered as distinct commodities that concurrently share a single water distribution system. The model can accommodate two-way flow pipes, represented by undirected arcs, and the perfect mixing condition. Additionally, blending requirements are specified at certain control nodes within the system to ensure that downstream users receive the desired water quality. The optimization model is highly nonlinear and solved by a hybrid genetic algorithm (GA). The GA is first used to globally search for the directions of all undirected arcs. Then a generalized reduced gradient (GRG) algorithm embedded in the GA is used to optimize the objective function for fitness evaluation. The proposed methodology was first tested and verified on a hypothetical system and then applied to the regional water distribution system of the Metropolitan Water District of Southern California. The results obtained indicate that the proposed hybrid GA is a viable way of converting an undirected network to a directed network by separating the complicating variables, and that the resulting directed network model can be solved iteratively and efficiently by a gradient-based algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a multiobjective genetic algorithm approach to the design of a water distribution network. The objectives considered are minimization of the network cost and maximization of a reliability measure. In this study, a new reliability measure, called network resilience, is introduced. This measure mimics a designer’s desire of providing excess head above the minimum allowable head at the nodes and of designing reliable loops with practicable pipe diameters. The proposed method produces a set of Pareto-optimal solutions in the search space of cost and network resilience. Genetic algorithms are observed to be poor in handling constraints. To handle constraints in a better way, a constraint handling technique that does not require a penalty coefficient and is applicable to water distribution systems is presented. The present model is applied to two example problems, which are widely reported. Comparison of the present method with other methods revealed that the network resilience based approach gave better results. [ABSTRACT FROM AUTHOR]

This article presents a critique of a previously published paper regarding pressure-deficient water systems.