scholarly journals Development of Multi-Objective Optimal Redundant Design Approach for Multiple Pipe Failure in Water Distribution System

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 553 ◽  
Author(s):  
Young Choi ◽  
Joong Kim
Keyword(s):  
Optimal Design ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Search Algorithm ◽  
Harmony Search ◽  
Water Distribution Systems ◽  
Design Approach ◽  
Pipe Failure ◽  
Multi Objective

This study proposes a multi-objective optimal design approach for water distribution systems, considering mechanical system redundancy under multiple pipe failure. Mechanical redundancy is applied to the system’s hydraulic ability, based on the pressure deficit between the pressure requirements under abnormal conditions. The developed design approach shows the relationships between multiple pipe failure states and system redundancy, for different numbers of pipe-failure conditions (e.g., first, second, third, …, tenth). Furthermore, to consider extreme demand modeling, the threshold of the demand quantity is investigated simultaneously with multiple pipe failure modeling. The design performance is evaluated using the mechanical redundancy deficit under extreme demand conditions. To verify the proposed design approach, an expanded version of the well-known benchmark network is used, configured as an ideal grid-shape, and the multi-objective harmony search algorithm is used as the optimal design approach, considering construction cost and system mechanical redundancy. This optimal design technique could be used to propose a standard for pipe failure, based on factors such as the number of broken pipes, during failure condition analysis for redundancy-based designs of water distribution systems.

Single and multi-objective optimal design of water distribution systems: application to the case study of the Hanoi system

2009 ◽  
Vol 9 (4) ◽  
pp. 395-404 ◽  
Author(s):  
Lina Perelman ◽  
Ariel Krapivka ◽  
Avi Ostfeld
Keyword(s):  
Optimal Design ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems ◽  
Research Literature ◽  
Future Research ◽  
Multi Objective ◽  
Objective Model ◽  
Single Objective

This manuscript describes the application of two recent methodologies developed by the authors for single and multi-objective optimal design of water distribution systems. The single-objective model is a hybrid algorithm incorporating decomposition, spanning tree search, and evolutionary computation, while the multi-objective algorithm integrates features form multi-objective genetic algorithms with the Cross Entropy combinatorial optimization scheme. The two models are implemented on the Hanoi water distribution system, one of the more explored systems in the research literature, through base runs and sensitivity analysis. The single-objective model produced the best known least cost solution for split pipe design, while the multi-objective model has shown robustness and well explanatory outcomes. Discussion of the accomplished results and suggestions for future research are provided.

scholarly journals Proposed probabilistic models of pipe failure in water distribution system

2018 ◽  
Vol 193 ◽  
pp. 02002
Author(s):  
Thi Minh Lanh Pham ◽  
Hai Ha Pham ◽  
Nguyen Anh Thu Do ◽  
Dinh Hong Le
Keyword(s):  
Water Supply ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Unit Length ◽  
Water Distribution Systems ◽  
Labor Cost ◽  
Experimental Models ◽  
Pipe Failure ◽  
Tree Model

All pipes in water supply network are installed underground, so it is difficult to identify pipe failure location during the operation of a system. Prediction of the risk of pipe failure in the water distribution systems is necessary for preparation of reparations and displacement of a pipe network system. Based on the probability of pipe failure, it will be possible to save money and labor cost for water supply companies. Many studies have been conducted on this topic, some of which used experimental models, others used statistical models in which recently many authors used regression model, but almost all the models come up with calculating the pipe failure rate per unit length of pipe in a year. It is not a direct probability of pipe failure. This article reviews various methods to evaluate pipe failure in water distribution systems. Based on that, the authors proposed two models: Regression Logistic Model and Decision Tree Model that would support an effective decision making for detecting the pipe failure and proposing appropriate solutions.

scholarly journals A hybrid cuckoo–harmony search algorithm for optimal design of water distribution systems

2015 ◽  
Vol 18 (3) ◽  
pp. 544-563 ◽  
Author(s):  
Razi Sheikholeslami ◽  
Aaron C. Zecchin ◽  
Feifei Zheng ◽  
Siamak Talatahari
Keyword(s):  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Cuckoo Search ◽  
Search Space ◽  
Optimization Method

Meta-heuristic algorithms have been broadly used to deal with a range of water resources optimization problems over the past decades. One issue that exists in the use of these algorithms is the requirement of large computational resources, especially when handling real-world problems. To overcome this challenge, this paper develops a hybrid optimization method, the so-called CSHS, in which a cuckoo search (CS) algorithm is combined with a harmony search (HS) scheme. Within this hybrid framework, the CS is employed to find the promising regions of the search space within the initial explorative stages of the search, followed by a thorough exploitation phase using the combined CS and HS algorithms. The utility of the proposed CSHS is demonstrated using four water distribution system design problems with increased scales and complexity. The obtained results reveal that the CSHS method outperforms the standard CS, as well as the majority of other meta-heuristics that have previously been applied to the case studies investigated, in terms of efficiently seeking optimal solutions. Furthermore, the CSHS has two control parameters that need to be fine-tuned compared to many other algorithms, which is appealing for its practical application as an extensive parameter-calibration process is typically computationally very demanding.

A New Energy Optimization Strategy for Pumping Operation in Water Distribution Systems

2012 ◽  
Author(s):  
Dhafar Al-Ani ◽  
Saeid Habibi
Keyword(s):  
Distribution System ◽  
Energy Cost ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution System ◽  
Water Distribution Systems ◽  
Energy Optimization ◽  
Operating Conditions ◽  
Optimization Strategy ◽  
Multi Objective

As time goes on, more and more operating-modes based on changing demand profiles will be compiled to enrich the range of feasible solutions for a water distribution system. This implies the conservation of energy consumed by a water pumping station and improves the ability for energy optimization. Another important goal was improving safety, reliability, and maintenance cost. In this paper, three important goals were addressed: cost-effectives, safety, and self-sustainability operations of water distribution systems. In this work, the objective functions to optimize were total electrical energy cost, maintenance costs, and reservoir water level variation while preserving the service provided to water clients. To accomplish these goals, an effective Energy Optimization Strategy (EOS) that manages trade-off among operational cost, system safety, and reliability was proposed. Moreover, the EOS aims at improving the operating conditions (i.e., pumping schedule) of an existing network system (i.e., with given capacities of tanks) and without physical changes in the infrastructure of the distribution systems. The new strategy consisted of a new Parallel Multi-objective Particle Swarm optimization with Adaptive Search-space Boundaries (P-MOPSO-ASB) and a modified EPANET. This has several advantages: obtaining a Pareto-front with solutions that are quantitatively equally good and providing the decision maker with the opportunity to qualitatively compare the solutions before their implementation into practice. The multi-objective optimization approach developed in this paper follows modern applications that combine an optimization algorithm with a network simulation model by using full hydraulic simulations and distributed demand models. The proposed EOS was successfully applied to a rural water distribution system, namely Saskatoon West. The results showed that a potential for considerable cost reductions in total energy cost was achieved (approximately % 7.5). Furthermore, the safety and the reliability of the system are preserved by using the new optimal pump schedules.

scholarly journals Water Quality Based Multi-objective Optimal Design of Water Distribution Systems

2016 ◽  
Vol 31 (1) ◽  
pp. 93-108 ◽  
Author(s):  
Meisam Shokoohi ◽  
Massoud Tabesh ◽  
Sara Nazif ◽  
Mehdi Dini
Keyword(s):  
Water Quality ◽  
Optimal Design ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems ◽  
Multi Objective

scholarly journals Application of genetic programming to modeling pipe failures in water distribution systems

2010 ◽  
Vol 13 (3) ◽  
pp. 419-428 ◽  
Author(s):  
Qiang Xu ◽  
Qiuwen Chen ◽  
Weifeng Li
Keyword(s):  
Genetic Programming ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Pipe Failure ◽  
Beijing City ◽  
Failure Data ◽  
Processing Strategies ◽  
Gis Data ◽  
Failure Models

The water loss from a water distribution system is a serious problem for many cities, which incurs enormous economic and social loss. However, the economic and human resource costs to exactly locate the leakage are extraordinarily high. Thus, reliable and robust pipe failure models are demanded to assess a pipe's propensity to fail. Beijing City was selected as the case study area and the pipe failure data for 19 years (1987–2005) were analyzed. Three different kinds of methods were applied to build pipe failure models. First, a statistical model was built, which discovered that the ages of leakage pipes followed the Weibull distribution. Then, two other models were developed using genetic programming (GP) with different data pre-processing strategies. The three models were compared thereafter and the best model was applied to assess the criticality of all the pipe segments of the entire water supply network in Beijing City based on GIS data.

scholarly journals An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems Design

Water ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1334
Author(s):  
Mohamed R. Torkomany ◽  
Hassan Shokry Hassan ◽  
Amin Shoukry ◽  
Ahmed M. Abdelrazek ◽  
Mohamed Elkholy
Keyword(s):  
Particle Swarm Optimization ◽  
Local Search ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems ◽  
Particle Swarm ◽  
Large Network ◽  
Swarm Optimization ◽  
Original Algorithm ◽  
Multi Objective

The scarcity of water resources nowadays lays stress on researchers to develop strategies aiming at making the best benefit of the currently available resources. One of these strategies is ensuring that reliable and near-optimum designs of water distribution systems (WDSs) are achieved. Designing WDSs is a discrete combinatorial NP-hard optimization problem, and its complexity increases when more objectives are added. Among the many existing evolutionary algorithms, a new hybrid fast-convergent multi-objective particle swarm optimization (MOPSO) algorithm is developed to increase the convergence and diversity rates of the resulted non-dominated solutions in terms of network capital cost and reliability using a minimized computational budget. Several strategies are introduced to the developed algorithm, which are self-adaptive PSO parameters, regeneration-on-collision, adaptive population size, and using hypervolume quality for selecting repository members. A local search method is also coupled to both the original MOPSO algorithm and the newly developed one. Both algorithms are applied to medium and large benchmark problems. The results of the new algorithm coupled with the local search are superior to that of the original algorithm in terms of different performance metrics in the medium-sized network. In contrast, the new algorithm without the local search performed better in the large network.

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