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A platform for research: civil engineering, architecture and urbanism
Uncertainty analysis of water distribution networks using type-2 fuzzy sets and parallel genetic algorithm
Water distribution networks are typically designed based on certain values of uncertain parameters such as reservoir head, nodal demand and friction coefficient to furnish acceptable performance by limiting nodal pressure head and pipes’ velocities. In this study, a fuzzy uncertainty analysis approach is developed to handle uncertainty of reservoir head and nodal demand over an extended period and long-term simulation, based on type-2 fuzzy logic. Furthermore, the long-term uncertainty of Hazen-Williams (HW) coefficient is also considered. A parallel genetic algorithm is introduced to solve a multi-objective optimization problem for fuzzy uncertainty analysis. The method is powered by a pressure dependent hydraulic simulator which is based on EPANET and an iterative procedure. It is implemented for a benchmark network from literature and a case study. Results show that network velocity is highly affected by uncertainties and the accumulation of different uncertainties may change the network performance significantly.
Uncertainty analysis of water distribution networks using type-2 fuzzy sets and parallel genetic algorithm
Water distribution networks are typically designed based on certain values of uncertain parameters such as reservoir head, nodal demand and friction coefficient to furnish acceptable performance by limiting nodal pressure head and pipes’ velocities. In this study, a fuzzy uncertainty analysis approach is developed to handle uncertainty of reservoir head and nodal demand over an extended period and long-term simulation, based on type-2 fuzzy logic. Furthermore, the long-term uncertainty of Hazen-Williams (HW) coefficient is also considered. A parallel genetic algorithm is introduced to solve a multi-objective optimization problem for fuzzy uncertainty analysis. The method is powered by a pressure dependent hydraulic simulator which is based on EPANET and an iterative procedure. It is implemented for a benchmark network from literature and a case study. Results show that network velocity is highly affected by uncertainties and the accumulation of different uncertainties may change the network performance significantly.
Uncertainty analysis of water distribution networks using type-2 fuzzy sets and parallel genetic algorithm
Geranmehr, Mohammadali (author) / Asghari, Keyvan (author) / Chamani, Mohammad R. (author)
Urban Water Journal ; 16 ; 193-204
2019-03-16
12 pages
Article (Journal)
Electronic Resource
English
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