Abstract
By the effect of pressure or velocity fluctuations, the water supply networks may be damaged. For avoiding of this case, suitable and optimized management of networks is very necessary. In this research, control of pressure and velocity was investigated to prevent problems of water supply network and also hydraulic characteristics were also predicted by Adaptive Neuro Fuzzy Inference System (ANFIS). In this way, first by zoning the city of Kangavar province (as case study) to six sub-zones based on distribution parameters, plotting of water supply networks with 10 years design period and target population of 95,000 based on 22 h in day irrigation and 29.6 square meter per capita at the end of design period were used. Pressure and velocity of network were then analyzed utilizing EPANET software. Based on the results, maximum pressure occurred at 3–3 node in third pressure region which estimate 100 m of water and maximum value of network velocity was estimated as 1.4 m per second. Also, results showed that the discharge was used in model according to diameter of tubes and selected paths in different regions are in appropriate range. Then, using the measured values, the fuzzy neural network was trained with the help of particle swarm algorithm, genetic algorithm, differential algorithm and ant colony algorithm optimized, and the optimal network for velocity prediction was obtained from fuzzy neural network with ant colony algorithm while for head loss fuzzy neural network with particle swarm algorithm was selected as the best model. According to the sensitivity analysis, diameter of pipes was found to be the most effective parameter in predicting velocity and pressure loss. Results showed the high capability of ANFIS in analyzing and predicting hydraulic properties of water supply tube.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Iranian Journal of Science and Technology, Transactions of Civil Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.