Application of statistical and intelligent methods in performance analysis of the ram pump

R Fatahialkouhi, B Lashkarara - 10 th International Congress on …, 2015 - researchgate.net
R Fatahialkouhi, B Lashkarara
10 th International Congress on Civil Engineering University of Tabriz, 2015researchgate.net
From the early nineteenth century, migration from rural to urban areas as an important social
phenomenon known throughout the world. On the one hand, the lack of adequate water
supply for agriculture and animal husbandry as a push factor in rural and on the other hand,
pull factors in urban In an interaction with each other, Thinking fosters villagers to migrate to
the cities. Uneconomical construction of water supply systems in sparsely populated rural or
impassable rural, rapid depletion of these areas is provided. Utilization of water hammer …
Abstract
From the early nineteenth century, migration from rural to urban areas as an important social phenomenon known throughout the world. On the one hand, the lack of adequate water supply for agriculture and animal husbandry as a push factor in rural and on the other hand, pull factors in urban In an interaction with each other, Thinking fosters villagers to migrate to the cities. Uneconomical construction of water supply systems in sparsely populated rural or impassable rural, rapid depletion of these areas is provided. Utilization of water hammer renewable energy can be a practical solution, Supply water to rural areas without spending huge amounts of water transfer. In this study, In addition to introducing the use of water hammer energy, in water transfer systems, the equations of space research provided to design ram pump using dimensional analysis and nonlinear regression. Statistical analysis of results shows that the proposed equations was compared with experimental observations, to estimate the dimensionless parameter HQ qh c are 0.69 for correlation coefficient and 1.1192 for the coefficient of the fitted line, and for the dimensionless parameter c QQ are 0.775 for correlation coefficient and 0.9904 for the coefficient of the fitted line. In the next phase, to refine results of neural network model was used. The architecture developed for this model predicts the dimensional parameters HQ qh c and c QQ with 1.1314 and 0.9648 for the coefficient of the fitted line respectively with compared the experimental observations, and while, the proposed equations estimated this parameters 1.22 and 3.52 percent less. As well as, the proposed equations in this study are simple and do not require to computer, thus the proposed equations are recommended to design and operation of the ram pumps.
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