Neuro-fuzzy approach in estimating Hazen-Williams friction coefficient for small-diameter polyethylene pipes

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dc.authoridYildirim, Gurol -- 0000-0003-1899-5379; Ozger, Mehmet -- 0000-0001-9812-9918
dc.contributor.authorYıldırım, Gürol
dc.contributor.authorÖzger, Mehmet
dc.date.accessioned13.07.201910:50:10
dc.date.accessioned2019-07-29T19:27:10Z
dc.date.available13.07.201910:50:10
dc.date.available2019-07-29T19:27:10Z
dc.date.issued2009
dc.departmentMühendislik Fakültesi
dc.description.abstractLow-pressurized multiple outlet pipelines are extensively used to uniformly distribute irrigation water under different types of low-volume micro-irrigation systems. Polyethylene (PE) is the main pipe material for smooth pipes in sub-main unit of a micro-irrigation system due to its flexibility and resistibility to the sun. For computing friction loss in PE pipes, many practicing engineers hesitate to use the generalized Darcy-Weisbach equation since the friction coefficient varies at each section of the lateral. Although its non-dimensional homogeneity and limitations in applicability, the empirical Hazen-Williams equation is still commonly preferred, because of its simplicity in practice. In the current hydraulic computations for friction loss, some typical fixed values for the Hazen-Williams coefficient (C(HW)) in PE pipes are still recommended regardless of pipe diameter. Experimental works have confirmed that there is a strong dependence of the C(HW) on pipe diameter (D), therefore a single value of the C(HW) cannot be used for all ranges of pipe diameters. The primary focus of this research is to investigate the accuracy of a fuzzy rule system approach to estimate the proper value of the C(HW) coefficient for different pipe diameters because of the imprecise, insufficient, ambiguous and uncertain data available. A neuro-fuzzy approach was developed to relate the input (flow rate and pipe diameter) and output (C(HW) and friction loss) variables. The application of the proposed approach was performed using the measured data for friction losses available from the recent experimental analysis, hence its performance was tested using some statistic parameters for error estimation. The examination results indicated that through fuzzy rules and membership functions the proposed model can be successfully used to identify the proper values of C(HW) coefficient hence accurately estimate friction losses through smooth PE pipes. (C) 2008 Elsevier Ltd. All rights reserved.
dc.identifier.doi10.1016/j.advengsoft.2008.11.001
dc.identifier.endpage599en_US
dc.identifier.issn0965-9978
dc.identifier.issue8en_US
dc.identifier.scopusqualityQ1
dc.identifier.startpage593en_US
dc.identifier.urihttps://doi.org/10.1016/j.advengsoft.2008.11.001
dc.identifier.urihttps://hdl.handle.net/20.500.12451/5804
dc.identifier.volume40en_US
dc.identifier.wosWOS:000266339000006
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Ltd.
dc.relation.ispartofAdvances in Engineering Software
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectPipe Network Analysis
dc.subjectHazen-Williams Equation
dc.subjectFriction Coefficient
dc.subjectNeuro-Fuzzy Technique
dc.subjectANFIS
dc.titleNeuro-fuzzy approach in estimating Hazen-Williams friction coefficient for small-diameter polyethylene pipes
dc.typeArticle

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