Neuro-fuzzy approach in estimating HazenWilliams friction coefficient for small-diameter polyethylene pipes
Low-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 DarcyWeisbach equation since the friction coefficient varies at each section of the lateral. Although its non-dimensional homogeneity and limitations in applicability, the empirical HazenWilliams 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 HazenWilliams coefficient (CHW) in PE pipes are still recommended regardless of pipe diameter. Experimental works have confirmed that there is a strong dependence of the CHW on pipe diameter (D), therefore a single value of the CHW 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 CHW 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 (CHW 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 CHW coefficient hence accurately estimate friction losses through smooth PE pipes.
friction coefficient hazenwilliams equation pipe network analysis neuro-fuzzy technique anfis