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Evaluation of the parameters affecting the roughness coefficient of sewer pipes with rigid and loose boundary conditions via kernel based approaches

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International Journal of Sediment Research 2020年第2期35卷 171-179页

作者： Kiyoumars Roushangar Roghayeh Ghasempour Sanam Biukaghazadeh Department of Water Resource Engineering Faculty of Civil EngineeringUniversity of Tabriz Center of Excellence in Hydroinformatics University of Tabriz

One of the important issues in water transport and sewer systems is determining the flow resistance and roughness coefficient.An accurate estimation of the roughness coefficient is a substantial issue in the design and operation of hydraulic structures such as sewer pipes,the calculation of water depth and flow velocity,and the accurate characterization of energy losses.The current study,applies two kernel based approaches [Support Vector Machine(SVM) and Gaussian Process Regression(GPR)] to develop roughness coefficient models for sewer pipes.In the modeling process,two types of sewer bed conditions were considered:loose bed and rigid bed.In order to develop the models,different input combinations were considered under three scenarios(Scenario 1:based on hydraulic characteristics,Scenarios2 and 3:based on hydraulic and sediment characteristics with and without considering sediment concentration as input).The results proved the capability of the kernel based approaches in prediction of the roughness coefficient and it was found that for prediction of this parameter in sewer pipes Scenario 3 performed better than Scenarios 1 and 2.Also,the sensitivity analysis results showed that Dgr(Dimensionless particle number) for a rigid bed and wb/y(ratio of deposited bed width,wb,to flow depth,y) for a loose bed had the most significant impact on the modeling process.

关键词： Gaussian process regression Loose bed rigid bed Roughness coefficient Sewer pipes Support vector machine

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