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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| Authors: | Kiyoumars Roushangar Roghayeh Ghasempour Sanam Biukaghazadeh |
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| Institution: | 1. Department of Water Resource Engineering, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran;2. Center of Excellence in Hydroinformatics, University of Tabriz, Tabriz, Iran;1. Industry-Academia Collaboration Foundation, Chonbuk National University, 567 Baejedae-ro, Deokjin-gu, Jeonju, 54896, Republic of Korea;2. Center for Jeongeup Industry-Academy Cooperation, Chonbuk National University, 9 Cheomdan-ro, Jeongeup, Jeonbuk, 56212, Republic of Korea;1. School of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada;2. School of the Built Environment, Heriot-Watt University, Edinburgh, UK;3. Department of Geography and Planning, School of Environmental Sciences, University of Liverpool, Liverpool, UK;4. Department of Geography, University of Lincoln, Lincoln, UK;1. Department of Civil & Structural Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bandar Baru Bangi, 43600, Malaysia;2. School of Civil and Environmental Engineering, College of Engineering, Nanyang Technical University, 50 Nanyang Avenue, 639798, Singapore;1. School of Electronic Science and Engineering, Southeast University, Nanjing 210096, China;2. State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China;1. Department of River Engineering and Disaster Management, Faculty of Hydrology and Water Resources, Thuyloi University, 175 Tay Son, Dong Da, Hanoi, Viet Nam;2. Unité de Modélisation Mathématiques et Informatique des Systèmes Complexes (UMMISCO), JEAI WARM, IRD, Sorbonne Université, F-93143 Bondy, France;3. Department of Civil and Environmental Engineering, Faculty of Engineering, National University of Singapore, Singapore;1. Department of Civil, Environmental and Natural Resources Engineering, Luleå University of Technology, Sweden;2. Department of Dams and Water Resources Engineering, University of Mosul, Iraq;3. Ministry of Higher Education and Scientific Research – KRG, Erbil, Iraq |
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| Abstract: | 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 w_b/y(ratio of deposited bed width,w_b,to flow depth,y) for a loose bed had the most significant impact on the modeling process. |
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| Keywords: | Gaussian process regression Loose bed Rigid bed Roughness coefficient Sewer pipes Support vector machine |
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