| People | Locations | Statistics |
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| Seuring, Stefan |
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| Nor Azizi, S. |
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| Pato, Margarida Vaz |
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| Kölker, Katrin |
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| Huber, Oliver |
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| Király, Tamás |
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| Spengler, Thomas Stefan |
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| Al-Ammar, Essam A. |
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| Dargahi, Fatemeh |
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| Mota, Rui |
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| Mazalan, Nurul Aliah Amirah |
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| Macharis, Cathy | Brussels |
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| Arunasari, Yova Tri |
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| Nunez, Alfredo | Delft |
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| Bouhorma, Mohammed |
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| Bonato, Matteo |
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| Fitriani, Ira |
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| Autor Correspondente Coelho, Sílvia. |
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| Pond, Stephen |
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| Okwara, Ukoha Kalu |
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| Toufigh, Vahid |
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| Campisi, Tiziana | Enna |
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| Ermolieva, Tatiana |
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| Sánchez-Cambronero, Santos |
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| Agzamov, Akhror |
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Talebbeydokhti, Nasser
in Cooperation with on an Cooperation-Score of 37%
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Publications (13/13 displayed)
- 2023Assessment of Seismic Resilience in Urban Water Distribution Network Considering Hydraulic Indicescitations
- 2023Evaluation of Darcy–Weisbach Friction Factors of Fiberglass Pipes Based on Internal Surface Roughness Measurementcitations
- 2022Correction to: Analytical and Numerical Solutions to Level Pool Routing Equations for Simplified Shapes of Inflow Hydrographs
- 2022Investigation of Energy Dissipation Rate of Stepped Vertical Overfall (SVO) Spillway Using Physical Modeling and Soft Computing Techniquescitations
- 2022Investigation of Iron and Lead Changes in Wastewater Treatment Sludge Decomposition Reactor With and Without Worm Existence
- 2022Analytical and Numerical Solutions to Level Pool Routing Equations for Simplified Shapes of Inflow Hydrographscitations
- 2022Optimizing Operational Parameters of Electrokinetic Technique Assisted by a Permeable Reactive Barrier for Remediation of Nitrate-Contaminated Soilcitations
- 2020Comparison of Explicit Relations for Calculating Colebrook Friction Factor in Pipe Network Analysis Using h-based Methodscitations
- 2019Development of a New Flow-dependent Scheme for Calculating Grain and Form Roughness Coefficientscitations
- 2019Analytical Solutions for Water Infiltration into Unsaturated–Semi-Saturated Soils Under Different Water Content Distributions on the Top Boundarycitations
- 2017External Validation Criteria and Uncertainty Analysis of Maximum Scour Depth at Downstream of Stilling Basins Based on EPR and MT Approachescitations
- 2016New Analytical Solutions to 2-D Water Infiltration and Imbibition into Unsaturated Soils for Various Boundary and Initial Conditionscitations
- 2011Modeling of non-breaking and breaking solitary wave run-up using shock-capturing TVD-WAF schemecitations
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document
Investigation of Energy Dissipation Rate of Stepped Vertical Overfall (SVO) Spillway Using Physical Modeling and Soft Computing Techniques
Abstract
In the present study a physical model of a stepped vertical overfall (SVO) spillway is proposed and designed as a novel combination of a free overfall spillway with horizontal steps. First, the hydraulic design characteristics of the proposed spillway were discussed using a laboratory-scaled model. Effective parameters on the energy dissipation rate were defined as the relative critical depth, Froude number, number of steps, and dimensionless steps’ geometry parameter using dimensional analysis. The energy dissipation rate of the stepped vertical overfall spillway is measured using a waterwheel laboratory setup. Different geometry and hydraulic scenarios were used to assess the energy dissipation rate variation of the proposed spillway. Furthermore, Support Vector Regression and Random Forest Regression methods were used to estimate the energy dissipation of the proposed structure. Investigating the energy dissipation rate of 27 geometry scenarios with the available range of discharge revealed that the energy dissipation rate against the water’s relative depth inside the SVO spillway follows a gradually increasing trend ranging between 88.53% to 98.06%. Also, random forest regression algorithm showed more accurate prediction performance than support vector regression approach with RMSE = 0.128 and R^2 = 0.99 in training stage and RMSE = 0.115 and R^2 = 0.99 in testing stage. The support vector regression model estimated the proposed spillway’s energy dissipation rate with an accuracy of RMSE = 0.67 and R^2 = 0.88 in training stage and RMSE = 0.61 and R^2 = 0.9 in testing stage.
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