Enhancing Hydraulic Efficiency of Pelton Turbines Through Computational Fluid Dynamics and Metaheuristic Optimization
In this work, the NSGA-II multi objective genetic algorithm, numerical methods, and parametric design techniques found in the Autodesk Inventor professional 2023 CAD software were combined to perform the geometrical optimization of the Pelton bucket geometry. The validation of the proposed method wa...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Algorithms |
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| Online Access: | https://www.mdpi.com/1999-4893/18/1/35 |
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| author | Guillermo Barragan Sebastian Atarihuana Edgar Cando Victor Hidalgo |
| author_facet | Guillermo Barragan Sebastian Atarihuana Edgar Cando Victor Hidalgo |
| author_sort | Guillermo Barragan |
| collection | DOAJ |
| description | In this work, the NSGA-II multi objective genetic algorithm, numerical methods, and parametric design techniques found in the Autodesk Inventor professional 2023 CAD software were combined to perform the geometrical optimization of the Pelton bucket geometry. The validation of the proposed method was carried out with numerical simulations using the OpenFOAM CFD program and taking into account the case study turbine’s operating conditions, as well as the k-SST turbulence model. The CFD simulation results and operational data from the case study turbine from the “Illuchi N°2” hydrocenter have been compared in order to validate the proposed methodology. The implementation of the NSGA-II in the design process resulted in optimized bucket geometrical parameters: bucket length, width, inlet angle, and outlet angle. These parameters not only resulted in a 2.56% increase in hydraulic efficiency, but also led to a 0.1 [kPa] reduction in the maximum pressure at the bottom of the bucket. Further research will involve testing these parameters using 3D printing methods to validate their effectiveness. |
| format | Article |
| id | doaj-art-21bca4e2ddbe4b7990d39579cff04b71 |
| institution | Kabale University |
| issn | 1999-4893 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj-art-21bca4e2ddbe4b7990d39579cff04b712025-01-24T13:17:33ZengMDPI AGAlgorithms1999-48932025-01-011813510.3390/a18010035Enhancing Hydraulic Efficiency of Pelton Turbines Through Computational Fluid Dynamics and Metaheuristic OptimizationGuillermo Barragan0Sebastian Atarihuana1Edgar Cando2Victor Hidalgo3Laboratorio de Mecánica Informática, Escuela Politécnica Nacional (EPN), Quito 170517, EcuadorLaboratorio de Mecánica Informática, Escuela Politécnica Nacional (EPN), Quito 170517, EcuadorLaboratorio de Mecánica Informática, Escuela Politécnica Nacional (EPN), Quito 170517, EcuadorLaboratorio de Mecánica Informática, Escuela Politécnica Nacional (EPN), Quito 170517, EcuadorIn this work, the NSGA-II multi objective genetic algorithm, numerical methods, and parametric design techniques found in the Autodesk Inventor professional 2023 CAD software were combined to perform the geometrical optimization of the Pelton bucket geometry. The validation of the proposed method was carried out with numerical simulations using the OpenFOAM CFD program and taking into account the case study turbine’s operating conditions, as well as the k-SST turbulence model. The CFD simulation results and operational data from the case study turbine from the “Illuchi N°2” hydrocenter have been compared in order to validate the proposed methodology. The implementation of the NSGA-II in the design process resulted in optimized bucket geometrical parameters: bucket length, width, inlet angle, and outlet angle. These parameters not only resulted in a 2.56% increase in hydraulic efficiency, but also led to a 0.1 [kPa] reduction in the maximum pressure at the bottom of the bucket. Further research will involve testing these parameters using 3D printing methods to validate their effectiveness.https://www.mdpi.com/1999-4893/18/1/35PeltonCFDNSGA-IIefficiencymetaheuristic |
| spellingShingle | Guillermo Barragan Sebastian Atarihuana Edgar Cando Victor Hidalgo Enhancing Hydraulic Efficiency of Pelton Turbines Through Computational Fluid Dynamics and Metaheuristic Optimization Algorithms Pelton CFD NSGA-II efficiency metaheuristic |
| title | Enhancing Hydraulic Efficiency of Pelton Turbines Through Computational Fluid Dynamics and Metaheuristic Optimization |
| title_full | Enhancing Hydraulic Efficiency of Pelton Turbines Through Computational Fluid Dynamics and Metaheuristic Optimization |
| title_fullStr | Enhancing Hydraulic Efficiency of Pelton Turbines Through Computational Fluid Dynamics and Metaheuristic Optimization |
| title_full_unstemmed | Enhancing Hydraulic Efficiency of Pelton Turbines Through Computational Fluid Dynamics and Metaheuristic Optimization |
| title_short | Enhancing Hydraulic Efficiency of Pelton Turbines Through Computational Fluid Dynamics and Metaheuristic Optimization |
| title_sort | enhancing hydraulic efficiency of pelton turbines through computational fluid dynamics and metaheuristic optimization |
| topic | Pelton CFD NSGA-II efficiency metaheuristic |
| url | https://www.mdpi.com/1999-4893/18/1/35 |
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