A multi-objective and CFD based optimization of roof-flap geometry and position for simultaneous drag and lift reduction
As the transport sector is responsible for the consumption of a vast proportion of the oil produced, it is mandatory to research feasible solutions to tackle this issue. The application of aerodynamic attachments for passive flow control and reducing resisting aerodynamic forces such as drag and lif...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Mohammad Rostamzadeh-Renani [verfasserIn] Mohammadreza Baghoolizadeh [verfasserIn] S. Mohammad Sajadi [verfasserIn] Reza Rostamzadeh-Renani [verfasserIn] Narjes Khabazian Azarkhavarani [verfasserIn] Soheil Salahshour [verfasserIn] Davood Toghraie [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2024 |
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| Übergeordnetes Werk: |
In: Propulsion and Power Research - KeAi Communications Co., Ltd., 2017, 13(2024), 1, Seite 26-45 |
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| Übergeordnetes Werk: |
volume:13 ; year:2024 ; number:1 ; pages:26-45 |
| Links: |
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| DOI / URN: |
10.1016/j.jppr.2024.02.004 |
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DOAJ097302058 |
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| 520 | |a As the transport sector is responsible for the consumption of a vast proportion of the oil produced, it is mandatory to research feasible solutions to tackle this issue. The application of aerodynamic attachments for passive flow control and reducing resisting aerodynamic forces such as drag and lift is one of the most practicable ways to minimize vehicle energy consumption. The flaps are one of the most innovative aerodynamic attachments that can enhance the flow motion in the boundary layer at the trailing edge of the wings. In the present paper, the flap is designed and modeled for controlling the airflow at the roof-end of a 2D Ahmed body model, inspired by the schematic of the flap at the trailing edge of the wing. As a result, the flap's geometry and position from the roof-end of the car model are parameterized, which leads to having four design variables. The objective functions of the present study are the vehicle's drag coefficient and lift coefficient. 25 Design of Experiment (DOE) points are considered enabling the Box-Behnken method. Then, each DOE point is modeled in the computational domain, and the flow-field around the model is simulated using Ansys Fluent software. The results obtained for the DOE points are employed by different regressors, and the relation between design variables and objective functions is extracted using GMDH-ANN. The GMDH-ANN is then coupled with three types of optimization algorithms, among which the Genetic algorithm proves to have the most ideal coupling process for optimization. Finally, after analyzing the variations in the geometry and position of the roof flap from the car roof-end, the roof-flap with specifications of L = 0.1726 m, α = 5.0875°, H = 0.0188 m, and d = 0.241 m can optimize the car drag and lift coefficients by 21.27% and 19.91%, respectively. The present research discusses the opportunities and challenges of optimal design roof-flap geometry and its influence on car aerodynamic performance. | ||
| 650 | 4 | |a Drag coefficient | |
| 650 | 4 | |a Lift coefficient | |
| 650 | 4 | |a Roof flap | |
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10.1016/j.jppr.2024.02.004 doi (DE-627)DOAJ097302058 (DE-599)DOAJ6b04f31c81264dd5a31991b5a1dd25c7 DE-627 ger DE-627 rakwb eng TL1-4050 Mohammad Rostamzadeh-Renani verfasserin aut A multi-objective and CFD based optimization of roof-flap geometry and position for simultaneous drag and lift reduction 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier As the transport sector is responsible for the consumption of a vast proportion of the oil produced, it is mandatory to research feasible solutions to tackle this issue. The application of aerodynamic attachments for passive flow control and reducing resisting aerodynamic forces such as drag and lift is one of the most practicable ways to minimize vehicle energy consumption. The flaps are one of the most innovative aerodynamic attachments that can enhance the flow motion in the boundary layer at the trailing edge of the wings. In the present paper, the flap is designed and modeled for controlling the airflow at the roof-end of a 2D Ahmed body model, inspired by the schematic of the flap at the trailing edge of the wing. As a result, the flap's geometry and position from the roof-end of the car model are parameterized, which leads to having four design variables. The objective functions of the present study are the vehicle's drag coefficient and lift coefficient. 25 Design of Experiment (DOE) points are considered enabling the Box-Behnken method. Then, each DOE point is modeled in the computational domain, and the flow-field around the model is simulated using Ansys Fluent software. The results obtained for the DOE points are employed by different regressors, and the relation between design variables and objective functions is extracted using GMDH-ANN. The GMDH-ANN is then coupled with three types of optimization algorithms, among which the Genetic algorithm proves to have the most ideal coupling process for optimization. Finally, after analyzing the variations in the geometry and position of the roof flap from the car roof-end, the roof-flap with specifications of L = 0.1726 m, α = 5.0875°, H = 0.0188 m, and d = 0.241 m can optimize the car drag and lift coefficients by 21.27% and 19.91%, respectively. The present research discusses the opportunities and challenges of optimal design roof-flap geometry and its influence on car aerodynamic performance. Drag coefficient Lift coefficient Roof flap Computational fluid dynamics Artificial neural network Genetic algorithm Motor vehicles. Aeronautics. Astronautics Mohammadreza Baghoolizadeh verfasserin aut S. Mohammad Sajadi verfasserin aut Reza Rostamzadeh-Renani verfasserin aut Narjes Khabazian Azarkhavarani verfasserin aut Soheil Salahshour verfasserin aut Davood Toghraie verfasserin aut In Propulsion and Power Research KeAi Communications Co., Ltd., 2017 13(2024), 1, Seite 26-45 (DE-627)746705905 (DE-600)2716734-3 2212540X nnns volume:13 year:2024 number:1 pages:26-45 https://doi.org/10.1016/j.jppr.2024.02.004 kostenfrei https://doaj.org/article/6b04f31c81264dd5a31991b5a1dd25c7 kostenfrei http://www.sciencedirect.com/science/article/pii/S2212540X24000075 kostenfrei https://doaj.org/toc/2212-540X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2024 1 26-45 |
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10.1016/j.jppr.2024.02.004 doi (DE-627)DOAJ097302058 (DE-599)DOAJ6b04f31c81264dd5a31991b5a1dd25c7 DE-627 ger DE-627 rakwb eng TL1-4050 Mohammad Rostamzadeh-Renani verfasserin aut A multi-objective and CFD based optimization of roof-flap geometry and position for simultaneous drag and lift reduction 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier As the transport sector is responsible for the consumption of a vast proportion of the oil produced, it is mandatory to research feasible solutions to tackle this issue. The application of aerodynamic attachments for passive flow control and reducing resisting aerodynamic forces such as drag and lift is one of the most practicable ways to minimize vehicle energy consumption. The flaps are one of the most innovative aerodynamic attachments that can enhance the flow motion in the boundary layer at the trailing edge of the wings. In the present paper, the flap is designed and modeled for controlling the airflow at the roof-end of a 2D Ahmed body model, inspired by the schematic of the flap at the trailing edge of the wing. As a result, the flap's geometry and position from the roof-end of the car model are parameterized, which leads to having four design variables. The objective functions of the present study are the vehicle's drag coefficient and lift coefficient. 25 Design of Experiment (DOE) points are considered enabling the Box-Behnken method. Then, each DOE point is modeled in the computational domain, and the flow-field around the model is simulated using Ansys Fluent software. The results obtained for the DOE points are employed by different regressors, and the relation between design variables and objective functions is extracted using GMDH-ANN. The GMDH-ANN is then coupled with three types of optimization algorithms, among which the Genetic algorithm proves to have the most ideal coupling process for optimization. Finally, after analyzing the variations in the geometry and position of the roof flap from the car roof-end, the roof-flap with specifications of L = 0.1726 m, α = 5.0875°, H = 0.0188 m, and d = 0.241 m can optimize the car drag and lift coefficients by 21.27% and 19.91%, respectively. The present research discusses the opportunities and challenges of optimal design roof-flap geometry and its influence on car aerodynamic performance. Drag coefficient Lift coefficient Roof flap Computational fluid dynamics Artificial neural network Genetic algorithm Motor vehicles. Aeronautics. Astronautics Mohammadreza Baghoolizadeh verfasserin aut S. Mohammad Sajadi verfasserin aut Reza Rostamzadeh-Renani verfasserin aut Narjes Khabazian Azarkhavarani verfasserin aut Soheil Salahshour verfasserin aut Davood Toghraie verfasserin aut In Propulsion and Power Research KeAi Communications Co., Ltd., 2017 13(2024), 1, Seite 26-45 (DE-627)746705905 (DE-600)2716734-3 2212540X nnns volume:13 year:2024 number:1 pages:26-45 https://doi.org/10.1016/j.jppr.2024.02.004 kostenfrei https://doaj.org/article/6b04f31c81264dd5a31991b5a1dd25c7 kostenfrei http://www.sciencedirect.com/science/article/pii/S2212540X24000075 kostenfrei https://doaj.org/toc/2212-540X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2024 1 26-45 |
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10.1016/j.jppr.2024.02.004 doi (DE-627)DOAJ097302058 (DE-599)DOAJ6b04f31c81264dd5a31991b5a1dd25c7 DE-627 ger DE-627 rakwb eng TL1-4050 Mohammad Rostamzadeh-Renani verfasserin aut A multi-objective and CFD based optimization of roof-flap geometry and position for simultaneous drag and lift reduction 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier As the transport sector is responsible for the consumption of a vast proportion of the oil produced, it is mandatory to research feasible solutions to tackle this issue. The application of aerodynamic attachments for passive flow control and reducing resisting aerodynamic forces such as drag and lift is one of the most practicable ways to minimize vehicle energy consumption. The flaps are one of the most innovative aerodynamic attachments that can enhance the flow motion in the boundary layer at the trailing edge of the wings. In the present paper, the flap is designed and modeled for controlling the airflow at the roof-end of a 2D Ahmed body model, inspired by the schematic of the flap at the trailing edge of the wing. As a result, the flap's geometry and position from the roof-end of the car model are parameterized, which leads to having four design variables. The objective functions of the present study are the vehicle's drag coefficient and lift coefficient. 25 Design of Experiment (DOE) points are considered enabling the Box-Behnken method. Then, each DOE point is modeled in the computational domain, and the flow-field around the model is simulated using Ansys Fluent software. The results obtained for the DOE points are employed by different regressors, and the relation between design variables and objective functions is extracted using GMDH-ANN. The GMDH-ANN is then coupled with three types of optimization algorithms, among which the Genetic algorithm proves to have the most ideal coupling process for optimization. Finally, after analyzing the variations in the geometry and position of the roof flap from the car roof-end, the roof-flap with specifications of L = 0.1726 m, α = 5.0875°, H = 0.0188 m, and d = 0.241 m can optimize the car drag and lift coefficients by 21.27% and 19.91%, respectively. The present research discusses the opportunities and challenges of optimal design roof-flap geometry and its influence on car aerodynamic performance. Drag coefficient Lift coefficient Roof flap Computational fluid dynamics Artificial neural network Genetic algorithm Motor vehicles. Aeronautics. Astronautics Mohammadreza Baghoolizadeh verfasserin aut S. Mohammad Sajadi verfasserin aut Reza Rostamzadeh-Renani verfasserin aut Narjes Khabazian Azarkhavarani verfasserin aut Soheil Salahshour verfasserin aut Davood Toghraie verfasserin aut In Propulsion and Power Research KeAi Communications Co., Ltd., 2017 13(2024), 1, Seite 26-45 (DE-627)746705905 (DE-600)2716734-3 2212540X nnns volume:13 year:2024 number:1 pages:26-45 https://doi.org/10.1016/j.jppr.2024.02.004 kostenfrei https://doaj.org/article/6b04f31c81264dd5a31991b5a1dd25c7 kostenfrei http://www.sciencedirect.com/science/article/pii/S2212540X24000075 kostenfrei https://doaj.org/toc/2212-540X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2024 1 26-45 |
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10.1016/j.jppr.2024.02.004 doi (DE-627)DOAJ097302058 (DE-599)DOAJ6b04f31c81264dd5a31991b5a1dd25c7 DE-627 ger DE-627 rakwb eng TL1-4050 Mohammad Rostamzadeh-Renani verfasserin aut A multi-objective and CFD based optimization of roof-flap geometry and position for simultaneous drag and lift reduction 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier As the transport sector is responsible for the consumption of a vast proportion of the oil produced, it is mandatory to research feasible solutions to tackle this issue. The application of aerodynamic attachments for passive flow control and reducing resisting aerodynamic forces such as drag and lift is one of the most practicable ways to minimize vehicle energy consumption. The flaps are one of the most innovative aerodynamic attachments that can enhance the flow motion in the boundary layer at the trailing edge of the wings. In the present paper, the flap is designed and modeled for controlling the airflow at the roof-end of a 2D Ahmed body model, inspired by the schematic of the flap at the trailing edge of the wing. As a result, the flap's geometry and position from the roof-end of the car model are parameterized, which leads to having four design variables. The objective functions of the present study are the vehicle's drag coefficient and lift coefficient. 25 Design of Experiment (DOE) points are considered enabling the Box-Behnken method. Then, each DOE point is modeled in the computational domain, and the flow-field around the model is simulated using Ansys Fluent software. The results obtained for the DOE points are employed by different regressors, and the relation between design variables and objective functions is extracted using GMDH-ANN. The GMDH-ANN is then coupled with three types of optimization algorithms, among which the Genetic algorithm proves to have the most ideal coupling process for optimization. Finally, after analyzing the variations in the geometry and position of the roof flap from the car roof-end, the roof-flap with specifications of L = 0.1726 m, α = 5.0875°, H = 0.0188 m, and d = 0.241 m can optimize the car drag and lift coefficients by 21.27% and 19.91%, respectively. The present research discusses the opportunities and challenges of optimal design roof-flap geometry and its influence on car aerodynamic performance. Drag coefficient Lift coefficient Roof flap Computational fluid dynamics Artificial neural network Genetic algorithm Motor vehicles. Aeronautics. Astronautics Mohammadreza Baghoolizadeh verfasserin aut S. Mohammad Sajadi verfasserin aut Reza Rostamzadeh-Renani verfasserin aut Narjes Khabazian Azarkhavarani verfasserin aut Soheil Salahshour verfasserin aut Davood Toghraie verfasserin aut In Propulsion and Power Research KeAi Communications Co., Ltd., 2017 13(2024), 1, Seite 26-45 (DE-627)746705905 (DE-600)2716734-3 2212540X nnns volume:13 year:2024 number:1 pages:26-45 https://doi.org/10.1016/j.jppr.2024.02.004 kostenfrei https://doaj.org/article/6b04f31c81264dd5a31991b5a1dd25c7 kostenfrei http://www.sciencedirect.com/science/article/pii/S2212540X24000075 kostenfrei https://doaj.org/toc/2212-540X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2024 1 26-45 |
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10.1016/j.jppr.2024.02.004 doi (DE-627)DOAJ097302058 (DE-599)DOAJ6b04f31c81264dd5a31991b5a1dd25c7 DE-627 ger DE-627 rakwb eng TL1-4050 Mohammad Rostamzadeh-Renani verfasserin aut A multi-objective and CFD based optimization of roof-flap geometry and position for simultaneous drag and lift reduction 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier As the transport sector is responsible for the consumption of a vast proportion of the oil produced, it is mandatory to research feasible solutions to tackle this issue. The application of aerodynamic attachments for passive flow control and reducing resisting aerodynamic forces such as drag and lift is one of the most practicable ways to minimize vehicle energy consumption. The flaps are one of the most innovative aerodynamic attachments that can enhance the flow motion in the boundary layer at the trailing edge of the wings. In the present paper, the flap is designed and modeled for controlling the airflow at the roof-end of a 2D Ahmed body model, inspired by the schematic of the flap at the trailing edge of the wing. As a result, the flap's geometry and position from the roof-end of the car model are parameterized, which leads to having four design variables. The objective functions of the present study are the vehicle's drag coefficient and lift coefficient. 25 Design of Experiment (DOE) points are considered enabling the Box-Behnken method. Then, each DOE point is modeled in the computational domain, and the flow-field around the model is simulated using Ansys Fluent software. The results obtained for the DOE points are employed by different regressors, and the relation between design variables and objective functions is extracted using GMDH-ANN. The GMDH-ANN is then coupled with three types of optimization algorithms, among which the Genetic algorithm proves to have the most ideal coupling process for optimization. Finally, after analyzing the variations in the geometry and position of the roof flap from the car roof-end, the roof-flap with specifications of L = 0.1726 m, α = 5.0875°, H = 0.0188 m, and d = 0.241 m can optimize the car drag and lift coefficients by 21.27% and 19.91%, respectively. The present research discusses the opportunities and challenges of optimal design roof-flap geometry and its influence on car aerodynamic performance. Drag coefficient Lift coefficient Roof flap Computational fluid dynamics Artificial neural network Genetic algorithm Motor vehicles. Aeronautics. Astronautics Mohammadreza Baghoolizadeh verfasserin aut S. Mohammad Sajadi verfasserin aut Reza Rostamzadeh-Renani verfasserin aut Narjes Khabazian Azarkhavarani verfasserin aut Soheil Salahshour verfasserin aut Davood Toghraie verfasserin aut In Propulsion and Power Research KeAi Communications Co., Ltd., 2017 13(2024), 1, Seite 26-45 (DE-627)746705905 (DE-600)2716734-3 2212540X nnns volume:13 year:2024 number:1 pages:26-45 https://doi.org/10.1016/j.jppr.2024.02.004 kostenfrei https://doaj.org/article/6b04f31c81264dd5a31991b5a1dd25c7 kostenfrei http://www.sciencedirect.com/science/article/pii/S2212540X24000075 kostenfrei https://doaj.org/toc/2212-540X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2024 1 26-45 |
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A multi-objective and CFD based optimization of roof-flap geometry and position for simultaneous drag and lift reduction |
| abstract |
As the transport sector is responsible for the consumption of a vast proportion of the oil produced, it is mandatory to research feasible solutions to tackle this issue. The application of aerodynamic attachments for passive flow control and reducing resisting aerodynamic forces such as drag and lift is one of the most practicable ways to minimize vehicle energy consumption. The flaps are one of the most innovative aerodynamic attachments that can enhance the flow motion in the boundary layer at the trailing edge of the wings. In the present paper, the flap is designed and modeled for controlling the airflow at the roof-end of a 2D Ahmed body model, inspired by the schematic of the flap at the trailing edge of the wing. As a result, the flap's geometry and position from the roof-end of the car model are parameterized, which leads to having four design variables. The objective functions of the present study are the vehicle's drag coefficient and lift coefficient. 25 Design of Experiment (DOE) points are considered enabling the Box-Behnken method. Then, each DOE point is modeled in the computational domain, and the flow-field around the model is simulated using Ansys Fluent software. The results obtained for the DOE points are employed by different regressors, and the relation between design variables and objective functions is extracted using GMDH-ANN. The GMDH-ANN is then coupled with three types of optimization algorithms, among which the Genetic algorithm proves to have the most ideal coupling process for optimization. Finally, after analyzing the variations in the geometry and position of the roof flap from the car roof-end, the roof-flap with specifications of L = 0.1726 m, α = 5.0875°, H = 0.0188 m, and d = 0.241 m can optimize the car drag and lift coefficients by 21.27% and 19.91%, respectively. The present research discusses the opportunities and challenges of optimal design roof-flap geometry and its influence on car aerodynamic performance. |
| abstractGer |
As the transport sector is responsible for the consumption of a vast proportion of the oil produced, it is mandatory to research feasible solutions to tackle this issue. The application of aerodynamic attachments for passive flow control and reducing resisting aerodynamic forces such as drag and lift is one of the most practicable ways to minimize vehicle energy consumption. The flaps are one of the most innovative aerodynamic attachments that can enhance the flow motion in the boundary layer at the trailing edge of the wings. In the present paper, the flap is designed and modeled for controlling the airflow at the roof-end of a 2D Ahmed body model, inspired by the schematic of the flap at the trailing edge of the wing. As a result, the flap's geometry and position from the roof-end of the car model are parameterized, which leads to having four design variables. The objective functions of the present study are the vehicle's drag coefficient and lift coefficient. 25 Design of Experiment (DOE) points are considered enabling the Box-Behnken method. Then, each DOE point is modeled in the computational domain, and the flow-field around the model is simulated using Ansys Fluent software. The results obtained for the DOE points are employed by different regressors, and the relation between design variables and objective functions is extracted using GMDH-ANN. The GMDH-ANN is then coupled with three types of optimization algorithms, among which the Genetic algorithm proves to have the most ideal coupling process for optimization. Finally, after analyzing the variations in the geometry and position of the roof flap from the car roof-end, the roof-flap with specifications of L = 0.1726 m, α = 5.0875°, H = 0.0188 m, and d = 0.241 m can optimize the car drag and lift coefficients by 21.27% and 19.91%, respectively. The present research discusses the opportunities and challenges of optimal design roof-flap geometry and its influence on car aerodynamic performance. |
| abstract_unstemmed |
As the transport sector is responsible for the consumption of a vast proportion of the oil produced, it is mandatory to research feasible solutions to tackle this issue. The application of aerodynamic attachments for passive flow control and reducing resisting aerodynamic forces such as drag and lift is one of the most practicable ways to minimize vehicle energy consumption. The flaps are one of the most innovative aerodynamic attachments that can enhance the flow motion in the boundary layer at the trailing edge of the wings. In the present paper, the flap is designed and modeled for controlling the airflow at the roof-end of a 2D Ahmed body model, inspired by the schematic of the flap at the trailing edge of the wing. As a result, the flap's geometry and position from the roof-end of the car model are parameterized, which leads to having four design variables. The objective functions of the present study are the vehicle's drag coefficient and lift coefficient. 25 Design of Experiment (DOE) points are considered enabling the Box-Behnken method. Then, each DOE point is modeled in the computational domain, and the flow-field around the model is simulated using Ansys Fluent software. The results obtained for the DOE points are employed by different regressors, and the relation between design variables and objective functions is extracted using GMDH-ANN. The GMDH-ANN is then coupled with three types of optimization algorithms, among which the Genetic algorithm proves to have the most ideal coupling process for optimization. Finally, after analyzing the variations in the geometry and position of the roof flap from the car roof-end, the roof-flap with specifications of L = 0.1726 m, α = 5.0875°, H = 0.0188 m, and d = 0.241 m can optimize the car drag and lift coefficients by 21.27% and 19.91%, respectively. The present research discusses the opportunities and challenges of optimal design roof-flap geometry and its influence on car aerodynamic performance. |
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| title_short |
A multi-objective and CFD based optimization of roof-flap geometry and position for simultaneous drag and lift reduction |
| url |
https://doi.org/10.1016/j.jppr.2024.02.004 https://doaj.org/article/6b04f31c81264dd5a31991b5a1dd25c7 http://www.sciencedirect.com/science/article/pii/S2212540X24000075 https://doaj.org/toc/2212-540X |
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| author2 |
Mohammadreza Baghoolizadeh S. Mohammad Sajadi Reza Rostamzadeh-Renani Narjes Khabazian Azarkhavarani Soheil Salahshour Davood Toghraie |
| author2Str |
Mohammadreza Baghoolizadeh S. Mohammad Sajadi Reza Rostamzadeh-Renani Narjes Khabazian Azarkhavarani Soheil Salahshour Davood Toghraie |
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| up_date |
2024-07-04T00:43:00.461Z |
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