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...

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Veröffentlicht in:	Propulsion and Power Research Jg. 13; H. 1; S. 26 - 45
Hauptverfasser:	Rostamzadeh-Renani, Mohammad, Baghoolizadeh, Mohammadreza, Sajadi, S. Mohammad, Rostamzadeh-Renani, Reza, Azarkhavarani, Narjes Khabazian, Salahshour, Soheil, Toghraie, Davood
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Beijing Elsevier B.V 01.03.2024 KeAi Publishing Communications Ltd KeAi Communications Co., Ltd
Schlagworte:	Accessories Aerodynamic coefficients Aerodynamic forces Air flow Artificial neural network Boundary layers Computational fluid dynamics Design of experiments Drag coefficient Drag coefficients Drag reduction Energy consumption Flow control Fossil fuels Genetic algorithm Genetic algorithms Geometry Group method of data handling Lift coefficient Mathematical models Multiple objective analysis Neural networks Optimization Optimization algorithms Reynolds number Roof flap Software Trailing edges Transportation industry Turbines Two dimensional bodies Vehicles Vortices Roof flap Artificial neural network Computational fluid dynamics Lift coefficient Genetic algorithm Drag coefficient
ISSN:	2212-540X, 2097-3454, 2212-540X
Online-Zugang:	Volltext
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