CAD-based Aerodynamic Shape Optimization Using Geometry Surrogate Model And Adjoint Methods

The aerodynamic shape optimization design system was established in this paper. In the system, the RANS equation was used for solving the flowing; the free form deformation (FFD) method was used for the geometry parameterization, and the genetic algorithm was used for the optimization search. For the reducing of the time cost, the Kriging model was used for the surrogate model instead of the CFD simulation during the optimization design. The aerodynamic shape design of a swept wing was presented which used the system, and the result indicated that the 14% drag coefficient was reduced at the cruise conditions, which proved the validity of the system.

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Aerodynamic Shape Optimization Using Feature based CAD Systems and Adjoint Methods

18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference ◽

10.2514/6.2017-3999 ◽

2017 ◽

Cited By ~ 1

Author(s):

Dheeraj Agarwal ◽

Simao Marques ◽

Trevor T. Robinson ◽

Cecil G. Armstrong ◽

Philip Hewitt

Keyword(s):

Shape Optimization ◽

Aerodynamic Shape Optimization ◽

Adjoint Methods ◽

Cad Systems ◽

Aerodynamic Shape ◽

Feature Based

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Surrogate model for aerodynamic shape optimization of a tractor-trailer in crosswinds

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering ◽

10.1177/0954407012442295 ◽

2012 ◽

Vol 226 (10) ◽

pp. 1325-1339 ◽

Cited By ~ 3

Author(s):

Xu Gong ◽

Zhengqi Gu ◽

Zhenlei Li

Keyword(s):

Fluid Dynamics ◽

Computational Fluid Dynamics ◽

Shape Optimization ◽

Drag Coefficient ◽

Surrogate Model ◽

Aerodynamic Drag ◽

Aerodynamic Shape Optimization ◽

Aerodynamic Shape ◽

Design Variables ◽

Aerodynamic Drag Coefficient

A surrogate model-based aerodynamic shape optimization method applied to the wind deflector of a tractor-trailer is presented in this paper. The aerodynamic drag coefficient of the tractor-trailer with and without the wind deflector subjected to crosswinds is analyzed. The numerical results show that the wind deflector can decrease drag coefficient. Four parameters are used to describe the wind deflector geometry: width, length, height, and angle. A 30-level design of experiments study using the optimal Latin hypercube method was conducted to analyze the sensitivity of the design variables and build a database to set up the surrogate model. The surrogate model was constructed based on the Kriging interpolation technique. The fitting precision of the surrogate model was examined using computational fluid dynamics and certified using a surrogate model simulation. Finally, a multi-island genetic algorithm was used to optimize the shape of the wind deflector based on the surrogate model. The tolerance between the results of the computational fluid dynamics simulation and the surrogate model was only 0.92% when using the optimal design variables, and the aerodynamic drag coefficient decreased by 4.65% compared to the drag coefficient of the tractor-trailer installed with the original wind deflector. The effect of the optimal shape of the wind deflector was validated by computational fluid dynamics and wind tunnel experiment.

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