Aerodynamic Shape Design of Hypersonic Vehicles via Interval-Robust Optimization Method Including Geometric Tolerances and Multiple Flight Conditions

2021 ◽  
Vol 34 (3) ◽  
pp. 04021017
Author(s):  
Yuning Zheng
Keyword(s):  
Robust Optimization ◽  
Optimization Method ◽  
Shape Design ◽  
Hypersonic Vehicles ◽  
Aerodynamic Shape ◽  
Geometric Tolerances

Comparison of optimization algorithms for aerodynamic shape design

AIAA Journal ◽  
1997 ◽  
Vol 35 ◽  
pp. 1413-1415
Author(s):  
Shigeru Obayashi ◽  
Takanori Tsukahara
Keyword(s):  
Optimization Algorithms ◽  
Shape Design ◽  
Aerodynamic Shape

Shape-design optimization of hull structures considering thermal deformation

2013 ◽  
Vol 228 (13) ◽  
pp. 2266-2277
Author(s):  
Myung-Jin Choi ◽  
Min-Geun Kim ◽  
Seonho Cho
Keyword(s):  
Optimal Design ◽  
Design Optimization ◽  
Thermal Deformation ◽  
Parametric Design ◽  
Optimization Method ◽  
Optimization Process ◽  
Design Parameters ◽  
Shape Design ◽  
Shape Design Optimization ◽  
Modified Method

We developed a shape-design optimization method for the thermo-elastoplasticity problems that are applicable to the welding or thermal deformation of hull structures. The point is to determine the shape-design parameters such that the deformed shape after welding fits very well to a desired design. The geometric parameters of curved surfaces are selected as the design parameters. The shell finite elements, forward finite difference sensitivity, modified method of feasible direction algorithm and a programming language ANSYS Parametric Design Language in the established code ANSYS are employed in the shape optimization. The objective function is the weighted summation of differences between the deformed and the target geometries. The proposed method is effective even though new design variables are added to the design space during the optimization process since the multiple steps of design optimization are used during the whole optimization process. To obtain the better optimal design, the weights are determined for the next design optimization, based on the previous optimal results. Numerical examples demonstrate that the localized severe deviations from the target design are effectively prevented in the optimal design.

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