TY - JOUR
T1 - Multi-objective aerodynamic optimization of two-dimensional hypersonic forebody-inlet based on the heuristic algorithm
AU - Fu, Junjie
AU - Qu, Feng
AU - Liu, Qingsong
AU - Sun, Di
AU - Bai, Junqiang
N1 - Publisher Copyright:
© 2022 Elsevier Masson SAS
PY - 2022/4
Y1 - 2022/4
N2 - Nowadays, the forebody-inlet integrated design optimization becomes more and more important in improving the performance of hypersonic vehicles. And several achievements have been made to improve the performance of the two-dimensional hypersonic forebody-inlet integrated vehicle. However, all these works are faced with many defects. For example, the work adopting the gradient algorithm is easy to be trapped in the local optimum solution. The data-driven optimization method is with a low level of accuracy. Moreover, the geometry parameterization methods adopted in those optimization procedures are hardly implemented to complex configurations. In this study, a global-searching multi-objective optimization framework is proposed to overcome these limitations and to carry out multi-objective optimization of the two-dimensional hypersonic forebody-inlet shape. The framework includes the Free-Form Deformation (FFD) method, the mesh deformation method, the high-accuracy Reynolds Averaged Navier-Stokes (RANS) solver, and the global-searching heuristic algorithm. Results obtained by this framework indicate that the total pressure recovery coefficient, the pressure rising ratio, and the mass flow coefficient are increased by 3.97%, 9% and 7.35%, respectively, which suggests that the optimization framework proposed in this study is promising to be widely used in practical engineering applications.
AB - Nowadays, the forebody-inlet integrated design optimization becomes more and more important in improving the performance of hypersonic vehicles. And several achievements have been made to improve the performance of the two-dimensional hypersonic forebody-inlet integrated vehicle. However, all these works are faced with many defects. For example, the work adopting the gradient algorithm is easy to be trapped in the local optimum solution. The data-driven optimization method is with a low level of accuracy. Moreover, the geometry parameterization methods adopted in those optimization procedures are hardly implemented to complex configurations. In this study, a global-searching multi-objective optimization framework is proposed to overcome these limitations and to carry out multi-objective optimization of the two-dimensional hypersonic forebody-inlet shape. The framework includes the Free-Form Deformation (FFD) method, the mesh deformation method, the high-accuracy Reynolds Averaged Navier-Stokes (RANS) solver, and the global-searching heuristic algorithm. Results obtained by this framework indicate that the total pressure recovery coefficient, the pressure rising ratio, and the mass flow coefficient are increased by 3.97%, 9% and 7.35%, respectively, which suggests that the optimization framework proposed in this study is promising to be widely used in practical engineering applications.
KW - Forebody-inlet
KW - Free-Form Deformation method
KW - Heuristic algorithm
KW - Multi-objective optimization
UR - http://www.scopus.com/inward/record.url?scp=85126545055&partnerID=8YFLogxK
U2 - 10.1016/j.ast.2022.107470
DO - 10.1016/j.ast.2022.107470
M3 - 文章
AN - SCOPUS:85126545055
SN - 1270-9638
VL - 123
JO - Aerospace Science and Technology
JF - Aerospace Science and Technology
M1 - 107470
ER -