基于离散伴随的高超内转式进气道气动优化设计

doi:10.7527/S1000-6893.2022.28352

Abstract

Abstract:

Despite its relatively good inlet capture ability and high air compression efficiency， the inward turning inlet cannot be locally adjusted in the preliminary design， and improvement in the adverse effects of complex flow structures such as flow separation and secondary flow caused by shock/boundary layer interference is difficult. Therefore， performance optimization is necessary. The current design optimization of the hypersonic inward turning inlet faces many challenges such as the complex profile， large-scale design variables， and the high accuracy requirement of the flowfield numerical simulation. The gradient optimization method based on discrete adjoint is adopted to carry out the aerodynamic design optimization for the inward turning inlet with a wedge forebody. The optimization results show that the undulating shape of the inner and outer compression sections significantly changes the internal shock structure， reduces the wall pressure gradient， and thereby abates the streamwise vortex. In addition， the interference intensity between the shock train and the boundary layer in the isolation section is significantly weakened， inhibiting the expansion of the low energy flow region. Under the design condition， compared with the initial configuration， the aerodynamic performance of the optimized configuration is significantly improved. The total pressure recovery coefficient， the flow coefficient and the pressure ratio at the exit are increased by 8.767%， 0.163%， and 0.763%， respectively， while the drag is reduced by 1.658%.

Key words: hypersonic, inward turning inlet, discrete adjoint, gradient-based optimization, aerodynamic design

CLC Number:

V211.48

Xiaofeng WANG, Feng QU, Junjie FU, Zeyu WANG, Chaoyu LIU, Junqiang BAI. Discrete adjoint-based aerodynamic design optimization for hypersonic inward turning inlet[J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(19): 128352-128352.

Figures/Tables 32

Table 1

Fig.1

Fig.2

Fig.3

Table 2

Computational performances of different dense grids

网格疏密	σ_e	$Δ σ e$ /%	φ_e	$Δ φ e$ /%
疏	0.497 1	-1.564	0.917 0	-0.575
中等密度	0.507 6	0.515	0.922 7	0.043
密	0.505 0	0	0.922 3	0

Table 2

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

Table 3

Table 4

Fig.9

Fig.10

Table 5

Table 6

Table 7

Table 8

Fig.11

Fig.12

Fig.13

Fig.14

Fig.15

Fig.16

Fig.17

Fig.18

Fig.19

Fig.20

Fig.21

Fig.22

Fig.23

Fig.24

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设计变量	伴随方程法/10^-2	有限差分法/10^-2	相对误差/%
1	-1.860 7	-1.861 5	0.043
2	-1.743 3	-1.747 5	0.241
3	-1.214 7	-1.211 2	-0.288
4	-0.71	-0.709 5	-0.070
5	-0.296 9	-0.292 2	-1.583
6	-0.042 9	-0.040 8	-4.895
7	0.292	0.287 2	-1.644
8	0.684 2	0.691 1	1.009
9	0.957 7	0.952	-0.595
10	1.075 6	1.081 5	0.549

设计变量	伴随方程法/10^-3	有限差分法/10^-3	相对误差/%
1	1.404 1	1.348 4	-3.967
2	2.940 8	2.932	-0.299
3	3.811 8	3.843 7	0.837
4	3.774 4	3.855 9	2.159
5	2.831 3	2.887	1.967
6	1.354 9	1.362 6	0.568
7	-0.333 2	-0.329 2	-1.200
8	-1.771 9	-1.809 5	2.122
9	-2.544 4	-2.591 5	1.851
10	-2.658 6	-2.634 3	-0.914

参数	初始构型	优化构型	变化量/%
σ_th	0.701 0	0.697 8	-0.456
φ_th	0.921 9	0.922 5	0.065
P_th/P_∞	24.425	25.393	3.963
Ma_th	3.040 4	3.007 8	-1.072

参数	初始构型	优化构型	变化量/%
σ_e	0.507 6	0.552 1	8.767
φ_e	0.922 7	0.924 2	0.163
P_e/P_∞	28.956	29.177	0.763
Ma_e	2.657 4	2.695 6	1.438

参数	初始构型	优化构型	变化量/%
C_D_，_p	0.006 17	0.006 19	0.324
C_D_，_f	0.003 48	0.003 30	-5.172
C_D	0.009 65	0.009 49	-1.658

Discrete adjoint-based aerodynamic design optimization for hypersonic inward turning inlet

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Ma_∞	参数	初始构型	优化构型	变化量/%
5.5	σ_e	0.540 2	0.552 5	2.277
5.5	φ_e	0.872 4	0.874 2	0.206
5	σ_e	0.578 7	0.589 9	1.935
5	φ_e	0.806 8	0.815 9	1.128

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