基于遗传/梯度混合优化策略的高超内转式进气道设计方法

doi:10.7527/S1000-6893.2024.30808

Abstract

Abstract:

The hypersonic inward-turning inlet has attracted wide attention because of its higher compression efficiency and larger flow coefficient. Nowadays， traditional design methods cannot achieve the optimal performance of the inlet. Therefore， coupling the genetic algorithm and the gradient algorithm， this paper proposes a new design method for the hypersonic inward-turning inlet based on the hybrid optimization strategy， and completes the design of the inlet at Mach number 6. Firstly， the global configuration design of the basic flowfield is conducted using genetic optimization， resulting in a Pareto front of basic flowfields with good performance. Among them， a typical dual-shock wave basic flowfield is selected to design the dual-shock wave inward-turning inlet. Secondly， the refined shape design of the above inlet is carried out based on adjoint gradient optimization， which further improves the performance of the inlet. Consequently， compared to inward-turning inlets designed using the traditional forward design methods， the performance of the inlet constructed by the design method is significantly improved. The flow coefficient， total pressure recovery coefficient and pressure rising ratio are increased by 2.33%， 13.15% and 7.90%， respectively， and the distortion coefficient （DC₆₀） is reduced by 3.70%. During the global configuration design， the overall parameters of the basic flowfield， such as the radius of the center body and outlet， are designed to obtain the optimal-performing global configuration of basic flowfield. During the refined shape design， the fluctuations of the inlet surface improve the mass capture performance and compression capability of the shock wave in the isolation section. In addition， the surface deformation also weakens the total pressure loss caused by the second incident shock wave， the development of streamwise vortexes and the flow separation induced by shock-wave/turbulent-layer interaction in the isolation section. Furthermore， the weakening of streamwise vortexes and flow separation results in the reduction of total pressure loss in the isolation section and the improvement of flow uniformity on the outflow boundary.

Key words: hypersonic, inward-turning inlet, genetic algorithm, gradient-based optimization, basic flowfield

CLC Number:

V211.48

Jun CHEN, Feng QU, Junjie FU. Design method of hypersonic inward turning inlet based on genetic and gradient hybrid optimization strategy[J]. Acta Aeronautica et Astronautica Sinica, 2025, 46(3): 130808.

Figures/Tables 39

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References 43

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构型	CR	CRI	σ_i	p_i/p₀	Ma_i	σ_o	p_o/p₀	Ma_o
ori	4.53	1.59	0.917 3	4.88	4.521	0.913 5	10.28	3.975
opt1	4.61	1.41	0.959 0	5.85	4.411	0.954 1	10.22	4.008
opt2	4.74	1.51	0.935 6	5.45	4.447	0.940 0	10.48	3.968
opt1相对ori参数变化/%	1.72	-11.1	4.54	19.9	-2.43	4.45	-0.59	0.83
opt2相对ori参数变化/%	4.61	-4.91	1.99	11.7	-1.63	2.90	1.96	-0.18

构型	a/mm	L/mm	d/mm	l/mm	CR_inlet	CRI_inlet
Inlet_ori	200	1 873	66.50	664.6	5.65	2.01
Inlet_opt1	200	1 856	66.18	661.8	5.70	1.76
Inlet_opt2	200	1 797	68.95	689.5	5.25	1.83

网格	φ	Δ₁/%	σ_out	Δ₂/%	p_out/p₀	Δ₃/%	Ma_out	Δ₄/%
疏	0.966 8	-0.98	0.515 0	-3.44	23.59	1.34	2.779	-1.37
中	0.975 2	-0.13	0.531 7	-0.32	23.30	0.10	2.814	-0.12
密	0.976 4	0	0.533 4	0	23.27	0	2.818	0

构型	φ	σ_th	p_th/p₀	Ma_th	σ_out	p_out/p₀	Ma_out	DC₆₀
Inlet_ori	0.975 2	0.696 6	19.10	3.191	0.531 7	23.30	2.814	4.27
Inlet_opt1	0.965 4	0.736 5	19.87	3.215	0.553 1	23.18	2.841	4.88
Inlet_opt2	0.977 3	0.734 9	17.78	3.319	0.548 8	20.25	2.934	5.23
opt1相对ori参数变化/%	-1.00	5.73	4.03	0.75	4.02	-0.52	0.96	14.13
opt2相对ori参数变化/%	0.22	5.50	-6.91	4.01	3.22	-13.09	4.26	22.32

构型	φ	σ_th	p_th/p₀	Ma_th	σ_out	p_out/p₀	Ma_out	DC₆₀
Inlet_ori	0.780 0	0.799 0	15.26	1.95	0.677 2	16.67	1.78	1.37
Inlet_opt1	0.768 3	0.966 3	12.11	3.71	0.686 8	16.41	1.80	1.55
Inlet_opt2	0.784 3	0.824 2	12.84	2.09	0.695 4	14.23	1.90	1.62
opt1相对ori参数变化/%	-1.49	20.94	-86.18	89.83	1.42	-1.58	0.90	13.54
opt2相对ori参数变化/%	0.55	3.15	-15.84	6.84	2.69	-14.67	6.63	18.05

Design method of hypersonic inward turning inlet based on genetic and gradient hybrid optimization strategy

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构型	Ma₀	φ	σ_th	p_th/p₀	Ma_th	σ_out	p_out/p₀	Ma_out	DC₆₀
Inlet_opt3	6	0.997 9	0.767 1	16.96	3.338	0.601 6	25.14	2.848	4.11
Inlet_opt3	4	0.811 6	0.966 1	2.12	3.71	0.672 9	18.54	1.71	1.38
Inlet_opt3相对Inlet_opt1的参数变化/%	6	3.37	4.15	-14.65	3.83	8.77	8.46	0.25	-15.63
Inlet_opt3相对Inlet_opt1的参数变化/%	4	5.64	-0.02	0.46	-0.04	-2.02	12.96	-4.96	-11.43
Inlet_opt3相对Inlet_ori的参数变化/%	6	2.33	10.12	-11.20	4.61	13.15	7.90	1.21	-3.70
Inlet_opt3相对Inlet_ori的参数变化/%	4	4.06	20.91	-86.12	89.75	-0.63	11.17	-4.10	0.56

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