高超声速升力体迎风面精细化降热优化设计

doi:10.7527/S1000-6893.2022.27728

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高超声速升力体迎风面精细化降热优化设计

李昊歌, 杨华(), 杨雨欣, 陈伟芳

浙江大学航空航天学院，杭州 310027

收稿日期:2022-06-30 修回日期:2022-07-28 接受日期:2022-08-24 出版日期:2022-12-25 发布日期:2022-09-13
通讯作者: 杨华 E-mail:yhsaa@zju.edu.cn
基金资助:
国家自然科学基金(U20B2007)

Refinement optimization design for heat reduction on windward surface of hypersonic lifting body

Haoge LI, Hua YANG(), Yuxin YANG, Weifang CHEN

School of Aeronautics and Astronautics，Zhejiang University，Hangzhou 310027，China

Received:2022-06-30 Revised:2022-07-28 Accepted:2022-08-24 Online:2022-12-25 Published:2022-09-13
Contact: Hua YANG E-mail:yhsaa@zju.edu.cn
Supported by:
National Natural Science Foundation of China(U20B2007)

摘要/Abstract

摘要：

高超声速飞行器以小攻角飞行时，由于激波干扰，迎风面沿流向出现条带状高热流区，不利于机体热防护系统的设计。针对在50 km高度以马赫数17攻角 $8 °$ 状态飞行的升力体，开展气动力热综合优化研究。采用连续伴随方法进行气动力热特性参数的物面一阶灵敏度分析，提出结合气动灵敏度的贝塞尔自由变形参数化方法，对控制体和设计空间进行优化调整，进而提升气动全局优化方法。以驻点热流、有效装填空间、升阻比和机体长宽尺寸包络为约束，为满足高超声速飞行器的气动防热和隔热需求，分别以降低迎风面条带热流率和沿展向外推条带位置为目标，对迎风面外形开展单/多目标多约束气动全局优化。采用构建的参数化方法，经单目标寻优，迎风面条带热流峰值的降幅提升36%，条带位置外推量由19.7%提高至21.6%；多目标最优解集的物面热流率整体进一步下降，Pareto前沿收缩并向前推进，更趋最优解，实现了升力体气动力热精细化设计。

关键词: 升力体, 高超声速, 气动设计, 全局优化, 气动热, 灵敏度分析, 参数化

Abstract:

When hypersonic vehicle flies at a certain angle of attack， shock wave interaction causes banded high heat flux regions along the flow direction on the windward surface， imposing an adverse effect on the design of thermal protection systems. We investigate the aerodynamic thermal optimization of a lifting body flying at Mach number of 17 and an angle of attack of 8 $°$ at 50 km altitude. To improve the aerodynamic global optimization design framework， the continuous adjoint method is firstly adopted to analyze the first-order surface sensitivity of aerodynamic force and thermal characteristic parameters， and the Bèzier free-form deformation method for parameterization based on sensitivity analysis is then proposed. Specifically， the control lattice and design space are both adjusted using this method. To meet the aerodynamic heat protection and thermal insulation requirements of hypersonic vehicles， the single and multi-objective aerodynamic global optimization of the windward side shape is performed with the objectives of heat reduction of banded high heat flux regions on the windward side and spanwise movement of the banded regions outwards. The constraints include stagnation heat flux， effective inner volume， lift-to-drag ratio， length and width. After the single-objective optimization， the decline degree of the peak value of the heat flux on the banded region is increased by 36%， and movement of the spanwise location of banded regions is enhanced from 19.7% up to 21.6% using the proposed parameterization method. In terms of multi-objective design， the overall decrease in heat flux of the optimal solution sets is observed using the parameterization method based on sensitivity analysis， and the Pareto front shrinks and advances towards the optimum， achieving the aerodynamic and thermal refinement design of the lifting body.

Key words: lifting body, hypersonic, aerodynamic design, global optimization, aerodynamic heating, sensitivity analysis, parameterization

中图分类号:

V221

李昊歌, 杨华, 杨雨欣, 陈伟芳. 高超声速升力体迎风面精细化降热优化设计[J]. 航空学报, 2022, 43(S2): 124-137.

Haoge LI, Hua YANG, Yuxin YANG, Weifang CHEN. Refinement optimization design for heat reduction on windward surface of hypersonic lifting body[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(S2): 124-137.

图/表 18

表 1

升力体外形网格无关性研究

分析量	网格1	网格2	网格3
第1层网格间距/（10^-6 m）	1	5	10
升力系数C_L	0.175 8	0.176 7	0.177 1
阻力系数C_D	0.065 6	0.065 7	0.065 8
升阻比L/D	2.680	2.690	2.693
翼前缘局部高热流率峰值/（ $k W ⋅ m - 2$ ）	1 000	1 015	1 026

表 1

图 1

图 2

图 3

图 4

图 5

图 6

图 7

图 8

图 9

表 2

表 3

图 10

表 4

图 11

图 12

表 5

图 13

参考文献 41

1	安复兴, 李磊, 苏伟, 等. 高超声速飞行器气动设计中的若干关键问题[J]. 中国科学: 物理学力学天文学, 2021, 51(10): 6-25.
	AN F X, LI L, SU W, et al. Key issues in hypersonic vehicle aerodynamic design[J]. Scientia Sinica (Physica, Mechanica ＆ Astronomica), 2021, 51(10): 6-25 (in Chinese).
2	LANDON M, HALL D, UDY J, et al. Automatic supersonic/hypersonic aerodynamic shape optimization: AIAA-1994-1898[R]. Reston: AIAA, 1994.
3	ZHANG B, FENG Z W, XU B T, et al. Efficient aerodynamic shape optimization of the hypersonic lifting body based on free form deformation technique[J]. IEEE Access, 7: 147991-148003.
4	ZHANG T T, WANG Z G, HUANG W, et al. Parameterization and optimization of hypersonic-gliding vehicle configurations during conceptual design[J]. Aerospace Science and Technology, 2016, 58: 225-234.
5	夏陈超. 基于CFD的飞行器高保真度气动外形优化设计方法[D]. 杭州: 浙江大学, 2016: 124-128.
	XIA C C. High-fidelity aerodynamic shape optimization method of aircraft based on computational fluid dynamics[D]. Hangzhou: Zhejiang University, 2016: 124-128 (in Chinese).
6	MA Y, YANG T, FENG Z W, et al. Hypersonic lifting body aerodynamic shape optimization based on the multiobjective evolutionary algorithm based on decomposition[J]. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2015, 229(7): 1246-1266.
7	DI GIORGIO S, QUAGLIARELLA D, PEZZELLA G, et al. An aerothermodynamic design optimization framework for hypersonic vehicles[J]. Aerospace Science and Technology, 2019, 84: 339-347.
8	王荣, 张学军, 纪楚群, 等. 基于高效数值方法的一种高超声速飞行器外形气动力/热综合优化设计研究[J]. 空气动力学学报, 2014, 32(5): 618-622, 633.
	WANG R, ZHANG X J, JI C Q, et al. Aerodynamic heat and force optimization for a hypersonic vehicle based on effective space marching and stream trace methods[J]. Acta Aerodynamica Sinica, 2014, 32(5): 618-622, 633 (in Chinese).
9	冯毅, 刘深深, 卢风顺, 等. 一种可重复使用天地往返升力体飞行器概念及其气动布局优化设计研究[J]. 空气动力学学报, 2017, 35(4): 563-571.
	FENG Y, LIU S S, LU F S, et al. Study on a new RLV lifting body concept and its aerodynamic configuration optimization design[J]. Acta Aerodynamica Sinica, 2017, 35(4): 563-571 (in Chinese).
10	EYI S N. Aerothermodynamic design optimization in hypersonic flows[C]∥49th AIAA/ASME/SAE/ASEE Joint Propulsion Conference. Reston: AIAA, 2013.
11	EYI S N, HANQUIST K M, BOYD I D. Shape optimization of reentry vehicles to minimize heat loading: AIAA-2019-0973[R]. Reston: AIAA, 2019.
12	INGER G R. Non-equilibrium boundary layer effects on the aerodynamic heating of hypersonic vehicles[J]. Acta Astronautica, 1995, 36(4): 205-216.
13	XIA C C, TAO Y P, JIANG T T, et al. Multiobjective shape optimization of a hypersonic lifting body using a correlation-based transition model[J]. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2016, 230(12): 2220-2232.
14	ATKINSON M, POGGIE J, CAMBEROS J. Hypersonic flow computations for an elliptic cone at high angle of incidence[J]. Journal of Spacecraft and Rockets, 2012, 49(3): 496-506.
15	MASTERS D A, POOLE D J, TAYLOR N J, et al. Impact of shape parameterisation on aerodynamic optimisation of benchmark problem: AIAA-2016-1544[R]. Reston: AIAA, 2016.
16	JAMESON A. Aerodynamic shape optimization using the adjoint method[R]. Lectures at the Von Karman Institute. Brussels, 2003.
17	COPELAND S R, PALACIOS F, ALONSO J J. Adjoint-based aerothermodynamic shape design of hypersonic vehicles in non-equilibrium flows: AIAA-2014-0513[R]. Reston: AIAA, 2014.
18	EYI S N, YUMUŞAK M. Aerothermodynamic shape optimization of hypersonic blunt bodies[J]. Engineering Optimization, 2015, 47(7): 909-926.
19	EYI S N, HANQUIST K M, BOYD I D. Aerothermodynamic design optimization of hypersonic vehicles[J]. Journal of Thermophysics and Heat Transfer, 2018, 33(2): 392-406.
20	KIM J H, KIM J W, KIM K Y. Axial-flow ventilation fan design through multi-objective optimization to enhance aerodynamic performance[J]. Journal of Fluids Engineering, 2011, 133(10): 101101.
21	CATALANO L A, QUAGLIARELLA D, VITAGLIANO P L. Aerodynamic shape design using hybrid evolutionary computing and multigrid-aided finite-difference evaluation of flow sensitivities[J]. Engineering Computations, 2015, 32(2): 178-210.
22	韩忠华, 许晨舟, 乔建领, 等. 基于代理模型的高效全局气动优化设计方法研究进展[J]. 航空学报, 2020, 41(5): 623344.
	HAN Z H, XU C Z, QIAO J L, et al. Recent progress of efficient global aerodynamic shape optimization using surrogate-based approach[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(5): 623344 (in Chinese).
23	韩忠华. Kriging模型及代理优化算法研究进展[J]. 航空学报, 2016, 37(11): 3197-3225.
	HAN Z H. Kriging surrogate model and its application to design optimization: A review of recent progress[J]. Acta Aeronautica et Astronautica Sinica, 2016, 37(11): 3197-3225 (in Chinese).
24	CHUNG H S, ALONSO J. Using gradients to construct cokriging approximation models for high-dimensional design optimization problems: AIAA-2002-0317[R]. Reston: AIAA, 2002.
25	LAURENCEAU J, SAGAUT P. Building efficient response surfaces of aerodynamic functions with kriging and cokriging[J]. AIAA Journal, 2008, 46(2): 498-507.
26	KIM K H, KIM C, RHO O H. Methods for the accurate computations of hypersonic flows[J]. Journal of Computational Physics, 2001, 174(1): 38-80.
27	POOLE D J, ALLEN C B, RENDALL T. Control point-based aerodynamic shape optimization applied to AIAA ADODG test cases: AIAA-2015-1947[R]. Reston: AIAA, 2015.
28	POOLE D J, ALLEN C B, RENDALL T. Application of control point-based aerodynamic shape optimization to two-dimensional drag minimization: AIAA-2014-0413[R]. Reston: AIAA, 2014.
29	POOLE D J, ALLEN C B, RENDALL T. A constrained global optimization framework: AIAA-2014-2034[R]. Reston: AIAA, 2014.
30	于广元. 基于自由变形技术的伴随方法优化设计大曲率扩压通道[D]. 南京: 南京航空航天大学, 2014: 133.
	YU G Y. Aerodynamic design of large curvature diffuser channel by using adjoint method based on FFD technique[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2014: 133 (in Chinese).
31	孙岩松. 带几何约束条件的空间变形方法[D]. 大连: 大连理工大学, 2002: 67.
	SUN Y S. Spatial deformation method with geometric constraints[D]. Dalian: Dalian University of Technology, 2002: 67 (in Chinese).
32	唐静, 邓有奇, 马明生, 等. 飞翼气动优化中参数化和网格变形技术[J]. 航空学报, 2015, 36(5): 1480-1490.
	TANG J, DENG Y Q, MA M S, et al. Parameterization and grid deformation techniques for flying-wing aerodynamic optimization[J]. Acta Aeronautica et Astronautica Sinica, 2015, 36(5): 1480-1490 (in Chinese).
33	TASHNIZI E S, TAHERI A A, HEKMAT M H. Investigation of the adjoint method in aerodynamic optimization using various shape parameterization techniques[J]. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2010, 32(2): 176-186.
34	LUKACZYK T W, CONSTANTINE P, PALACIOS F, et al. Active subspaces for shape optimization: AIAA-2014-1171[R]. Reston: AIAA, 2014.
35	LI H G, LI C R, CHEN W F, et al. Sensitivity-based parameterization for aerodynamic shape global optimization[J]. Journal of Aerospace Engineering, 2022, 35(2): 4021127.
36	SRINATH D N, MITTAL S. Optimal airfoil shapes for low Reynolds number flows[J]. International Journal for Numerical Methods in Fluids, 2009, 61(4): 355-381.
37	JEONG S, OBAYASHI S, YAMAMOTO K. A Kriging-based probabilistic optimization method with an adaptive search region[J]. Engineering Optimization, 2006, 38(5): 541-555.
38	VERMA S, PANT M, SNASEL V. A comprehensive review on NSGA-Ⅱ for multi-objective combinatorial optimization problems[J]. IEEE Access, 9: 57757-57791.
39	HUANG J, YAO W X. Multi-objective design optimization of blunt body with spike and aerodisk in hypersonic flow[J]. Aerospace Science and Technology, 2019, 93: 105122.
40	夏陈超, 邵纯, 姜婷婷, 等. 基于FFD方法的高超声速升力体气动优化[J]. 固体火箭技术, 2015, 38(6): 751-756.
	XIA C C, SHAO C, JIANG T T, et al. Aerodynamic optimization of hypersonic lifting body based on FFD method[J]. Journal of Solid Rocket Technology, 2015, 38(6): 751-756 (in Chinese).
41	YANG F, CHEN Z L. Multi-objective aerodynamic optimization using active multi-output Gaussian process and mesh deformation method[J]. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2022, 236(4): 767-776.

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

变量	下限	上限
V（1）	1.016	1.011
V（2）	1.045	1.033
V（3）	1.043	1.027
V（4）	1.107	1.063
V（5）	1.161	1.087
V（6）	1.052	1.068
V（7）	1.101	1.101
V（8）	1.119	1.117
V（9）	1.347	1.344
V（10）	1.500	1.500

气动特性参数	优化外形		相对初始外形/%
气动特性参数	均布控制体	SCHI	相对初始外形/%
Q_a	163.1	158.0	-10.8
L/D	2.685	2.695	0.2
Q_s	5 948.3	5 948.0	0.1
Q_max，1	212.5	200.7	-1.7
Q_max，2	172.6	165.4	-5.2
Q_max，3	143.1	139.9	-15.2
Q_max，4	124.2	126.0	-23.6

气动特性参数	优化外形		相对初始外形/%
气动特性参数	均布控制体	SCHI	相对初始外形/%
z_a/m	0.244	0.248	21.6
L/D	2.694	2.695	0.2
Q_s/（kW·m^-2）	5 991.9	5 992.6	-0.3
z₁/m	0.254	0.254	10.6
z₂/m	0.252	0.252	22.0
z₃/m	0.243	0.243	30.3
z₄/m	0.227	0.244	26.4

优化目标和约束	初始外形	外形1	外形2	外形3
L/D	2.690	2.698	2.699	2.685
Q_s/（kW·m^-2）	5 941.0	5 922.6	5 921.4	5 933.1
V/m³	0.741	0.752	0.750	0.749
Q_a/（kW·m^-2）	177.1	172.2	168.5	161.2
z_a^*/m	0.204	0.244	0.238	0.227

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高超声速升力体迎风面精细化降热优化设计

Refinement optimization design for heat reduction on windward surface of hypersonic lifting body

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