基于引气控制的热气防冰优化设计方法

doi:10.7527/S1000-6893.2023.29285

Abstract

Abstract:

In-flight icing occurs on wings and engine inlets when aircraft fly through clouds containing supercooled water droplets， which is detrimental to flight safety. Hot air anti-icing is one of the most widely used anti-icing technologies. To ensure that anti-icing requirements are met with lower bleed air quantities， an optimization design method based on bleed air control for hot air anti-icing system is developed. A fast prediction method for hot air anti-icing performance based on Proper Orthogonal Decomposition and Radial Basis Function neural networks is constructed， enabling rapid evaluation of the surface temperature and runback water mass flow rate distributions for different anti-icing configurations within the anti-icing optimization design space. Genetic algorithms and Nondominated Sorting Genetic Algorithms are employed for the single- and multi-objective optimization problems of the hot air anti-icing system. The fast prediction method for hot air anti-icing performance is used to evaluate the objective and constraint functions of individuals in the population. While satisfying the constraint functions of the optimization problem， the single-objective optimized design can reduce the required bleed air quantity by 23.41% compared to the baseline design. The multi-objective optimization design produces a series of optimized anti-icing configurations， and the design engineers can choose the most suitable anti-icing configuration design by evaluating the weights of both bleed air reduction and anti-icing performance enhancement.

Key words: hot air anti-icing, anti-icing performance fast prediction, genetic algorithm, single-objective optimization design, multi-objective optimization design

CLC Number:

Qian YANG, Haoran ZHENG, Xianda CHENG, Wei DONG. Optimization design method for hot air anti⁃icing system based on bleed air control[J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(S2): 729285-729285.

Figures/Tables 12

Fig.1

Table 1

Fig.2

Table 2

Training samples

编号	L/mm	x_pic/mm	y_pic/mm	θ₀/（°）	θ₁/（°）
1	26.38	19.475	-1.94	13.00	32.075
2	31.78	9.725	-5.02	11.80	43.425
3	39.86	-4.925	1.46	1.00	25.175
$⋮$	$⋮$	$⋮$	$⋮$	$⋮$	$⋮$
500	30.98	10.575	7.14	5.48	28.875

Table 2

Table 3

Testing samples

编号	L/mm	x_pic/mm	y_pic/mm	θ₀/（°）	θ₁/（°）
1	31.3	4.875	-8.7	15.4	33.625
2	36.1	17.125	-4.7	-12.2	35.375
3	20.5	7.375	0.1	11.8	34.875
$⋮$	$⋮$	$⋮$	$⋮$	$⋮$	$⋮$
100	35.9	-1.625	-4.5	-6.2	44.375

Table 3

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

Fig.9

References 23

1	桂业伟，周志宏，李颖晖，等. 关于飞机结冰的多重安全边界问题［J］. 航空学报， 2017， 38（2）： 520734.
	GUI Y W， ZHOU Z H， LI Y H， et al. Multiple safety boundaries protection on aircraft icing［J］. Acta Aeronautica et Astronautica Sinica， 2017， 38（2）： 520734 （in Chinese）.
2	LYNCH F T， KHODADOUST A. Effects of ice accretions on aircraft aerodynamics［J］. Progress in Aerospace Sciences， 2001， 37（8）： 669-767.
3	周莉，徐浩军，龚胜科，等. 飞机结冰特性及防除冰技术研究［J］. 中国安全科学学报， 2010， 20（6）： 105-110.
	ZHOU L， XU H J， GONG S K， et al. Research of aircraft icing characteristics and anti-icing and de-icing technology［J］. China Safety Science Journal （CSSJ）， 2010， 20（6）： 105-110 （in Chinese）.
4	陈勇，孔维梁，刘洪. 飞机过冷大水滴结冰气象条件运行设计挑战［J］. 航空学报， 2023， 44（1）： 626973.
	CHEN Y， KONG W L， LIU H. Challenge of aircraft design under operational conditions of supercooled large water droplet icing［J］. Acta Aeronautica et Astronautica Sinica， 2023， 44（1）： 626973 （in Chinese）.
5	GUO Z Q， GUO X F， YANG Q， et al. Heat transfer characteristics of unexpanded jet impingement in piccolo hot air anti-icing chamber［J］. Applied Thermal Engineering， 2022， 200： 117540.
6	PAPADAKIS M， WONG S H， YEONG H W， et al. Icing tunnel experiments with a hot air anti-icing system： AIAA-2008-0444［R］. Reston： AIAA， 2008.
7	GUO Z Q， ZHENG M， YANG Q， et al. Effects of flow parameters on thermal performance of an inner-liner anti-icing system with jets impingement heat transfer［J］. Chinese Journal of Aeronautics， 2021， 34（9）： 119-132.
8	CABLER S. Aircraft Ice Protection： AC_20-73A［R］. Federal Aviation Administration， 2016.
9	SANTOS L， DOMINGOS R， MARIA R， et al. Sensitivity analysis of a bleed air anti-ice thermal model to geometrical and operational parameters： AIAA-2008-0445［R］. Reston： AIAA， 2008.
10	杨倩，郭晓峰，李芹，等. 基于POD和代理模型的热气防冰性能预测方法［J］. 航空学报， 2023， 44（1）： 626992.
	YANG Q， GUO X F， LI Q， et al. Hot air anti-icing performance estimation method based on POD and surrogate model［J］. Acta Aeronautica et Astronautica Sinica， 2023， 44（1）： 626992 （in Chinese）.
11	PELLISSIER M P C， HABASHI W G， PUEYO A. Optimization via FENSAP-ICE of aircraft hot-air anti-icing systems［J］. Journal of Aircraft， 2011， 48（1）： 265-276.
12	NIU J， SANG W， QIU A， et al. An optimization of anti-icing chamber based on POD and KRIGING［C］∥32nd Congress of the International Council of the Aeronautical Sciences. Washington，D.C.： ICAS， 2020：1132.
13	CARDOSO J M P， COUTINHO J G F， DINIZ P C. Embedded computing for high performance： Efficient mapping of computations using customization， code transformations and compilation［M］. Cambridge： Morgan Kaufmann Publishers， an imprint of Elsevier， 2017.
14	NAYAK S. Fundamentals of optimization techniques with algorithms［M］. Pittsburgh： Academic Press， 2020.
15	SIROVICH L. Turbulence and the dynamics of coherent structures. Ⅰ. Coherent structures［J］. Quarterly of Applied Mathematics， 1987， 45（3）： 561-571.
16	SIROVICH L. Turbulence and the dynamics of coherent structures. Ⅱ. Symmetries and transformations［J］. Quarterly of Applied Mathematics， 1987， 45（3）： 573-582.
17	SIROVICH L. Turbulence and the dynamics of coherent structures. Ⅲ. Dynamics and scaling［J］. Quarterly of Applied Mathematics， 1987， 45（3）： 583-590.
18	MOODY J， DARKEN C J. Fast learning in networks of locally-tuned processing units［J］. Neural Computation， 1989， 1（2）： 281-294.
19	XIE T T， YU H， WILAMOWSKI B. Comparison between traditional neural networks and radial basis function networks［C］∥ 2011 IEEE International Symposium on Industrial Electronics. Piscataway： IEEE Press， 2011： 1194-1199.
20	MCKAY M D， BECKMAN R J， CONOVER W J. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code［J］. Technometrics， 2000， 42（1）： 55-61.
21	MORRIS M D， MITCHELL T J. Exploratory designs for computational experiments［J］. Journal of Statistical Planning and Inference， 1995， 43（3）： 381-402.
22	YANG Q， GUO X F， ZHENG H R， et al. Single- and multi-objective optimization of an aircraft hot-air anti-icing system based on Reduced Order Method［J］. Applied Thermal Engineering， 2023， 219： 119543.
23	CHRISTENSEN E A， BRØNS M， SØRENSEN J N. Evaluation of proper orthogonal decomposition： based decomposition techniques applied to parameter-dependent nonturbulent flows［J］. SIAM Journal on Scientific Computing， 1999， 21（4）： 1419-1434.

设计参数	基础设计	参数取值区间
L/mm	30	［20， 40］
x_pic/mm	0	［5， 20］
y_pic/mm	0	［-10， 10］
θ₀/（°）	0	［-20， 20］
θ₁/（°）	45	［20， 45］

[1]	Zhuangzhuang CUI, Xin YUAN, Guoqing ZHAO, Simeng JING, Qijun ZHAO. Influence of control strategy on forward flight performance of coaxial rigid rotor high⁃speed helicopters [J]. Acta Aeronautica et Astronautica Sinica, 2024, 45(9): 529256-529256.
[2]	Wenjun DING, Yajun CHAI, Dongdong HOU, Chiyu WANG, Guozong ZHANG, Zhaoyong MAO. Path planning for AUV&UAV cross⁃domain collaborative search and tracking [J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(21): 528471-528471.
[3]	Wenhao BI, Jiuli ZHOU, Xiaobo DUAN, An ZHANG, Shuangfei XU. Optimal fire distribution method of small diameter guided bomb in air-to-surface strike based on multi-factor modified NSGA-Ⅱ [J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(17): 328116-328116.
[4]	Bin WANG, Jianjun ZHENG, Wei LIU, Gaoli WANG. Testing load transacting method based on assessment target equivalent [J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(17): 228064-228064.
[5]	Qian YANG, Xiaofeng GUO, Qin LI, Wei DONG. Hot air anti-icing performance estimation method based on POD and surrogate model [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023, 44(1): 626992-626992.
[6]	HAN Kai, DONG Richang, SHAO Fengwei, GONG Wenbin, CHANG Jiachao. Dynamic topology optimization of navigation satellite inter-satellite links network based on improved genetic algorithm [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(9): 326095-326095.
[7]	HU Jiaxin, RUI Shu, GAO Ruichao, GOU Jianjun, GONG Chunlin. Hybrid optimization method for structural layout and size of flight vehicles [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(5): 225363-225363.
[8]	DUAN Yanhui, ZHOU Xin, GAO Shijiexi, LIN Jinxing, ZHANG Huaibao, WANG Guangxue. Two-step optimal strategy for load balancing of structured grid [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(9): 625751-625751.
[9]	ZHONG Yun, WAN Lujun, ZHANG Jieyong. Optimized selection method for air combat course of action with interval uncertainty [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(2): 324282-324282.
[10]	HE Cheng, MA Dongli, JIA Yuhong, YANG Muqing, CHEN Gang. Multi-objective optimization design for joined-wing SensorCraft [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(12): 224761-224761.
[11]	ZOU Shiyu, LI Fuming, XIE Aiping, ZHOU Tao, LIU Peng. Resource allocation based on improved fireworks algorithm [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(12): 324716-324716.
[12]	LIU Jixin, JIANG Hao, DONG Xinfang, LAN Sijie, WANG Haozhe. Dynamic collaborative sequencing method for arrival flights based on air traffic density [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(7): 323717-323717.
[13]	GU Wenting, ZHAO Zhenshan, ZHOU Hanwei, FENG Jian, TAN Zhaoguang, LI Dong. Powered-on nacelle design on blended-wing-body configuration with podded engines [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2019, 40(9): 623047-623047.
[14]	WU Ke, ZHANG Huazhen, LAN Lan, ZHOU Yang. Shape active control of a CFRP reflector and placement optimization of actuator [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2019, 40(7): 222751-222751.
[15]	ZHANG Jing, HE You, PENG Yingning, LI Gang. Neural network and artificial potential field based cooperative and adversarial path planning [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2019, 40(3): 322493-322493.

Optimization design method for hot air anti⁃icing system based on bleed air control

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 12

References 23

Related Articles 15

Recommended Articles

Metrics

Comments