通用飞行器气动优化设计数字化集成平台——DIPasda

doi:10.7527/S1000-6893.2019.23348

Abstract

Abstract: The development of the future aviation industry needs to solve the key problems of multidisciplinary integrated design and provide a powerful design method and tools for the design of new high-performance aircraft. This paper presents an automated digitalized integrated platform for aerodynamics synthetic design and assessment (DIPasda) for complex shape. Our goal is to present a new general-purpose, robust, and efficient optimization platform which is aimed at real-life constrained designs where the conventional design approaches are complicated and time-consuming. The DIPasda system consists of a collection of functional modules for performance design and optimization studies by numerical optimization schemes, geometry parameterization techniques, surrogate models, high-fidelity computational analysis tools for different disciplines and so on. By introducing the system architecture of the platform in detail, the main functional modules, adjoint optimization, and multi-objective optimization process, the flexibility of the system architecture design and the completeness of the functional modules are demonstrated. At last, optimization tests are presented to show the system's design optimization capability.

Key words: aerodynamic design, optimization platform, coupling adjoint optimization, evolutionary algorithm, multi-objective optimization, multidiscipline optimization

CLC Number:

V211.3

SUN Junfeng, ZHOU Zhu, HUANG Yong, PANG Yufei, LU Fengshun, XU Yong. Digital integrated platform for universal aircraft aerodynamic design optimization: DIPasda[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(5): 623348-623348.

References 24

[1]	MOHAMMD A Z, BREZILLON J. Shape optimization using the aero-structural coupled adjoint approach for viscous flow[C]//Proceedings of Evolutionary and Deterministic for Design, Optimization and Control, 2011.
[2]	LEOVIRIYAKIT K, JAMESON A. Case studies in aero-structural wing planform and section optimization:AIAA-2004-5372[R]. Reston, VA:AIAA, 2004.
[3]	MELVIN R G, HUFFMAN W P. Recent progress in aerodynamic design optimization[J]. International Journal for Numerical Methods in Fluids, 1999, 30(2):205-216.
[4]	周铸, 黄江涛, 高正红, 等.民用飞机气动外形数值优化设计面临的挑战与展望[J]. 航空学报, 2019, 40(1):522370. ZHOU Z, HUANG J T, GAO Z H, et al. Challenges and prospects of numerical optimization design for laorge civil aircraft aerodynamic shape[J]. Acta Aeronautica et Astronautica Sinica, 2019, 40(1):522370(in Chinese).
[5]	STEPHEN T, LEDOU X, WILLIAM W, et al. MDOPT-a multidisciplinary design optimization system using higher order analysis codes[C]//10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston:AIAA, 2004.
[6]	GRAY J, MOOREY K T, NAYLOR B A. OpenMDAO:An open source framework for multidisciplinary analysis and optimization[C]//Proceedings of 13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference. Reston, VA:AIAA, 2010.
[7]	JAMESON J, PIERCE N A, MARTINELLI L. Optimum aerodynamics design using the Navier-Stokes equations:AIAA-1997-0101[R]. Reston:AIAA, 1997.
[8]	NIELSEN E J, ANDERSON W K. Recent improvements in aerodynamic design optimization on unstructured meshes:AIAA-2001-0596[R]. Reston, VA:AIAA, 2001.
[9]	黄江涛, 周铸, 刘刚, 等.飞行器气动/结构多学科延迟耦合伴随系统数值研究[J]. 航空学报, 2018, 39(5):121731. HUANG J T, ZHOU Z, LIU G, et al. Numerical study of aero-structural multidisciplinary lagged coupled adjoint system for aircraft[J]. Acta Aeronautica et Astronautica Sinica, 2018, 39(5):121731(in Chinese).
[10]	COELLO C A, VAN VELDUIZEN D A, LAMONT G B. Evolutionary algorithms for solving multi-Objective problems[M]. New York:Kluwer Academic Publishers, 2002.
[11]	郑传宇, 黄江涛, 周铸, 等. 飞翼翼型高维多目标空间多学科综合优化设计[J]. 空气动力学学报, 2017, 35(4):587-597. ZHENG C Y, HUANG J T, ZHOU Z, et al. Multidisciplinary optimization design of high dimensional target space for flying wing airfoil[J]. Acta Aerodynamica Sinica, 2017, 35(4):587-597(in Chinese).
[12]	SOBIESZCZANSKI-SOBIESKI J. Sensitivity analysis and multidisciplinary optimization for aircraft design:Recent advance and results[J]. Journal of Aircraft, 1990, 27(12):993-1001.
[13]	PIEGL L, TILLER W. The NURBS book[M]. Berlin:Springer, 1997.
[14]	MKULFAN B. Recent extensions and applications of the "CST" universal parametric geometry representation method:AIAA-2007-7709[R]. Reston:AIAA, 2007.
[15]	SEDERBERG T W, PARRY S R. Freeform deforming of solid geometric models[J]. Computer Graphics, 1986, 22(4):151-160.
[16]	SAMAREH J A. Aerodynamic shape optimization based on free-form deformation:AIAA-2004-4630[R]. Reston:AIAA, 2004.
[17]	PANG Y F, ZHANG S J, SUN J F. An adaptive grid rebuilding method for multi-zone structured grid[C]//6th Asia Workshop on Computational Fluid Dynamics, 2006.
[18]	MCKAY M D, CONOVER W J, BECKMAN R J. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code[J]. Technometrics, 1979, 21(3):239-245.
[19]	方开泰, 马长兴. 正交与均匀试验设计[M]. 北京:科学出版社,1980. FANG K T, MA C X. Orthogonal and uniform experimental design[M]. Beijing:Science Press, 1980(in Chinese).
[20]	JEONG S, MURAYMA M. Efficient optimization design method using Kriging model[J]. Journal of Aircraft, 2005, 42(2):413-420.
[21]	肖涵山, 陈作斌, 刘刚, 等. 基于Euler方程的三维自适应笛卡尔网格应用研究[J]. 空气动力学学报, 2003, 21(2):202-210. XIAO H S, CHEN Z B, LIU G, et al. Applications of 3-D adaptive Cartesian grid algorithm based on the Euler equations[J]. Acta Aerodynamica Sinica, 2003, 21(2):202-210(in Chinese).
[22]	牟斌, 肖中云, 周铸, 等. 多重网格技术在复杂粘性流场计算中的应用及研究[J]. 空气动力学学报, 2006, 24(1):51-54. MOU B, XIAO Z Y, ZHOU Z, et al. Application and investigation of multi-block multi-grid method in complicated viscous flow fields calculation[J]. Acta Aerodynamica Sinica, 2006, 24(1):51-54(in Chinese).
[23]	黄江涛, 高正红, 余婧, 等. 大型民用飞机气动外形典型综合设计方法[J]. 航空学报, 2019, 40(2):522369. HUANG J T, GAO Z H, YU J, et al. A typical integrated design method design method for aerodynamics shape optimization of large civil aircraft[J]. Acta Aeronautica et Astronautica Sinica, 2019, 40(2):522369(in Chinese).
[24]	黄江涛, 周铸, 余婧, 等. 考虑飞行器动力系统进排气效应的设计参数灵敏度分析研究[J]. 推进技术, 2019, 40(2):250-258. HUANG J T, ZHOU Z, YU J, et al. Sensitivity analysis of design variables considering intake and exhaust effects[J]. Journal of Propulsion Technology, 2019,40(2):250-258(in Chinese).

Digital integrated platform for universal aircraft aerodynamic design optimization: DIPasda

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References 24

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	Chao LIANG, Li YANG, Chengsheng PAN, Yaowen QI. Multi-QoS constraints routing algorithm based on satellite network dynamic resource graph [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023, 44(1): 326422-326422.
[2]	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.
[3]	ZOU Ziyuan, CHEN Qifeng. Decision tree-based target assignment for confrontation of multiple space vehicles [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(S1): 726910-726910.
[4]	SUN Gang, PENG Shuang, CHEN Hao, WU Jiangjiang, LI Jun. Multi-objective optimization method oriented to integrated scenario of TT & C resources and data transmission resources [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(9): 326114-326114.
[5]	ZHENG Shuai, WANG Zihan, ZHAO Haoran, YANG Pengtao, HONG Jun. Layout optimization method of aircraft fuel gauging sensor based on differential evolution algorithm [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(8): 125809-125809.
[6]	JING Tao, TIAN Xitian. Multi-objective optimization method for aircraft tolerance allocation based on Monte Carlo-adaptive differential evolution algorithm [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(3): 425278-425278.
[7]	WANG Yiwen, LAN Xiayu, SHI Yayun, HUA Jun, BAI Junqiang, ZHOU Zhu. Gradient optimization design for laminar airfoil considering inspiration effect [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(11): 527323-527323.
[8]	LUO Qing, ZHANG Tao, SHAN Peng, ZHANG Wentao, LIU Zihao. Generating reconfiguration blueprints for IMA systems based on improved Q-learning [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(8): 525792-525792.
[9]	ZHANG Junfeng, YOU Lubao, YANG Chunwei, HU Rong. Arrival sequencing and scheduling based on multi-objective Imperialist competitive algorithm [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(6): 324439-324439.
[10]	SUN Gang, CHEN Hao, PENG Shuang, DU Chun, LI Jun. Multi-objective optimization algorithm for satellite range scheduling based on preference MOEA [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(4): 524475-524475.
[11]	ZUO Guang, AI Bangcheng. Aerodynamic design of advanced space transportation system: Review [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(2): 624077-624077.
[12]	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.
[13]	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.
[14]	LUO Jiaqi, YANG Jing. Aerodynamic design optimization of a single low-speed compressor stage by an adjoint method [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(5): 623368-623368.
[15]	LI Runze, ZHANG Yufei, CHEN Haixin. Strategies and methods for multi-objective aerodynamic optimization design for supercritical wings [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(5): 623409-623409.