基于离散伴随的层流翼优化设计方法

doi:10.7527/S1000-6893.2021.26132

流体力学与飞行力学

本期目录 | 过刊浏览 | 高级检索

前一篇 | 后一篇

基于离散伴随的层流翼优化设计方法

杨体浩¹, 王一雯², 王雨桐⁴, 史亚云³, 周铸⁴

1. 西北工业大学航空学院, 西安 710072;
2. 西北工业大学无人系统技术研究院, 西安 710072;
3. 西安交通大学航天学院, 西安 710049;
4. 中国空气动力研究与发展中心, 绵阳 621000

收稿日期:2021-07-20 修回日期:2021-09-22 发布日期:2022-01-26
通讯作者: 史亚云,E-mail:yayunshi@xjtu.edu.cn E-mail:yayunshi@xjtu.edu.cn
基金资助:
国家自然科学基金（11902320，12002284）

Discrete adjoint-based optimization approach for laminar flow wings

YANG Tihao¹, WANG Yiwen², WANG Yutong⁴, SHI Yayun³, ZHOU Zhu⁴

1. School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China;
2. Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China;
3. School of Aerospace, Xi'an Jiaotong University, Xi'an 710049, China;
4. China Aerodynamics Research and Development Center, Mianyang 621000, China

Received:2021-07-20 Revised:2021-09-22 Published:2022-01-26
Supported by:
National Natural Science Foundation of China (11902320, 12002284)

摘要/Abstract

摘要： 层流技术是未来发展绿色航空的核心技术，可处理大规模设计变量的高效、鲁棒的优化设计方法是推动层流技术工程应用转化的关键环节之一。基于高可信度RANS求解器，结合准三维层流边界层方程、Drela-Giles和C1准则，建立了可同时捕捉Tollmien-Schlichting （TS）和Crossflow （CF）不稳定性的转捩预测方法，与典型风洞和飞行试验对比，验证了该方法的可靠性。通过严格物面插值、获得准确的间歇因子函数以剔除气动力计算引入的数值噪声，精确推导了考虑转捩的耦合伴随方程，并结合无矩阵存储技术、链式求导法则、反向混合自动微分及Coupled Krylov （CK）算法发展了耦合伴随方程高效求解方法，最终建立了基于离散伴随的层流翼梯度优化设计方法。针对典型客机翼身组合体构型的气动优化显著推迟了转捩，获得了10.48%的减阻收益。优化结果表明，建立的层流翼梯度优化方法能够有效处理多种转捩机制并存的复杂三维层流翼优化问题。

关键词: 离散伴随, 层流转捩, 减阻, 梯度优化, 流向转捩, 横流转捩

Abstract: Laminar flow is one of the key technologies in the future development of green aviation, while an efficient and reliable design optimization approach for problems with a large number of design variables is the key to promoting the industrial application of the laminar flow technique. Based on the high-fidelity RANS solver, and combined with the quasi-three-dimensional laminar boundary layer equation, Drela-Giles and C1 criteria, a transition prediction method, which can simultaneously capture Tollmien-Schlichting (TS) and Crossflow (CF) instabilities, is established. Comparison of the simulation results with typical wind tunnel and flight tests shows the reliability of the simulation approach. An accurate intermittency function is obtained by strictly interpolating the surface values to eliminate the numerical noise for the aerodynamic forces simulation. The coupled adjoint equation considering transition is derived accurately, and solved efficiently by combining the matrix-free technique, the chain rule, the hybrid reverse automatic differentiation, and the Coupled Krylov (CK) algorithm. Finally, the discrete adjoint-based laminar flow wings optimization method is built. The optimization of a wing-body configuration with typical characteristics of regional airliners demonstrates that the transition is effectively delayed, with 10.48% of the total drag reduced. The optimization results reveal that the gradient-based laminar flow wings optimization framework can deal with complex three-dimensional laminar flow wings optimization problems with multiple transition mechanisms.

Key words: discrete adjoint, laminar-turbulent transition, drag reduction, gradient-based optimization, streamwise transition, crossflow transition

中图分类号:

V221.3

杨体浩, 王一雯, 王雨桐, 史亚云, 周铸. 基于离散伴随的层流翼优化设计方法[J]. 航空学报, 2022, 43(12): 126132.

YANG Tihao, WANG Yiwen, WANG Yutong, SHI Yayun, ZHOU Zhu. Discrete adjoint-based optimization approach for laminar flow wings[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(12): 126132.

参考文献

[1] ARNAL D, ARCHAMBAUD J P. Laminar-turbulent transition control:NLF, LFC, HLFC[C]//Advances in Laminar-Turbulent Transition Modeling, 2008.
[2] DE'POMPEIS R, CINQUETTI P, MARTINI P I S. Development and certification flight test on the piaggio P.180 avanti aircraft:A general overview:SAE Technical Paper 911003[R]. Warrendale:SAE International,1991.
[3] FUJINO M, YOSHIZAKI Y, KAWAMURA Y. Natural-laminar-flow airfoil development for a lightweight business jet[J]. Journal of Aircraft, 2003, 40(4):609-615.
[4] CROUCH J. Modeling transition physics for laminar flow control[C]//38th Fluid Dynamics Conference and Exhibit. Reston:AIAA, 2008.
[5] EPPINK J L. The effect of forward-facing steps on stationary crossflow instability growth and breakfown[C]//AIAA Aerospace Sciences Meeting, 2018.
[6] ARNAL D, CASALIS G. Laminar-turbulent transition prediction in three-dimensional flows[J]. Progress in Aerospace Sciences, 2000, 36(2):173-191.
[7] KRUMBEIN A, KRIMMELBEIN N, SCHRAUF G. Automatic transition prediction in hybrid flow solver, part 1:Methodology and sensitivities[J]. Journal of Aircraft, 2009, 46(4):1176-1190.
[8] KRUMBEIN A, KRIMMELBEIN N, SCHRAUF G. Automatic transition prediction in hybrid flow solver, part 2:Practical application[J]. Journal of Aircraft, 2009, 46(4):1191-1199.
[9] LIAO W, MALIK M R, LEE-RAUSCH E M, et al. Boundary-layer stability analysis of the mean flows obtained using unstructured grids[J]. Journal of Aircraft, 2015, 52(1):49-63.
[10] SHI Y, GROSS R, MADER C A, et al. Transition prediction based on linear stability theory with the RANS solver for three-dimensional configurations[C]//Proceedings of the AIAA Aerospace Sciences Meeting, AIAA SciTech Forum, 2018.
[11] ARNAL D. Transition prediction in transonic flow[M]//Symposium transsonicum III. Berlin:Springer Berlin Heidelberg, 1989:253-262.
[12] PERRAUD J, ARNAL D, CASALIS G, et al. Automatic transition predictions using simplified methods[J]. AIAA Journal, 2009, 47(11):2676-2684.
[13] YANG T H, ZHONG H, CHEN Y F, et al. Transition prediction and sensitivity analysis for a natural laminar flow wing glove flight experiment[J]. Chinese Journal of Aeronautics, 2021, 34(8):34-47.
[14] 杨体浩, 白俊强, 史亚云, 等. 考虑吸气分布影响的HLFC机翼优化设计[J]. 航空学报, 2017, 38(12):121158. YANG T H, BAI J Q, SHI Y Y, et al. Optimization design for HLFC wings considering influence of suction distribution[J]. Acta Aeronautica et Astronautica Sinica, 2017, 38(12):121158(in Chinese).
[15] 史亚云, 郭斌, 刘倩, 等. 基于能量观点的混合层流优化设计[J]. 北京航空航天大学学报, 2019, 45(6):1162-1174. SHI Y Y, GUO B, LIU Q, et al. Hybrid laminar flow optimization design from energy view[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(6):1162-1174(in Chinese).
[16] HAN Z H, CHEN J, ZHANG K S, et al. Aerodynamic shape optimization of natural-laminar-flow wing using surrogate-based approach[J]. AIAA Journal, 2018, 56(7):2579-2593.
[17] KENWAY G K W, MADER C A, HE P, et al. Effective adjoint approaches for computational fluid dynamics[J]. Progress in Aerospace Sciences, 2019, 110:100542.
[18] JAMESON A. Aerodynamic design via control theory[J]. Journal of Scientific Computing, 1988, 3(3):233-260.
[19] BREZILLON J, DWIGHT R P. Applications of a discrete viscous adjoint method for aerodynamic shape optimisation of 3D configurations[J]. CEAS Aeronautical Journal, 2012, 3(1):25-34.
[20] ALBRING T, SAGEBAUM M, GAUGER N R. New results in numerical and experimental fluid mechanics X[C]//19th STAB/DGLR Symposium Munich. Cham:Springer International Publishing, 2014.
[21] HE P, MADER C A, MARTINS J R R A, et al. An aerodynamic design optimization framework using a discrete adjoint approach with OpenFOAM[J]. Computers & Fluids, 2018, 168:285-303.
[22] 陈颂, 白俊强, 史亚云, 等. 民用客机机翼/机身/平尾构型气动外形优化设计[J]. 航空学报, 2015, 36(10):3195-3207. CHEN S, BAI J Q, SHI Y Y, et al. Aerodynamic shape optimization design of civil jet wing-body-tail configuration[J]. Acta Aeronautica et Astronautica Sinica, 2015, 36(10):3195-3207(in Chinese).
[23] 白俊强, 雷锐午, 杨体浩, 等. 基于伴随理论的大型客机气动优化设计研究进展[J]. 航空学报, 2019, 40(1):522642. BAI J Q, LEI R W, YANG T H, et al. Progress of adjoint-based aerodynamic optimization design for large civil aircraft[J]. Acta Aeronautica et Astronautica Sinica, 2019, 40(1):522642(in Chinese).
[24] 黄江涛, 张绎典, 高正红, 等. 基于流场/声爆耦合伴随方程的超声速公务机声爆优化[J]. 航空学报, 2019, 40(5):122505. HUANG J T, ZHANG Y D, GAO Z H, et al. Sonic boom optimization of supersonic jet based on flow/sonic boom coupled adjoint equations[J]. Acta Aeronautica et Astronautica Sinica, 2019, 40(5):122505(in Chinese).
[25] ZHANG P F, LU J, WANG Z D, et al. Adjoint-based optimization method with linearized SST turbulence model and a frozen gamma-theta transition model approach for turbomachinery design[C]//Proceedings of ASME Turbo Expo 2015:Turbine Technical Conference and Exposition, 2015.
[26] KHAYATZADEH P, NADARAJAH S. Aerodynamic shape optimization of natural laminar flow (NLF) airfoils[C]//50th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition. Reston:AIAA, 2012.
[27] HALILA G L, MARTINS J R, FIDKOWSKI K J. Adjoint-based aerodynamic shape optimization including transition to turbulence effects[J]. Aerospace Science and Technology, 2020, 107:106243.
[28] LANGTRY R B, MENTER F R. Correlation-based transition modeling for unstructured parallelized computational fluid dynamics codes[J]. AIAA Journal, 2009, 47(12):2894-2906.
[29] LEE J D, JAMESON A. Natural-laminar-flow airfoil and wing design by adjoint method and automatic transition prediction[C]//47th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, 2009.
[30] RASHAD R, ZINGG D W. Aerodynamic shape optimization for natural laminar flow using a discrete-adjoint approach[J]. AIAA Journal, 2016, 54(11):3321-3337.
[31] SHI Y, MADER C A, HE S, et al. Natural laminar flow airfoil optimization design using a discrete adjoint approach[J]. AIAA Journal, 2020, 58(11):4702-4722.
[32] SHI Y, MADER C A, HE S, et al. Natural laminar flow wing optimization using a discrete adjoint approach[J]. Structural and Multidisciplinary Optimization, 2021, 64(5):1-22.
[33] GLEYZES C, COUSTEIX J, BONNET J L. A calculation method of leading-edge separation bubbles[M]//Numerical and physical aspects of aerodynamic flows II. Berlin:Springer, 1984:173-192.
[34] SPALART P, ALLMARAS S. A one-equation turbulence model for aerodynamic flows[C]//30th Aerospace Sciences Meeting and Exhibit. Reston:AIAA, 1992.
[35] SHI Y Y, YANG T H, BAI J Q, et al. Research of transition criterion for semi-empirical prediction method at specified transonic regime[J]. Aerospace Science and Technology, 2019, 88:95-109.
[36] 杨体浩, 白俊强, 王丹, 等. 考虑发动机干扰的尾吊布局后体气动优化设计[J]. 航空学报, 2014, 35(7):1836-1844. YANG T H, BAI J Q, WANG D, et al. Aerodynamic optimization design for after-body of tail-mounted engine layout considering interference of engines[J]. Acta Aeronautica et Astronautica Sinica, 2014, 35(7):1836-1844(in Chinese).
[37] MACK L M. Special course on stability and transition of laminar flow:AGARD-709[R]. Pairs:AGARD, 1984.

E-mail：hkxb@buaa.edu.cn

关于我们

期刊社服务

专业学科

封面文章

友情链接

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

基于离散伴随的层流翼优化设计方法

Discrete adjoint-based optimization approach for laminar flow wings

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	王雪鹤, 柴春硕, 邢世龙, 樊枫, 黄水林. 共轴高速直升机反流区翼型设计及减阻机理[J]. 航空学报, 2024, 45(9): 529960-529960.
[2]	李广佳, 王红波, 张凯, 仪志胜. 临近空间太阳能无人机增升减阻技术综述[J]. 航空学报, 2024, 45(5): 529644-529644.
[3]	赵轲, 邓俊, 黄江涛, 陈树生, 高正红. 飞翼布局高低速一体化气动优化设计[J]. 航空学报, 2024, 45(15): 129367-129367.
[4]	张定华, 何智伟, 张学宝, 罗明. 叶片多尺度表面对压气机气动性能影响及其高性能制造研究进展[J]. 航空学报, 2024, 45(13): 629642-629642.
[5]	韦鼎元, 章思龙, 韦健飞, 左婧滢, 李欣, 鲍文. 高马赫数燃烧室离散孔燃料膜热防护和减阻特性[J]. 航空学报, 2024, 45(11): 529075-529075.
[6]	曾繁宇, 邱云龙, 曹占伟, 张伦, 陈伟芳. 超声速湍流边界层阵列式微吹气流动控制与减阻特性[J]. 航空学报, 2023, 44(S2): 729396-729396.
[7]	高世琦, 丁博, 解旭祯, 李铮, 陈林, 钱首元, 焦子涵, 白光辉. 等离子体激励在高速流动中的减阻机制[J]. 航空学报, 2023, 44(S2): 729373-729373.
[8]	陈艺夫, 马宇航, 蓝庆生, 孙卫平, 史亚云, 杨体浩, 白俊强. 基于多项式混沌法的翼型不确定性分析及梯度优化设计[J]. 航空学报, 2023, 44(8): 127446-127446.
[9]	曹文博, 刘溢浪, 张伟伟. 基于降阶模型和梯度优化的流场加速收敛方法[J]. 航空学报, 2023, 44(6): 127090-127090.
[10]	刘超宇, 屈峰, 孙迪, 刘传振, 钱战森, 白俊强. 基于离散伴随的高超声速密切锥乘波体气动优化设计[J]. 航空学报, 2023, 44(4): 126664-126664.
[11]	韩荣, 刘伟, 杨小亮. 高超声速飞行器自适应减阻盘动态减阻机理[J]. 航空学报, 2023, 44(4): 126633-126633.
[12]	曾品棚, 陈树生, 李金平, 贾苜梁, 高正红. 减阻杆与环形喷流组合构型钝头降热数值模拟[J]. 航空学报, 2023, 44(22): 128407-128407.
[13]	樊宇翔, 赵瑞, 左政玄, 杨光, 李宇. 气体引射效应对壁面热流和摩擦阻力的影响[J]. 航空学报, 2023, 44(21): 528587-528587.
[14]	丁玉临, 韩忠华, 乔建领, 聂晗, 宋文萍, 宋笔锋. 超声速民机总体气动布局设计关键技术研究进展[J]. 航空学报, 2023, 44(2): 626310-626310.
[15]	王晓峰, 屈峰, 付俊杰, 王泽宇, 刘超宇, 白俊强. 基于离散伴随的高超内转式进气道气动优化设计[J]. 航空学报, 2023, 44(19): 128352-128352.