Aerodynamic Shape Optimization Using Geometry Surrogates and Adjoint Method

被引:13
|
作者
Bobrowski, Kamil [1 ]
Ferrer, Esteban [1 ]
Valero, Eusebio [1 ]
Barnewitz, Holger [2 ]
机构
[1] Tech Univ Madrid, Dept Appl Math, ETSIAE UPM, Sch Aeronaut, Madrid 28040, Spain
[2] Airbus Operat GmbH, Flight Phys Dept, D-28199 Bremen, Germany
关键词
DESIGN; INTERPOLATION; FLOWS;
D O I
10.2514/1.J055766
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Nowadays, classical configurations of civil transportation airplanes are well optimized, with further improvements expected to be of the order of a single drag count. To achieve it, the entire airplane has to be taken into account during the aerodynamic shape optimization, which requires handling complex geometries with computer-aided-design software. So far, the integration of this software and aerodynamic shape optimization has been difficult, due to the framework complexity and problematic gradient evaluation. In this paper, the authors propose to substitute the computer-aided-design engine with a surrogate model of the surface deformation. The resulting framework does not require calls to the computer-aided-design software during the optimization. In addition, the surrogate model has been analytically differentiated and coupled with a mesh-adjoint method based on the radial-basis-functions to enable an efficient gradient-based optimization. The methodology is validated using two cases: a three-dimensional wing geometry in inviscid, transonic-flow conditions and a three-dimensional wing-body-tail configuration in a turbulent and transonic regime.
引用
收藏
页码:3304 / 3317
页数:14
相关论文
共 50 条
  • [21] AERODYNAMIC SHAPE DESIGN OPTIMIZATION FOR TURBOMACHINERY CASCADE BASED ON DISCRETE ADJOINT METHOD
    Zhang, Chaolei
    Peng, Zhenping
    PROCEEDINGS OF THE ASME TURBO EXPO 2011, VOL 7, PTS A-C, 2012, : 1219 - 1228
  • [22] ADJOINT-RESPONSE SURFACE METHOD IN AERODYNAMIC SHAPE OPTIMIZATION OF TURBOMACHINERY BLADES
    Tang, Xiao
    Luo, Jiaqi
    Liu, Feng
    PROCEEDINGS OF THE ASME TURBO EXPO: TURBINE TECHNICAL CONFERENCE AND EXPOSITION, 2016, VOL 2C, 2016,
  • [23] Adjoint Based Aerodynamic Shape Optimisation Using Kinetic Meshfree Method
    Malagi, Keshav S.
    Mamidi, Nischay R.
    Anil, Nemili
    Ramesh, Vasudev
    Deshpande, Suresh M.
    INTERNATIONAL JOURNAL OF COMPUTATIONAL FLUID DYNAMICS, 2023, 37 (03) : 234 - 249
  • [24] Machine learning for adjoint vector in aerodynamic shape optimization
    Mengfei Xu
    Shufang Song
    Xuxiang Sun
    Wengang Chen
    Weiwei Zhang
    Acta Mechanica Sinica, 2021, 37 : 1416 - 1432
  • [25] Aerodynamic shape optimization based on discrete adjoint and RBF
    Abergo, Luca
    Morelli, Myles
    Guardone, Alberto
    JOURNAL OF COMPUTATIONAL PHYSICS, 2023, 477
  • [26] Machine learning for adjoint vector in aerodynamic shape optimization
    Xu, Mengfei
    Song, Shufang
    Sun, Xuxiang
    Chen, Wengang
    Zhang, Weiwei
    ACTA MECHANICA SINICA, 2021, 37 (09) : 1416 - 1432
  • [27] Aerodynamic Shape Optimization continuous or discrete adjoint formulation
    Hiernaux, S
    Essers, JA
    COMPUTATIONAL FLUID DYNAMICS '98, VOL 1, PARTS 1 AND 2, 1998, : 598 - 603
  • [28] Aerodynamic Shape Optimization Using First and Second Order Adjoint and Direct Approaches
    Dimitrios I. Papadimitriou
    Kyriakos C. Giannakoglou
    Archives of Computational Methods in Engineering, 2008, 15 : 447 - 488
  • [29] Shape Optimization of Nanophotonic Devices Using the Adjoint Method
    Keraly, Christopher Lalau
    Bhargava, Samarth
    Ganapati, Vidya
    Scranton, Gregg
    Yablonovitch, Eli
    2014 CONFERENCE ON LASERS AND ELECTRO-OPTICS (CLEO), 2014,
  • [30] Aerodynamic Shape Optimization Using First and Second Order Adjoint and Direct Approaches
    Papadimitriou, Dimitrios I.
    Giannakoglou, Kyriakos C.
    ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2008, 15 (04) : 447 - 488