A partitioned scheme for adjoint shape sensitivity analysis of fluid-structure interactions involving non-matching meshes

被引:0
作者
Najian Asl, Reza [1 ]
Antonau, Ihar [1 ]
Ghantasala, Aditya [1 ]
Dettmer, Wulf G. [2 ]
Wuechner, Roland [1 ]
Bletzinger, Kai-Uwe [1 ]
机构
[1] Tech Univ Munich, Lehrstuhl Stat, Arcisstr 21, D-80333 Munich, Germany
[2] Swansea Univ, Coll Engn, Zienkiewicz Ctr Computat Engn, Swansea, W Glam, Wales
关键词
Adjoint shape sensitivity analysis; fluid-structure interaction; partitioned coupling; black-box adjoint solvers; non-matching meshes; STATE AEROELASTIC ANALYSIS; DESIGN OPTIMIZATION; AERODYNAMIC DESIGN; FORMULATION; ALGORITHMS; CONSISTENT; FRAMEWORK; SOLVER;
D O I
10.1080/10556788.2020.1806275
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
This work presents a partitioned solution procedure to compute shape gradients in fluid-structure interaction (FSI) using black-box adjoint solvers. Special attention is paid to project the gradients onto the undeformed configuration due to the mixed Lagrangian-Eulerian formulation of large-deformation FSI in this work. The adjoint FSI problem is partitioned as an assembly of well-known adjoint fluid and structural problems. The sub-adjoint problems are coupled with each other by augmenting the target functions with auxiliary functions, independent of the concrete choice of the underlying adjoint formulations. The auxiliary functions are linear force-based or displacement-based functionals which are readily available in well-established single-disciplinary adjoint solvers. Adjoint structural displacements, adjoint fluid displacements, and domain-based adjoint sensitivities of the fluid are the coupling fields to be exchanged between the adjoint solvers. A reduced formulation is also derived for the case of boundary-based adjoint shape sensitivity analysis for fluids. Numerical studies show that the complete formulation computes accurate shape gradients whereas inaccuracies appear in the reduced gradients. Mapping techniques including nearest element interpolation and the mortar method are studied in computational adjoint FSI. It is numerically shown that the mortar method does not introduce spurious oscillations in primal and sensitivity fields along non-matching interfaces.
引用
收藏
页码:546 / 576
页数:31
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  • [41] Goal-oriented error estimation for fluid-structure interaction problems
    Richter, Th
    [J]. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2012, 223 : 28 - 42
  • [42] Coupled adjoint-based sensitivities in large-displacement fluid-structure interaction using algorithmic differentiation
    Sanchez, R.
    Albring, T.
    Palacios, R.
    Gauger, N. R.
    Economon, T. D.
    Alonso, J. J.
    [J]. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, 2018, 113 (07) : 1081 - 1107
  • [43] Interface Jacobian-based Co-Simulation
    Sicklinger, S.
    Belsky, V.
    Engelmann, B.
    Elmqvist, H.
    Olsson, H.
    Wuechner, R.
    Bletzinger, K. -U.
    [J]. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, 2014, 98 (06) : 418 - 444
  • [44] Singhammer K.F., 2019, THESIS
  • [45] Stavropoulou E., 2015, THESIS
  • [46] SU2, 2018, STANFORD U UNSTRUCTU
  • [47] INCOMPRESSIBLE-FLOW COMPUTATIONS WITH STABILIZED BILINEAR AND LINEAR EQUAL-ORDER-INTERPOLATION VELOCITY-PRESSURE ELEMENTS
    TEZDUYAR, TE
    MITTAL, S
    RAY, SE
    SHIH, R
    [J]. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 1992, 95 (02) : 221 - 242
  • [48] Assessment and improvement of mapping algorithms for non-matching meshes and geometries in computational FSI
    Wang, Tianyang
    Wuechner, Roland
    Sicklinger, Stefan
    Bletzinger, Kai-Uwe
    [J]. COMPUTATIONAL MECHANICS, 2016, 57 (05) : 793 - 816
  • [49] Efficient Monolithic Solution Algorithm for High-Fidelity Aerostructural Analysis and Optimization
    Zhang, Zimi J.
    Zingg, David W.
    [J]. AIAA JOURNAL, 2018, 56 (03) : 1251 - 1265
  • [50] High-fidelity aerostructural optimization with integrated geometry parameterization and mesh movement
    Zhang, Zimi J.
    Khosravi, Shahriar
    Zingg, David W.
    [J]. STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2017, 55 (04) : 1217 - 1235