A review of flexible multibody dynamics for gradient-based design optimization

被引:25
|
作者
Gufler, Veit [1 ]
Wehrle, Erich [1 ]
Zwoelfer, Andreas [2 ]
机构
[1] Free Univ Bozen Bolzano, Fac Sci & Technol, Univ Pl,Piazza Univ 1, I-39100 Bozen Bolzano, South Tyrol, Italy
[2] Tech Univ Munich, Chair Appl Mech, Boltzmannstr 15, D-85748 Garching, Germany
关键词
Flexible multibody dynamics; Design optimization; Gradient-based optimization; Sensitivity analysis; EQUIVALENT STATIC LOADS; DIFFERENTIAL-ALGEBRAIC EQUATIONS; IMPROVED NUMERICAL DISSIPATION; SENSITIVITY-ANALYSIS; STRUCTURAL OPTIMIZATION; COORDINATE FORMULATION; TOPOLOGY OPTIMIZATION; FLOATING FRAME; SYSTEMS; DEFORMATION;
D O I
10.1007/s11044-021-09802-z
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
Design optimization of flexible multibody dynamics is critical to reducing weight and therefore increasing efficiency and lowering costs of mechanical systems. Simulation of flexible multibody systems, though, typically requires high computational effort which limits the usage of design optimization, especially when gradient-free methods are used and thousands of system evaluations are required. Efficient design optimization of flexible multibody dynamics is enabled by gradient-based optimization methods in concert with analytical sensitivity analysis. The present study summarizes different formulations of the equations of motion of flexible multibody dynamics. Design optimization techniques are introduced, and applications to flexible multibody dynamics are categorized. Efficient sensitivity analysis is the centerpiece of gradient-based design optimization, and sensitivity methods are introduced. The increased implementation effort of analytical sensitivity analysis is rewarded with high computational efficiency. An exemplary solution strategy for system and sensitivity evaluations is shown with the analytical direct differentiation method. Extensive literature sources are shown related to recent research activities.
引用
收藏
页码:379 / 409
页数:31
相关论文
共 50 条
  • [31] Gradient-Based Multiobjective Optimization with Uncertainties
    Peitz, Sebastian
    Dellnitz, Michael
    NEO 2016: RESULTS OF THE NUMERICAL AND EVOLUTIONARY OPTIMIZATION WORKSHOP NEO 2016 AND THE NEO CITIES 2016 WORKSHOP, 2018, 731 : 159 - 182
  • [32] Using blade element momentum methods with gradient-based design optimization
    Ning, Andrew
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2021, 64 (02) : 991 - 1014
  • [33] Rational catalyst design for CO oxidation: a gradient-based optimization strategy
    Wang, Ziyun
    Hu, P.
    CATALYSIS SCIENCE & TECHNOLOGY, 2021, 11 (07) : 2604 - 2615
  • [34] INVESTIGATION OF ANALYSIS AND GRADIENT-BASED DESIGN OPTIMIZATION USING NEURAL NETWORKS
    Fuchi, Kazuko W.
    Wolf, Eric M.
    Makhija, David S.
    Wukie, Nathan A.
    Schrock, Christopher R.
    Beran, Philip S.
    PROCEEDINGS OF THE ASME 2020 CONFERENCE ON SMART MATERIALS, ADAPTIVE STRUCTURES AND INTELLIGENT SYSTEMS (SMASIS2020), 2020,
  • [35] Cascaded Metasurface Design Using Electromagnetic Inversion With Gradient-Based Optimization
    Brown, Trevor
    Mojabi, Puyan
    IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, 2022, 70 (03) : 2033 - 2045
  • [36] General implementation of multilevel parallelization in a gradient-based design optimization algorithm
    Rajan, S. D.
    Belegundu, A. D.
    Damle, A. S.
    Lau, D.
    St Ville, J.
    AIAA JOURNAL, 2006, 44 (09) : 1993 - 2001
  • [37] Gradient-Based Design Optimization of a Switched Reluctance Motor for an HVAC Application
    Sayed, Ehab
    Bakr, Mohamed H.
    Bilgin, Berker
    Emadi, Ali
    2020 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE & EXPO (ITEC), 2020, : 1031 - 1037
  • [38] A gradient-based polynomial chaos approach for risk and reliability-based design optimization
    A. J. Torii
    R. H. Lopez
    L. F. F. Miguel
    Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2017, 39 : 2905 - 2915
  • [39] Reliability-Based Design Optimization of Uncertain Stochastic Systems: Gradient-Based Scheme
    Jensen, H. A.
    Kusanovic, D. S.
    Valdebenito, M. A.
    Schueller, G. I.
    JOURNAL OF ENGINEERING MECHANICS, 2012, 138 (01) : 60 - 70
  • [40] A gradient-based polynomial chaos approach for risk and reliability-based design optimization
    Torii, A. J.
    Lopez, R. H.
    Miguel, L. F. F.
    JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING, 2017, 39 (07) : 2905 - 2915