A time-space Kriging-based sequential metamodeling approach for multi-objective crashworthiness optimization

被引:20
|
作者
Gao, F. L. [1 ,2 ]
Bai, Y. C. [1 ]
Lin, C. [1 ]
Kim, I. Y. [3 ]
机构
[1] Beijing Inst Technol, Sch Mech Engn, Natl Engn Lab Elect Vehicles, Beijing 100081, Peoples R China
[2] CATARC Automot Test Ctr Tianjin Co Ltd, Tianjin 300300, Peoples R China
[3] Queens Univ, Dept Mech & Mat Engn, Kingston, ON K7L 3N6, Canada
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Multi-objective crashworthiness optimization; Time-space metamodeling; Kriging model; Intelligent sampling approach; Adaptive weighted sum method; MULTICELL TUBES; ELLIPSE TUBES; DESIGN;
D O I
10.1016/j.apm.2018.12.011
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A time-space Kriging-based sequential metamodeling approach is proposed for multi objective crashworthiness optimization (MOCO) in this paper. By defining the novel time space design criteria, the constructed metamodels for the optimization objectives include the characteristic mechanical responses with respect to both the structural space domain and crash time domain, compared to standard metrics with the extremum of the time history of the entire structure. The adaptive addition of new samples is performed to gradually improve the approximation accuracy during the optimization with the guidance of an adaptive weighted sum method. The effectiveness of the proposed method is demonstrated by investigating a multi-cell thin-walled crashworthiness design problem. Finally, its effectiveness in practical engineering is validated by the crashworthiness design for a vehicle under full-overlap frontal crash loadcase. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:378 / 404
页数:27
相关论文
共 50 条
  • [1] Robust optimization: A kriging-based multi-objective optimization approach
    Ribaud, Melina
    Blanchet-Scalliet, Christophette
    Helbert, Celine
    Gillot, Frederic
    [J]. RELIABILITY ENGINEERING & SYSTEM SAFETY, 2020, 200
  • [2] KRIGING METAMODELING IN MULTI-OBJECTIVE SIMULATION OPTIMIZATION
    Zakerifar, Mehdi
    Biles, William E.
    Evans, Gerald W.
    [J]. PROCEEDINGS OF THE 2009 WINTER SIMULATION CONFERENCE (WSC 2009 ), VOL 1-4, 2009, : 2066 - 2073
  • [3] Exploiting Gradient for Kriging-based Multi-Objective Aerodynamic Optimization
    Palar, Pramudita Satria
    Shimoyama, Koji
    [J]. 2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2017, : 501 - 508
  • [4] Analysis of multi-objective Kriging-based methods for constrained global optimization
    Cédric Durantin
    Julien Marzat
    Mathieu Balesdent
    [J]. Computational Optimization and Applications, 2016, 63 : 903 - 926
  • [5] Analysis of multi-objective Kriging-based methods for constrained global optimization
    Durantin, Cedric
    Marzat, Julien
    Balesdent, Mathieu
    [J]. COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 2016, 63 (03) : 903 - 926
  • [6] Kriging-based infill sampling criterion for constraint handling in multi-objective optimization
    Jesús Martínez-Frutos
    David Herrero-Pérez
    [J]. Journal of Global Optimization, 2016, 64 : 97 - 115
  • [7] Kriging-based infill sampling criterion for constraint handling in multi-objective optimization
    Martinez-Frutos, Jesus
    Herrero-Perez, David
    [J]. JOURNAL OF GLOBAL OPTIMIZATION, 2016, 64 (01) : 97 - 115
  • [8] Kriging Metamodeling-Assisted Multi-Objective Optimization of CMOS Current Conveyors
    Kotti, Mouna
    Fakhfakh, Mourad
    Tlelo-Cuautle, Esteban
    [J]. 15TH INTERNATIONAL CONFERENCE ON SYNTHESIS, MODELING, ANALYSIS AND SIMULATION METHODS AND APPLICATIONS TO CIRCUIT DESIGN (SMACD 2018), 2018, : 293 - 296
  • [9] Multi-objective sensor placement optimization in SHM systems with Kriging-based mode shape interpolation
    de Souza Mello, Felipe Martarella
    Pereira, Joao Luiz Junho
    Gomes, Guilherme Ferreira
    [J]. JOURNAL OF SOUND AND VIBRATION, 2024, 568
  • [10] Kriging-based multi-objective optimization on high-speed train aerodynamics using sequential infill criterion with gradient information
    Dai, Zhiyuan
    Li, Tian
    Krajnovic, Sinisa
    Zhang, Weihua
    [J]. PHYSICS OF FLUIDS, 2024, 36 (03)