Damage tolerance reliability analysis combining Kriging regression and support vector machine classification

被引:13
作者
Chocat, Rudy [1 ,2 ,4 ]
Beaucaire, Paul [2 ]
Debeugny, Lclc [1 ]
Lefebvre, Jean-Pierre [2 ]
Sainvitu, Caroline [3 ]
Breitkopf, Piotr [4 ]
Wyart, Eric [3 ]
机构
[1] ArianeGrp, F-27204 Foret De Vernon, Vernon, France
[2] Cenaero France, 462 Rue Benjamin Delessert, F-77554 Moissy Cramayel, France
[3] Cenaero, Rue Freres Wright 29, B-6041 Charleroi, Belgium
[4] Univ Technol Compiegne, Lab Roberval, UTC CNRS FRE2012, F-60203 Compiegne, France
关键词
Damage tolerance; Fracture mechanics; Reliability; Kriging; Support vector machine; Subset simulation; SMALL FAILURE PROBABILITIES; RESPONSE-SURFACE; DESIGN; OPTIMIZATION; PROPAGATION; FATIGUE;
D O I
10.1016/j.engfracmech.2019.106514
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
Damage tolerance analysis associates a Fracture Mechanical model with the Failure Assessment Diagram to define the state of a space engine component. The reliability analysis treats the variability of numerical models assessing the probability of failure within Linear Elastic Fracture Mechanics (LEFM) hypotheses. However, these models, while providing quantitative information in the safe domain, give only qualitative information for failed components. This work proposes an original methodology to combine Kriging regression and the Support Vector Machine classification along with transition criteria between both approaches. To accurately describe the limit state, we define a specific enrichment strategy. The efficiency of the proposed methodology is illustrated on reference test cases.
引用
收藏
页数:13
相关论文
共 42 条
  • [31] ASSESSMENT OF THE INTEGRITY OF STRUCTURES CONTAINING DEFECTS
    MILNE, I
    AINSWORTH, RA
    DOWLING, AR
    STEWART, AT
    [J]. INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING, 1988, 32 (1-4) : 3 - 104
  • [32] NASGRO, 2014, FRACT MECH FAT CRACK
  • [33] An efficient reliability method combining adaptive Support Vector Machine and Monte Carlo Simulation
    Pan, Qiujing
    Dias, Daniel
    [J]. STRUCTURAL SAFETY, 2017, 67 : 85 - 95
  • [34] Platt JC, 2000, ADV NEUR IN, P61
  • [35] Comparison of pure and "Latinized" centroidal Voronoi tessellation against various other statistical sampling methods
    Romero, Vicente J.
    Burkardt, John V.
    Gunzburger, Max D.
    Peterson, Janet S.
    [J]. RELIABILITY ENGINEERING & SYSTEM SAFETY, 2006, 91 (10-11) : 1266 - 1280
  • [36] Uncertainty quantification and model validation of fatigue crack growth prediction
    Sankararaman, Shankar
    Ling, You
    Mahadevan, Sankaran
    [J]. ENGINEERING FRACTURE MECHANICS, 2011, 78 (07) : 1487 - 1504
  • [37] Adaptive virtual support vector machine for reliability analysis of high-dimensional problems
    Song, Hyeongjin
    Choi, K. K.
    Lee, Ikjin
    Zhao, Liang
    Lamb, David
    [J]. STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2013, 47 (04) : 479 - 491
  • [38] A hybrid algorithm for reliability analysis combining Kriging and subset simulation importance sampling
    Tong, Cao
    Sun, Zhili
    Zhao, Qianli
    Wang, Qibin
    Wang, Shuang
    [J]. JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2015, 29 (08) : 3183 - 3193
  • [39] STATISTICAL NATURE OF FATIGUE CRACK-PROPAGATION
    VIRKLER, DA
    HILLBERRY, BM
    GOEL, PK
    [J]. JOURNAL OF ENGINEERING MATERIALS AND TECHNOLOGY-TRANSACTIONS OF THE ASME, 1979, 101 (02): : 148 - 153
  • [40] Substructuring FE-XFE approaches applied to three-dimensional crack propagation
    Wyart, E.
    Duflot, M.
    Coulon, D.
    Martiny, P.
    Pardoen, T.
    Remacle, J. -F.
    Lani, F.
    [J]. JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2008, 215 (02) : 626 - 638