Coupling multi-fidelity kriging and model-order reduction for the construction of virtual charts

被引：5

作者：

Nachar, Stephane ^{[1
]}

Boucard, Pierre-Alain ^{[1
]}

Neron, David ^{[1
]}

Bordeu, Felipe ^{[2
]}

机构：

[1] Univ Paris Saclay, LMT, ENS Paris Saclay, CNRS, 61 Ave President Wilson, F-94235 Cachan, France

[2] SAFRAN Tech, CS 80112, F-78772 Magny Les Hameaux, France

来源：

COMPUTATIONAL MECHANICS | 2019年 / 64卷 / 06期

关键词：

Metamodels; Reduced-order models; Viscoplasticity; Data fusion; PARAMETRIZED PROBLEMS; GLOBAL OPTIMIZATION; PGD; STRATEGY; DESIGN; OUTPUT;

D O I：

10.1007/s00466-019-01745-9

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

This article presents the coupling between multi-fidelity kriging and a database generated on-the-fly by model reduction to accelerate the generation of a surrogate model. The two-level multi-fidelity kriging method Evofusion is used for data fusion. The remarkable point is the generation of low-fidelity and high-fidelity observations from the same solver using the Proper Generalized Decomposition, a model-order reduction method. A 17x speedup is obtained here on an elasto-viscoplastic test case.

引用

页码：1685 / 1697

页数：13

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