Virtual, Digital and Hybrid Twins: A New Paradigm in Data-Based Engineering and Engineered Data

被引:169
作者
Chinesta, Francisco [1 ]
Cueto, Elias [2 ]
Abisset-Chavanne, Emmanuelle [3 ]
Duval, Jean Louis [4 ]
Khaldi, Fouad El [4 ]
机构
[1] ENSAM ParisTech, 151 Blvd Hop, F-75013 Paris, France
[2] Univ Zaragoza, Aragon Inst Engn Res, Maria de Luna S-N, Zaragoza 50018, Spain
[3] Ecole Cent Nantes, ESI Grp Chair, 1 Rue Noe, F-44300 Nantes, France
[4] ESI Grp, 3Bis Rue Saarinen, F-94528 Rungis, France
关键词
MATERIAL PARAMETER-IDENTIFICATION; MODEL ORDER REDUCTION; NONLINEAR DIMENSIONALITY REDUCTION; CONSISTENT CLUSTERING ANALYSIS; COMPUTATIONAL HOMOGENIZATION; WYPIWYG HYPERELASTICITY; VISCOPLASTIC MODELS; DATA ASSIMILATION; DECOMPOSITION; THERMODYNAMICS;
D O I
10.1007/s11831-018-9301-4
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Engineering is evolving in the same way than society is doing. Nowadays, data is acquiring a prominence never imagined. In the past, in the domain of materials, processes and structures, testing machines allowed extract data that served in turn to calibrate state-of-the-art models. Some calibration procedures were even integrated within these testing machines. Thus, once the model had been calibrated, computer simulation takes place. However, data can offer much more than a simple state-of-the-art model calibration, and not only from its simple statistical analysis, but from the modeling and simulation viewpoints. This gives rise to the the family of so-called twins: the virtual, the digital and the hybrid twins. Moreover, as discussed in the present paper, not only data serve to enrich physically-based models. These could allow us to perform a tremendous leap forward, by replacing big-data-based habits by the incipient smart-data paradigm.
引用
收藏
页码:105 / 134
页数:30
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