Data-driven non-linear elasticity: constitutive manifold construction and problem discretization

被引:116
作者
Ibanez, Ruben [1 ,2 ]
Borzacchiello, Domenico [2 ]
Aguado, Jose Vicente [1 ,2 ]
Abisset-Chavanne, Emmanuelle [1 ,2 ]
Cueto, Elias [3 ]
Ladeveze, Pierre [4 ]
Chinesta, Francisco [1 ,2 ]
机构
[1] Ecole Cent Nantes, ESI Grp Chair, 1 Rue Noe,BP 92101, F-44321 Nantes 3, France
[2] Ecole Cent Nantes, High Performance Comp Inst, 1 Rue Noe,BP 92101, F-44321 Nantes 3, France
[3] Univ Zaragoza, Aragon Inst Engn Res, Maria de Luna S-N, Zaragoza 50018, Spain
[4] ENS Paris Saclay, LMT, 61 Ave President Wilson, F-94230 Cachan, France
关键词
Data-driven computational mechanics; Data-intensive simulation; Inverse problems; Constitutive manifold;
D O I
10.1007/s00466-017-1440-1
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The use of constitutive equations calibrated from data has been implemented into standard numerical solvers for successfully addressing a variety problems encountered in simulation-based engineering sciences (SBES). However, the complexity remains constantly increasing due to the need of increasingly detailed models as well as the use of engineered materials. Data-Driven simulation constitutes a potential change of paradigm in SBES. Standard simulation in computational mechanics is based on the use of two very different types of equations. The first one, of axiomatic character, is related to balance laws (momentum, mass, energy,...), whereas the second one consists of models that scientists have extracted from collected, either natural or synthetic, data. Data-driven (or data-intensive) simulation consists of directly linking experimental data to computers in order to perform numerical simulations. These simulations will employ laws, universally recognized as epistemic, while minimizing the need of explicit, often phenomenological, models. The main drawback of such an approach is the large amount of required data, some of them inaccessible from the nowadays testing facilities. Such difficulty can be circumvented in many cases, and in any case alleviated, by considering complex tests, collecting as many data as possible and then using a data-driven inverse approach in order to generate the whole constitutive manifold from few complex experimental tests, as discussed in the present work.
引用
收藏
页码:813 / 826
页数:14
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