scholarly journals Consistent data-driven computational mechanics

2018 ◽  
Author(s):  
D. González ◽  
F. Chinesta ◽  
E. Cueto
Keyword(s):  
Computational Mechanics ◽  
Data Driven

A New Uncertainty Analysis-Based Framework for Data-Driven Computational Mechanics

2021 ◽  
pp. 1-22
Author(s):  
Xu Guo ◽  
Zongliang Du ◽  
Chang Liu ◽  
Shan Tang
Keyword(s):  
Phase Space ◽  
Uncertainty Analysis ◽  
Distinctive Feature ◽  
Computational Mechanics ◽  
Problem Formulation ◽  
Solution Set ◽  
Data Driven ◽  
Data Set ◽  
Classical Counterpart ◽  
Single Solution

Abstract In the present paper, a new uncertainty analysis-based framework for data-driven computational mechanics (DDCM) is established. Compared with its practical classical counterpart, the distinctive feature of this framework is that uncertainty analysis is introduced into the corresponding problem formulation explicitly. Instated of only focusing on a single solution in phase space, a solution set is sought for in order to account for the influence of the multi-source uncertainties associated with the data set on the data-driven solutions. An illustrative example provided shows that the proposed framework is not only conceptually new, but also has the potential of circumventing the intrinsic numerical difficulties pertaining to the classical DDCM framework.

scholarly journals Model-free data-driven computational mechanics enhanced by tensor voting

2021 ◽  
Vol 373 ◽  
pp. 113499
Author(s):  
Robert Eggersmann ◽  
Laurent Stainier ◽  
Michael Ortiz ◽  
Stefanie Reese
Keyword(s):  
Computational Mechanics ◽  
Data Driven ◽  
Tensor Voting ◽  
Model Free ◽  
Free Data

scholarly journals Thermodynamically consistent data-driven computational mechanics

2018 ◽  
Vol 31 (1) ◽  
pp. 239-253 ◽  
Author(s):  
David González ◽  
Francisco Chinesta ◽  
Elías Cueto
Keyword(s):  
Computational Mechanics ◽  
Data Driven
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