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Data Driven Computing with noisy material data sets.
- Source :
-
Computer Methods in Applied Mechanics & Engineering . Nov2017, Vol. 326, p622-641. 20p. - Publication Year :
- 2017
-
Abstract
- We formulate a Data Driven Computing paradigm, termed max-ent Data Driven Computing, that generalizes distance-minimizing Data Driven Computing and is robust with respect to outliers. Robustness is achieved by means of clustering analysis. Specifically, we assign data points a variable relevance depending on distance to the solution and on maximum-entropy estimation. The resulting scheme consists of the minimization of a suitably-defined free energy over phase space subject to compatibility and equilibrium constraints. Distance-minimizing Data Driven schemes are recovered in the limit of zero temperature. We present selected numerical tests that establish the convergence properties of the max-ent Data Driven solvers and solutions. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00457825
- Volume :
- 326
- Database :
- Academic Search Index
- Journal :
- Computer Methods in Applied Mechanics & Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 125546210
- Full Text :
- https://doi.org/10.1016/j.cma.2017.07.039