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Accuracy assessment of generalized parametric solutions for optimization and uncer-tainty quantification

Author
Diez, P.; Zlotnik, S.; Garcia, R.
Type of activity
Presentation of work at congresses
Name of edition
VII European Congress on Computational Methods in Applied Sciences and Engineering
Date of publication
2016
Presentation's date
2016-06-06
Book of congress proceedings
VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2016): Crete, Greece: June 5-10, 2016: proceedings
First page
1
Last page
1
URL
https://www.eccomas2016.org/proceedings/pdf/14228.pdf Open in new window
Abstract
Optimization of design and manufacturing is a real need of Industry and requires sampling repeatedly the computational models in different points of the multidimensional parametric design space. This undergoes an important computational effort and, in practice, a large time lapses before obtaining a reliable answer. The problem is similar in the framework of Uncertainty Quantification: characterizing a stochastic model requires solving a large number of deterministic instances, browsing a multid...
Keywords
Error Assessment, Proper Generalized Decomposition, Reduced Order Models
Group of research
LACÀN - Numerical Methods for Applied Sciences and Engineering

Participants