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Enhanced goal-oriented error assessment and computational strategies in adaptive reduced basis solver for stochastic problems

Author
Serafin, K.; Magnain, B.; Florentin, E.; Pares, N.; Diez, P.
Type of activity
Journal article
Journal
International journal for numerical methods in engineering
Date of publication
2017-05-04
Volume
110
Number
5
First page
440
Last page
466
DOI
https://doi.org/10.1002/nme.5363 Open in new window
Project funding
n-silico simulation-based engineering for real-time decision making: application to electric grids and automotion
Repository
http://hdl.handle.net/2117/104348 Open in new window
https://www.lacan.upc.edu/scientificPublications/files/pdfs/RB_CPU_lacan_preprint.pdf Open in new window
URL
http://onlinelibrary.wiley.com/doi/10.1002/nme.5363/abstract Open in new window
Abstract
This work focuses on providing accurate low-cost approximations of stochastic ¿nite elements simulations in the framework of linear elasticity. In a previous work, an adaptive strategy was introduced as an improved Monte-Carlo method for multi-dimensional large stochastic problems. We provide here a complete analysis of the method including a new enhanced goal-oriented error estimator and estimates of CPU (computational processing unit) cost gain. Technical insights of these two topics are pres...
Citation
Serafin, K., Magnain, B., Florentin, E., Pares, N., Diez, P. Enhanced goal-oriented error assessment and computational strategies in adaptive reduced basis solver for stochastic problems. "International journal for numerical methods in engineering", 4 Maig 2017, vol. 110, núm. 5, p. 440-466.
Keywords
adaptivity, goal-oriented error assessment, reduced basis, stochastic modeling
Group of research
LACÀN - Numerical Methods for Applied Sciences and Engineering

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