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NOVÁK, L. NOVÁK, D.
Original Title
Stochastic Spectral Methods in Uncertainty Quantification
Type
journal article - other
Language
English
Original Abstract
Uncertainty quantification is an important part of a probabilistic design of structures. Nonetheless, common Monte Carlo methods are highly computationally demanding or even not feasible for this task, especially in case of mathematical models of physical problems solved by finite element method. Therefore, the paper is focused on the efficient alternative approach for uncertainty quantification-stochastic spectral expansion, represented herein by Polynomial Chaos Expansion. In recent years, an application of stochastic spectral methods in uncertainty quantification is the topic of research for many scientists in various fields of science and its efficiency was shown by various studies. The paper presents basic theoretical background of polynomial chaos expansion and its connection to uncertainty quantification. The possibility of efficient statistical and sensitivity analysis is investigated and an application in analytical examples with known reference solution is presented herein. Moreover, practical implementation of methodology is discussed and developed SW tool is presented herein.
Keywords
Polynomial chaos expansion, Sensitivity analysis, Statistical analysis, Uncertainty quantification.
Authors
NOVÁK, L.; NOVÁK, D.
Released
31. 12. 2019
Publisher
VSB - Technical University of Ostrava
Location
Ostrava, Czec Republic
ISBN
1804-4824
Periodical
Transactions of the VŠB – Technical University of Ostrava, Civil Engineering Series
Year of study
19
Number
2
State
Czech Republic
Pages from
48
Pages to
53
Pages count
6
URL
http://tces.vsb.cz/Home/ArticleDetail/486
BibTex
@article{BUT162604, author="Lukáš {Novák} and Drahomír {Novák}", title="Stochastic Spectral Methods in Uncertainty Quantification", journal="Transactions of the VŠB – Technical University of Ostrava, Civil Engineering Series", year="2019", volume="19", number="2", pages="48--53", doi="10.35181/tces-2019-0019", issn="1804-4824", url="http://tces.vsb.cz/Home/ArticleDetail/486" }