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NOVÁK, L. NOVÁK, D.
Originální název
Estimation of coefficient of variation for structural analysis: The correlation interval approach
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
angličtina
Originální abstrakt
The paper is focused on the efficient estimation of the coefficient of variation for functions of correlated and uncorrelated random variables. Specifically, the paper deals with time-consuming functions solved by the non-linear finite element method. In this case, the semi-probabilistic methods must reduce the number of simulations as much as possible under several simplifying assumptions while preserving the accuracy of the obtained results. The selected commonly used methods are reviewed with the intent of investigating their theoretical background, assumptions and limitations. It is shown, that Taylor series expansion can be modified for fully correlated random variables, which leads to a significant reduction in the number of simulations independent of the dimension of the stochastic model (the number of input random variables). The concept of the interval estimation of the coefficient of variation using Taylor series expansion is proposed and applied to numerical examples of increasing complexity. It is shown that the obtained results correspond to the theoretical conclusions of the proposed method.
Klíčová slova
Semi-probabilistic approach; Estimation of coefficient of variation; Taylor series expansion; Correlation among random variables; Nataf transformation
Autoři
NOVÁK, L.; NOVÁK, D.
Vydáno
1. 9. 2021
Nakladatel
ELSEVIER
Místo
AMSTERDAM
ISSN
0167-4730
Periodikum
Structural Safety
Ročník
92
Číslo
1
Stát
Nizozemsko
Strany od
Strany do
11
Strany počet
URL
https://www.sciencedirect.com/science/article/abs/pii/S0167473021000254
BibTex
@article{BUT172054, author="Lukáš {Novák} and Drahomír {Novák}", title="Estimation of coefficient of variation for structural analysis: The correlation interval approach", journal="Structural Safety", year="2021", volume="92", number="1", pages="1--11", doi="10.1016/j.strusafe.2021.102101", issn="0167-4730", url="https://www.sciencedirect.com/science/article/abs/pii/S0167473021000254" }