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NOVÁK, L. NOVÁK, D.
Original Title
Estimation of coefficient of variation for structural analysis: The correlation interval approach
Type
journal article in Web of Science
Language
English
Original Abstract
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.
Keywords
Semi-probabilistic approach; Estimation of coefficient of variation; Taylor series expansion; Correlation among random variables; Nataf transformation
Authors
NOVÁK, L.; NOVÁK, D.
Released
1. 9. 2021
Publisher
ELSEVIER
Location
AMSTERDAM
ISBN
0167-4730
Periodical
Structural Safety
Year of study
92
Number
1
State
Kingdom of the Netherlands
Pages from
Pages to
11
Pages count
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" }