Publication detail

Taylor Series Expansion for Functions of Correlated Random Variables

NOVÁK, L.

Original Title

Taylor Series Expansion for Functions of Correlated Random Variables

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

Semi-probabilistic approach in combination with non-linear finite element method is employed more frequently nowadays for design and assessment of structures. In that case, it is crucial to estimate statistical moments of structural resistance assuming uncertain input variables. The task is the estimation of statistical moments of function of random variables solved by finite element method. One of the solutions is represented by Taylor series expansion, which can be further used for the derivation of specific differencing schemes. The paper is focused on derivation of accurate differencing schemes for functions of correlated random variables. It is numerically shown, that the proposed differencing schemes are more accurate in comparison to standard scheme in case of strong correlation.

Keywords

Taylor series expansion; statistical correlation; estimation of statistical moments; semi-probabilistic approach

Authors

NOVÁK, L.

Released

28. 1. 2021

Publisher

Vysoké učení technické v Brně, Fakulta stavební

Location

Brno, Česká republika

ISBN

978-80-86433-75-2

Book

Proceedings of Juniorstav 2021

Pages from

364

Pages to

368

Pages count

5

BibTex

@inproceedings{BUT168853,
  author="Lukáš {Novák}",
  title="Taylor Series Expansion for Functions of Correlated Random Variables",
  booktitle="Proceedings of Juniorstav 2021",
  year="2021",
  pages="364--368",
  publisher="Vysoké učení technické v Brně, Fakulta stavební",
  address="Brno, Česká republika",
  isbn="978-80-86433-75-2"
}