Publication detail

On distribution-based global sensitivity analysis by polynomial chaos expansion

NOVÁK, L.

Original Title

On distribution-based global sensitivity analysis by polynomial chaos expansion

Type

journal article in Web of Science

Language

English

Original Abstract

This paper presents a novel distribution-based global sensitivity analysis based on the Kullback-Leibler divergence derived directly from generalized polynomial chaos expansion (PCE). The synergy between PCE and Gram-Charlier expansion is utilized for derivation of novel and computationally efficient sensitivity indices. In contrast to a standard procedure for estimation of higher statistical moments, this paper reviews standard linearization problem of Hermite and Jacobi polynomials in order to efficiently estimate skewness and kurtosis direclty from PCE. Higher statistical moments are used for an estimation of probability distribution by Gram-Charlier expansion, which is represented by derived explicit cumulative distribution function. The proposed sensitivity indices taking the whole probability distribution into account are calculated for several numerical examples of increasing complexity in order to present their possibilities. It is shown, that the proposed sensitivity indices are obtained without any additional computational demands together with Sobol indices, and thus can be easily used as complementary information for a complex sensitivity analysis or any decision making in industrial applications. Application of the proposed approach on engineering structure is presented in case of prestressed concrete roof girders failing shear. Moreover, the potential of the proposed approach for reliability-oriented sensitivity analysis is investigated in pilot numerical example.(c) 2022 Elsevier Ltd. All rights reserved.

Keywords

Sensitivity analysis; Gram-Charlier expansion; Surrogate modelling; Kullback-Leibler divergence; Polynomial chaos expansion

Authors

NOVÁK, L.

Released

15. 7. 2022

Publisher

PERGAMON-ELSEVIER SCIENCE LTD

Location

OXFORD

ISBN

0045-7949

Periodical

COMPUTERS & STRUCTURES

Year of study

267

Number

1

State

United Kingdom of Great Britain and Northern Ireland

Pages from

1

Pages to

14

Pages count

14

URL

https://www.sciencedirect.com/science/article/pii/S0045794922000682

BibTex

@article{BUT178110,
  author="Lukáš {Novák}",
  title="On distribution-based global sensitivity analysis by polynomial chaos expansion",
  journal="COMPUTERS & STRUCTURES",
  year="2022",
  volume="267",
  number="1",
  pages="1--14",
  doi="10.1016/j.compstruc.2022.106808",
  issn="0045-7949",
  url="https://www.sciencedirect.com/science/article/pii/S0045794922000682"
}