Detail publikace

Variance-based adaptive sequential sampling for Polynomial Chaos Expansion

NOVÁK, L. VOŘECHOVSKÝ, M. SADÍLEK, V. SHIELDS, M.

Originální název

Variance-based adaptive sequential sampling for Polynomial Chaos Expansion

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

his paper presents a novel adaptive sequential sampling method for building Polynomial Chaos Expansion surrogate models. The technique enables one-by-one extension of an experimental design while trying to obtain an optimal sample at each stage of the adaptive sequential surrogate model construction process. The proposed sequential sampling strategy selects from a pool of candidate points by trying to cover the design domain proportionally to their local variance contribution. The proposed criterion for the sample selection balances both exploitation of the surrogate model and exploration of the design domain. The adaptive sequential sampling technique can be used in tandem with any user-defined sampling method, and here was coupled with commonly used Latin Hypercube Sampling and advanced Coherence D-optimal sampling in order to present its general performance. The obtained numerical results confirm its superiority over standard non-sequential approaches in terms of surrogate model accuracy and estimation of the output variance.

Klíčová slova

Polynomial Chaos Expansion; Adaptive sampling; Sequential sampling; Coherence optimal sampling;

Autoři

NOVÁK, L.; VOŘECHOVSKÝ, M.; SADÍLEK, V.; SHIELDS, M.

Vydáno

1. 12. 2021

Nakladatel

ELSEVIER

Místo

AMSTERDAM

ISSN

0045-7825

Periodikum

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Ročník

386

Číslo

114105

Stát

Nizozemsko

Strany od

1

Strany do

25

Strany počet

25

URL

https://www.sciencedirect.com/science/article/pii/S0045782521004369?dgcid=author

BibTex

@article{BUT172652,
  author="Lukáš {Novák} and Miroslav {Vořechovský} and Václav {Sadílek} and Michael {Shields}",
  title="Variance-based adaptive sequential sampling for Polynomial Chaos Expansion",
  journal="COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING",
  year="2021",
  volume="386",
  number="114105",
  pages="1--25",
  doi="10.1016/j.cma.2021.114105",
  issn="0045-7825",
  url="https://www.sciencedirect.com/science/article/pii/S0045782521004369?dgcid=author"
}