Detail publikačního výsledku

Distribution-Based Global Sensitivity Analysis By Polynomial Chaos Expansion

NOVÁK, L.; NOVÁK, D.

Originální název

Distribution-Based Global Sensitivity Analysis By Polynomial Chaos Expansion

Anglický název

Distribution-Based Global Sensitivity Analysis By Polynomial Chaos Expansion

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

The paper is focused on study of distribution based global sensitivity indices derived directly from polynomial chaos expansion. The significant advantage is that, once the approximation in form of polynomial chaos expansion is available it is possible to obtain first statistical moments, Sobol indices and also distribution function with proposed moment-independent sensitivity indices without additional computational demands. The key idea is to use only specific part of approximation and compare obtained conditional probability cumulative distribution function to original distribution assuming all variables free to vary. The difference between distributions is measured by Cramer-von Misses distance herein. However, it is generally possible to employ any type of measure. The method is validated by analytical example with known solution. Proposed approach is highly efficient and thus it can be recommended for practical applications, when it is not possible to perform sensitivity analysis by standard Monte Carlo approach.

Anglický abstrakt

The paper is focused on study of distribution based global sensitivity indices derived directly from polynomial chaos expansion. The significant advantage is that, once the approximation in form of polynomial chaos expansion is available it is possible to obtain first statistical moments, Sobol indices and also distribution function with proposed moment-independent sensitivity indices without additional computational demands. The key idea is to use only specific part of approximation and compare obtained conditional probability cumulative distribution function to original distribution assuming all variables free to vary. The difference between distributions is measured by Cramer-von Misses distance herein. However, it is generally possible to employ any type of measure. The method is validated by analytical example with known solution. Proposed approach is highly efficient and thus it can be recommended for practical applications, when it is not possible to perform sensitivity analysis by standard Monte Carlo approach.

Klíčová slova

Distribution-based sensitivity; Polynomial chaos expansion; Uncertainty quantification

Klíčová slova v angličtině

Distribution-based sensitivity; Polynomial chaos expansion; Uncertainty quantification

Autoři

NOVÁK, L.; NOVÁK, D.

Rok RIV

2021

Vydáno

24.11.2020

Nakladatel

Institute of Theretical and Applied Mechanics of the Czech Academy of Sciences

Místo

Praha

ISBN

978-80-214-5896-3

Kniha

ENGINEERING MECHANICS 2018 PROCEEDINGS, VOL 26

Strany od

380

Strany do

383

Strany počet

4

BibTex

@inproceedings{BUT168096,
  author="Lukáš {Novák} and Drahomír {Novák}",
  title="Distribution-Based Global Sensitivity Analysis By Polynomial Chaos Expansion",
  booktitle="ENGINEERING MECHANICS 2018 PROCEEDINGS, VOL 26",
  year="2020",
  pages="380--383",
  publisher="Institute of Theretical and Applied Mechanics of the Czech Academy of Sciences",
  address="Praha",
  isbn="978-80-214-5896-3"
}