Multidimensional quantification of uncertainty and application to a turbulent mixing model

Christos Barmparousis, Dimitris Drikakis

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This paper concerns the implementation of the generalized polynomial chaos (gPC) approach for parametric studies, including the quantification of uncertainty (UQ), of turbulence modelling. The method is applied to Richtmyer-Meshkov turbulent mixing. The K-L turbulence model has been chosen as a prototypical example, and parametric studies have been performed to examine the effects of closure coefficients and initial conditions on the flow results. It is shown that the proposed method can be used to obtain a relation between the uncertain inputs and the monitored flow quantities, thus efficiently performing parametric studies. It allows the simultaneous calibration and quantification of uncertainty in an efficient numerical framework.

LanguageEnglish
Pages385-403
Number of pages19
JournalInternational Journal for Numerical Methods in Fluids
Volume85
Issue number7
Early online date11 May 2017
DOIs
Publication statusPublished - 10 Nov 2017

Fingerprint

Turbulent Mixing
Quantification
Uncertainty
Turbulence models
Chaos theory
Turbulence Modeling
Polynomial Chaos
Turbulence
Generalized Polynomials
Polynomials
Calibration
Turbulence Model
Closure
Initial conditions
Model
Coefficient

Keywords

  • calibration
  • compressible flows
  • meta-model
  • optimisation
  • polynomial chaos
  • sensitivity
  • turbulence modelling
  • uncertainty quantification

Cite this

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abstract = "This paper concerns the implementation of the generalized polynomial chaos (gPC) approach for parametric studies, including the quantification of uncertainty (UQ), of turbulence modelling. The method is applied to Richtmyer-Meshkov turbulent mixing. The K-L turbulence model has been chosen as a prototypical example, and parametric studies have been performed to examine the effects of closure coefficients and initial conditions on the flow results. It is shown that the proposed method can be used to obtain a relation between the uncertain inputs and the monitored flow quantities, thus efficiently performing parametric studies. It allows the simultaneous calibration and quantification of uncertainty in an efficient numerical framework.",
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Multidimensional quantification of uncertainty and application to a turbulent mixing model. / Barmparousis, Christos; Drikakis, Dimitris.

In: International Journal for Numerical Methods in Fluids , Vol. 85, No. 7, 10.11.2017, p. 385-403.

Research output: Contribution to journalArticle

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