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Uncertainty quantification in chemical systems
Author(s) -
Najm H. N.,
Debusschere B. J.,
Marzouk Y. M.,
Widmer S.,
Le Maître O. P.
Publication year - 2009
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/nme.2551
Subject(s) - polynomial chaos , uncertainty quantification , probabilistic logic , representation (politics) , bayesian inference , inference , propagation of uncertainty , polynomial , probability density function , bayesian probability , mathematics , computer science , algorithm , mathematical optimization , monte carlo method , artificial intelligence , machine learning , statistics , mathematical analysis , politics , law , political science
We demonstrate the use of multiwavelet spectral polynomial chaos techniques for uncertainty quantification in non‐isothermal ignition of a methane–air system. We employ Bayesian inference for identifying the probabilistic representation of the uncertain parameters and propagate this uncertainty through the ignition process. We analyze the time evolution of moments and probability density functions of the solution. We also examine the role and significance of dependence among the uncertain parameters. We finish with a discussion of the role of non‐linearity and the performance of the algorithm. Copyright © 2009 John Wiley & Sons, Ltd.