Uncertainty quantification analysis of RANS of spray jets

Pietro Paolo Ciottoli, Andrea Petrocchi, Lorenzo Angelilli, Francisco Hernandez Perez, Riccardo Malpica Galassi, Francesco Picano, Mauro Valorani, Hong G. Im

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


Parametric uncertainty is propagated through Reynolds-averaged Navier-Stokes (RANS) computations of a prototypical acetone/air aerosol stream flowing in a dry air environment. Two parameters are considered as uncertain: the inflow velocity dissipation and a coefficient that blends the discrete random walk and the gradient-based dispersion models. A Bayesian setting is employed to represent the degree of belief about the parameters of interest in terms of probability theory, such that uncertainty is described with probability density functions. Random variables are represented by means of polynomial chaos expansions. The sensitivity of mean axial velocity and mean vapor mass fraction to the uncertain parameters is discussed.
Original languageEnglish (US)
Title of host publicationAIAA Propulsion and Energy 2020 Forum
PublisherAmerican Institute of Aeronautics and Astronautics
ISBN (Print)9781624106026
StatePublished - Aug 17 2020

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): OSR-2019-CCF-1975-35
Acknowledgements: The authors acknowledge the support of the Italian Ministry of University and Research (MIUR) and King Abdullah University of Science and Technology OSR-2019-CCF-1975-35 Subaward Agreement. Computational resources were provided by the KAUST Supercomputing Laboratory (KSL).


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