AuthorsCiottoli, Pietro Paolo
Hernandez Perez, Francisco
Malpica Galassi, Riccardo
Im, Hong G.
KAUST DepartmentClean Combustion Research Center
Computational Reacting Flow Laboratory (CRFL)
Mechanical Engineering Program
Physical Science and Engineering (PSE) Division
KAUST Grant NumberOSR-2019-CCF-1975-35
Online Publication Date2020-08-17
Print Publication Date2020-08-24
Permanent link to this recordhttp://hdl.handle.net/10754/664796
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AbstractParametric 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.
CitationCiottoli, P. P., Petrocchi, A., Angelilli, L., Hernandez Perez, F. E., Malpica Galassi, R., Picano, F., … Im, H. G. (2020). Uncertainty quantification analysis of RANS of spray jets. AIAA Propulsion and Energy 2020 Forum. doi:10.2514/6.2020-3882
SponsorsThe 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).