Abstract In computational fluid dynamics simulations of industrial flows, models based on the Reynolds-averaged Navier–Stokes (RANS) equations are expected to play an important role in decades to come. However, model uncertainties are still a major obstacle for the predictive capability of RANS simulations. This review examines both the parametric and structural uncertainties in turbulence models. We review recent literature on data-free (uncertainty propagation) and data-driven (statistical inference) approaches for quantifying and reducing model uncertainties in RANS simulations. Moreover, the fundamentals of uncertainty propagation and Bayesian inference are introduced in the context of RANS model uncertainty quantification. Finally, the literature on uncertainties in scale-resolving simulations is briefly reviewed with particular emphasis on large eddy simulations.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Quantification of model uncertainty in RANS simulations: A review


    Contributors:

    Published in:

    Publication date :

    2018-10-08


    Size :

    31 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Quantification of model uncertainty in RANS simulations: A review

    Xiao, Heng / Cinnella, Paola | Elsevier | 2019



    UNCERTAINTY QUANTIFICATION ANALYSIS OF RANS OF SPRAY JETS

    Ciottoli, Pietro Paolo / Petrocchi, Andrea / Angelilli, Lorenzo et al. | TIBKAT | 2020


    Uncertainty Quantification Analysis of RANS of Spray Jets

    Ciottoli, Pietro Paolo / Petrocchi, Andrea / Angelilli, Lorenzo et al. | AIAA | 2020


    Unsteady RANS Simulations with Uncertainty Quantification of Spray Combustor Under Liquid Rocket Engine Relevant Conditions

    Cavalieri, Davide / Liberatori, Jacopo / Malpica Galassi, Riccardo et al. | AIAA | 2023