![]() (2022), "Estimates of turbulence modeling uncertainties in NACA65 cascade flow predictions by Bayesian model-scenario averaging", International Journal of Numerical Methods for Heat & Fluid Flow, Vol. CitationÄe Zordo-Banliat, M., Merle, X., Dergham, G. The authors acknowledge the french National Agency for Research and Technology ( ANRT ) for providing support through the CIFRE PhD grant number 2018-1370. The authors then compare the capabilities of three different criteria. In this paper, three mixture models are constructed, based on alternative choices of the scenario probabilities. The role of such PMFs is to assign higher probability to calibration scenarios more likely to provide an accurate estimate of model coefficients for the new flow. suitable prior probability mass functions (PMFs) for the calibration scenarios. Therefore we cannot perfectly represent the effects of turbulence in the. ![]() A delicate step in the BMSA is the selection of suitable scenario-weighting criteria, i.e. ![]()
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