Bayesian quantification of thermodynamic uncertainties in dense gas flows
TypeArticles dans des revues avec comité de lecture
A Bayesian inference methodology is developed for calibrating complex equations of state used in numerical fluid flow solvers. Precisely, the input parameters of three equations of state commonly used for modeling the thermodynamic behavior of so-called dense gas flows, – i.e. flows of gases characterized by high molecular weights and complex molecules, working in thermodynamic conditions close to the liquid-vapor saturation curve–, are calibrated by means of Bayesian inference from reference aerodynamic data for a dense gas flow over a wing section. Flow thermodynamic conditions are such that the gas thermodynamic behavior strongly deviates from that of a perfect gas. In the aim of assessing the proposed methodology, synthetic calibration data –specifically, wall pressure data– are generated by running the numerical solver with a more complex and accurate thermodynamic model. The statistical model used to build the likelihood function includes a model-form inadequacy term, accounting for the gap between the model output associated to the best-fit parameters, and the rue phenomenon. Results show that, for all of the relatively simple models under investigation, calibrations lead to informative posterior probability density distributions of the input parameters and improve the predictive distribution significantly. Nevertheless, calibrated parameters strongly differ from their expected physical values. The relationship between this behavior and model-form inadequacy is discussed.
Files in this item
Showing items related by title, author, creator and subject.
MERLE, Xavier; CINNELLA, Paola (Elsevier, 2015)A Bayesian inference methodology is developed for calibrating complex equations of state used in numerical fluid flow solvers. Precisely, the input parameters of three equations of state commonly used for modeling the ...
GOMAR, Adrien; BOUVY, Quentin; SICOT, Frédéric; DUFOUR, Guillaume; CINNELLA, Paola; FRANCOIS, Benjamin (Elsevier, 2014)The convergence of Fourier-based time methods applied to turbomachinery flows is assessed. The focus is on the harmonic balance method, which is a timedomain Fourier-based approach standing as an efficient alternative to ...
SCIACOVELLI, L.; CINNELLA, Paola (ASME, 2014)Transonic flows through axial, multi-stage, transcritical ORC turbines, are investigated by using a numerical solver including advanced multiparameter equations of state and a high-order discretization scheme. The working ...
CONGEDO, Pietro; CORRE, Christophe; CINNELLA, Paola (AIAA, 2007)High-performance airfoils for transonic flows of Bethe–Zel’dovich–Thompson fluids are constructed using a robust and efficient Euler flow solver coupled with a multi-objective genetic algorithm. Bethe–Zel’dovich– Thompson ...
Numerical investigation of dense gas flows through transcritical multistage axial Organic Rankine Cycle turbines SCIACOVELLI, Lucas; CINNELLA, Paola (2013)Many recent studies suggest that supercritical Organic Rankine Cycles have a great potential for lowtemperature heat recovery applications, since they allow better recovery efficiency for a simplified cycle architecture. ...