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Efficient Uncertainty Quantification of Turbulent Flows through Supersonic ORC Nozzle Blades

Article dans une revue avec comité de lecture
Auteur
BUFI, Elio Antonio
134975 Laboratoire de Dynamique des Fluides [DynFluid]
CINNELLA, Paola
134975 Laboratoire de Dynamique des Fluides [DynFluid]

URI
http://hdl.handle.net/10985/15316
DOI
10.1016/j.egypro.2015.12.018
Date
2015
Journal
Energy Procedia

Résumé

This work aims at assessing different Uncertainty Quantification (UQ) methodologies for the stochastic analysis and robust design of Organic Rankine Cycle (ORC) turbines under multiple uncertainties. Precisely, we investigate the capability of several state-of-the art UQ methods to efficiently and accurately compute the average and standard deviation of the aerodynamic performance of supersonic ORC turbine expanders, whose geometry is preliminarily designed by means of a generalized Method Of Characteristics (MOC). Stochastic solutions provided by the adaptive Simplex Stochastic Collocation method, a Kriging-based response surface method, and a second-order accurate Method of Moments are compared to a reference solution obtained by running a full-factorial Probabilistic Collocation Method (PCM). The computational cost required to estimate the average adiabatic efficiency, Mach number and pressure coefficient, as well as their standard deviations, to within a given tolerance level is compared, and conclusions are drawn about the more suitable method for the robust design of ORC turbines.

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Documents liés

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  • Sensitivity of Supersonic ORC Turbine Injector Designs to Fluctuating Operating Conditions 
    Communication avec acte
    BUFI, Elio Antonio; CINNELLA, Paola; MERLE, Xavier; CINNELLA, Paola (ASME, 2015)
    The design of an efficient organic rankine cycle (ORC) expander needs to take properly into account strong real gas effects that may occur in given ranges of operating conditions, which can also be highly variable. In this ...
  • Convergence of Fourier-based time methods for turbomachinery wake passing problems 
    Article dans une revue avec comité de lecture
    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 ...
  • Bayesian estimates of parameter variability in the k − ε turbulence model 
    Article dans une revue avec comité de lecture
    EDELING, Wouter Nico; CINNELLA, Paola; DWIGHT, Richard P.; BIJL, H. (Elsevier, 2014)
    In this paper we are concerned with obtaining estimates for the error in Reynolds-Averaged Navier-Stokes (RANS) simulations based on the Launder-Sharma k−ε turbulence closure model, for a limited class of flows. In particular ...
  • Predictive RANS simulations via Bayesian Model-Scenario Averaging 
    Article dans une revue avec comité de lecture
    CINNELLA, Paola (Elsevier, 2014)
    The turbulence closure model is the dominant source of error in most Reynolds-Averaged Navier–Stokes simulations, yet no reliable estimators for this error component currently exist. Here we develop a stochastic, a posteriori ...
  • Airfoil Shape Optimization for Transonic Flows of Bethe–Zel’dovich–Thompson Fluids 
    Article dans une revue avec comité de lecture
    CONGEDO, Pietro; CORRE, Christophe; CINNELLA, Paola (American Institute of Aeronautics and Astronautics, 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 ...

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