Uncertainty Quantification: A Stochastic Method for Heat Transfer Prediction Using LES

In computational fluid dynamics (CFD), it is possible to identify namely two uncertainties: epistemic, related to the turbulence model, and aleatoric, representing the randomunknown conditions such as the boundary values and or geometrical variations. In the field of epistemic uncertainty, large eddy simulation (LES and DES) is the state of the art in terms of turbulence closures to predict the heat transfer in internal channels. The problem is still unresolved for the stochastic variations and how to include these effects in the LES studies. In this paper, for the first time in literature, a stochastic approach is proposed to include these variations in LES. By using a classical uncertainty quantification approach, the probabilistic collocation method is coupled to numerical large eddy simulation (NLES) in a duct with pin fins. The Reynolds number has been chosen as a stochastic variable with a normal distribution. The Reynolds number is representative of the uncertainties associated ...

L'articolo descrive l'utilizzo di un metodo di quantificazione dell'incertezza numerica applicato a un caso studio classico della refrigerazione interna di pale di alta pressione di turbina utilizzando il metodo LES. The article describes the use of a numerical method for the uncertainty quantification applied to a classic case study using LES.