NACA0012 wing with rounded tip

In this paper the Probabilistic Collocation method is used for uncertainty quantification of operational uncertainties in a transonic axial flow compressor (i.e. NASA Rotor 37).Compressor rotors are components of a gas turbine that are highly sensitive to operational and geometrical uncertainties. Validation of the Probabilistic Collocation method with a Monte Carlo simulation using 10,000 Latin Hypercube samples demonstrated that the Probabilistic Collocation method can successfully be applied to a turbomachinery case. The flow through the rotor is characterized by a bow shock in front of the leading edge, which interacts with the boundary layer of the next blade. The total pressure profile at the inlet of the rotor is assumed to be uncertain. A symmetric beta distribution was used for the pressure profile, with the standard deviation such that the uncertainty is in the same order of the measurement accuracy reported in literature. The mass flow was shown to be the most sensitive to the uncertainty, while the efficiency is least affected. It was shown by the compressor maps that is important to take the uncertainty in the total pressure profile at the inlet into account. The standard deviation of the static pressure field showed that the largest variation is present near the shock wave and mainly in the region of the strongest shock, which is near the tip of the blade.

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NACA0012 wing with rounded tip

Cited by 3 publications

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Toward Predictive RANS and SRS Computations of Turbulent External Flows of Practical Interest

Toward Predictive RANS and SRS Computations of Turbulent External Flows of Practical Interest

Simulation of Wingtip Vortex Flows with Reynolds-Averaged Navier–Stokes and Scale-Resolving Simulation Methods

The Application of the Probabilistic Collocation Method to a Transonic Axial Flow Compressor

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