Efficient uncertainty quantification in computational fluid dynamics

When modeling physical systems, several sources of uncertainty are present. For example, variability in boundary conditions like free stream velocity or ambient pressure are always present. Furthermore, uncertainties in geometry arise from production tolerances, wear or unknown deformations under loading. Uncertainties in computational fluid...

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

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...

Probabilistic collocation used in a Two-Step approached for efficient uncertainty quantification in computational fluid dynamics

In this paper a Two-Step approach is presented for uncertainty quantification for expensive problems with multiple uncertain parameters. Both steps are performed using the Probabilistic Collocation method. The first step consists of a sensitivity analysis to identify the most important parameters of the problem. The sensitivity derivatives are...

Airfoil Analysis with Uncertain Geometry using the Probabilistic Collocation method

Due to manufacturing tolerances, the airfoil of a wing after production is never exactly the same as the designed airfoil. Also during operation the geometry may change due to aerodynamic loading, icing or wear of the construction. The geometry can, therefore, be treated as uncertain. Uncertainties in the geometry of an airfoil are expected to...