Uncertainty Analysis for Large-Scale Industrial Radial Compressors

Abstract

This paper analyzes the influence of uncertainties on large-scale industrial radial compressors. The goal is to verify the robustness of new compressor designs towards operational and geometrical uncertainties. Key uncertainties for compressors are identified. Detailed measurements are conducted and modeled by probability distributions. These models then serve as input for the uncertainty analysis. For the uncertainty analysis different techniques are compared. The focus is on computationally efficient techniques, i.e., the required number of CFD simulations for the uncertainty analysis should be minimal. Promising methods are the Probabilistic Collocation Method and techniques that use response surface models in combination with the i-optimal design approach for generating sample points. Pure Monte Carlo simulations are not practical as they are too time-consuming. The key uncertainty considered here is the surface roughness. The effect is modeled with a commercial CFD RANS solver. The uncertainty analyzes show a performance decrease and variation for roughness values above the limit of hydraulically smooth surfaces.