Probabilistic analysis of compression system stability using importance sampling

Abstract

The probability of instability is computed via a new approach based on Importance Sampling and a dynamic compression system model. In contrast to ordinary Monte Carlo methods Importance Sampling offers reduced confidence intervals, reduced number of samples and reduced model execution times. The new approach avoids some of the problematic details associated with the traditional stability margin methodology including the additivity, linearity and normality assumptions. It also captures successfully the phase interaction effects between inlet distortion and stationary asymmetric tip clearance. The phase interaction is an example of a case when the stability margin approach fails to capture both the quantitative and qualitative behaviors.