Modeling In-Flight Ice Accretion Under Uncertain Conditions

Abstract

In-flight ice accretion under parametric uncertainty is investigated. Three test cases are presented that reproduce experiments carried out at the NASA’s Glenn Icing Research Tunnel facility. A preliminary accuracy assessment, achieved by comparing numerical predictions against experimental observations, confirms the robustness and the predictiveness of the computerized icing model. Besides, sensitivity analyses highlight the variance of the targeted outputs with respect to the different uncertain inputs. In rime icing conditions, a predominant role is played by the uncertainty affecting the airfoil angle of attack, the cloud liquid water content, and the mean volume diameter of droplets. In glaze icing conditions, the sensitivity analysis shows instead that the output variability is due mainly to the ambient temperature uncertainty. Moreover, this paper exposes a challenge inherent in the approximation of the full icing model by means of standard (linear) polynomial chaos regression techniques. The complexity is related to the approximation of the model behavior in domain regions scarcely affected by ice buildup. To mitigate this issue, a nonlinear regression method is proposed and applied.