2014/11/13 by Anthony M. DeGennaro, Clarence W. Rowley, DeGennaro, Anthony M. +3
Decision Sciences · Engineering · Environmental Science · #Data Analysis #FOS: Physical sciences #Icing and De-icing Technologies #Probabilistic and Robust Engineering Design #Statistics and Probability (physics.data-an) #Wind and Air Flow Studies
paper · pdf · doi:10.48550/arxiv.1411.3642
openalex publication_date 2014/11/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The formation and accretion of ice on the leading edge of a wing can be\ndetrimental to airplane performance. Complicating this reality is the fact that\neven a small amount of uncertainty in the shape of the accreted ice may result\nin a large amount of uncertainty in aerodynamic performance metrics (e.g.,\nstall angle of attack). The main focus of this work concerns using the\ntechniques of Polynomial Chaos Expansions (PCE) to quantify icing uncertainty\nmuch more quickly than traditional methods (e.g., Monte Carlo). First, we\npresent a brief survey of the literature concerning the physics of wing icing,\nwith the intention of giving a certain amount of intuition for the physical\nprocess. Next, we give a brief overview of the background theory of PCE.\nFinally, we compare the results of Monte Carlo simulations to PCE-based\nuncertainty quantification for several different airfoil icing scenarios. The\nresults are in good agreement and confirm that PCE methods are much more\nefficient for the canonical airfoil icing uncertainty quantification problem\nthan Monte Carlo methods.\n