2015/05/28 by Anthony M. DeGennaro, Clarence W. Rowley, DeGennaro, Anthony M. +3
Decision Sciences · Earth and Planetary Sciences · Engineering · #Cryospheric studies and observations #Data Analysis #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Icing and De-icing Technologies #Probabilistic and Robust Engineering Design #Statistics and Probability (physics.data-an)
paper · pdf · doi:10.48550/arxiv.1505.07844
openalex publication_date 2015/05/28 · openalex created_date 2022/10/03 · openalex updated_date 2026/07/28
The formation and accretion of ice on the leading edge of an airfoil can be\ndetrimental to aerodynamic performance. Furthermore, the geometric shape of\nleading edge ice profiles can vary significantly depending on a wide range of\nphysical parameters, which can translate into a wide variability in aerodynamic\nperformance. The purpose of this work is to explore the variability in airfoil\naerodynamic performance that results from variability in leading edge ice shape\nprofile. First, we demonstrate how to identify a low-dimensional set of\nparameters that governs ice shape from a database of ice shapes using Proper\nOrthogonal Decomposition (POD). Then, we investigate the effects of uncertainty\nin the POD coefficients. This is done by building a global response surface\nsurrogate using Polynomial Chaos Expansions (PCE). To construct this surrogate\nefficiently, we use adaptive sparse grid sampling of the POD parameter space.\nWe then analyze the data from a statistical standpoint.\n