Efficient Prediction of Ice Shapes in CFD Simulation of In-flight Icing Using a POD-Based Reduced Order Model

In-flight icing is a persistent threat to aircraft safety and, in particular, the droplet impingement areas and intensity on the aircraft surfaces must be further investigated for anti-icing and de-icing devices. As a step toward the prediction of droplet impingement on aircraft, an Eulerian-based droplet impingement code that provides collection efficiency is developed in this paper. A computational fluid dynamics solver was also developed to solve the dry air. Then, a proper orthogonal decomposition method (a reduced order model) that optimally captures the energy content from a large multi-dimensional data set is used to predict the collection efficiency and the iced shapes on an airfoil following the mean volume diameter, liquid water content, and angles of attack. As a result, it is shown that the collection efficiency and iced shapes are in good agreement with the simulated and predicted results.