Aircraft Icing Severity Evaluation

Aircraft icing refers to the ice buildup on the surface of an aircraft flying in icing conditions. The ice accretion on the aircraft alters the original aerodynamic configuration and degrades the aerodynamic performances and may lead to unsafe flight conditions. Evaluating the flow structure, icing mechanism and consequences is of great importance to the development of an anti/deicing technique. Studies have shown computational fluid dynamics (CFD) and machine learning (ML) to be effective in predicting the ice shape and icing severity under different flight conditions. CFD solves a set of partial differential equations to obtain the air flow fields, water droplets trajectories and ice shape. ML is a branch of artificial intelligence and, based on the data, the self-improved computer algorithms can be effective in finding the nonlinear mapping relationship between the input flight conditions and the output aircraft icing severity features.

The ability of the ICE-T microphysics scheme in HARMONIE-AROME to predict aircraft icing

In-cloud icing is a major hazard for aviation traffic and forecasting of these events is an important task for weather agencies worldwide. A common tool utilised by aviation forecasters is an icing intensity index based on supercooled liquid water from numerical weather prediction models. We seek to validate the modified microphysics scheme, ICE-T, in the HARMONIE-AROME numerical weather prediction model with respect to aircraft icing. Icing intensities and supercooled liquid water derived from two 3-month winter season simulations with the original microphysics code, CTRL, and ICE-T are compared with pilot reports of icing and satellite retrieved values of liquid and ice water content from CloudSat-CALIPSO and liquid water path from AMSR-2. The results show increased supercooled liquid water and higher icing indices in ICE-T. Several different thresholds and sizes of neighbourhood areas for icing forecasts were tested out, and ICE-T captures more of the reported icing events for all thresholds and nearly all neighbourhood areas. With a higher frequency of forecasted icing, a higher false-alarm ratio cannot be ruled out, but is not possible to quantify due to the lack of no-icing observations. The increased liquid water content in ICE-T shows a better match with the retrieved satellite observations, yet the values are still greatly underestimated at lower levels. Future studies should investigate this issue further, as liquid water content also has implications for downstream processes such as the cloud radiative effect, latent heat release, and precipitation.

An Unsteady Model for Aircraft Icing Based on Tightly-Coupled Method and Phase-Field Method

An unsteady tightly-coupled icing model is established in this paper to solve the numerical simulation problem of unsteady aircraft icing. The multi-media fluid of air and droplets is regarded as a single medium fluid with variable material properties. Taking the droplet concentration as the phase parameter and the droplet resistance coefficient as the interphase force, the mass concentration distribution of the droplet is obtained by solving the Cahn–Hilliard equation. Fick’s law is introduced to improve the Cahn–Hilliard equation to predict the droplet shadow zone. On this basis, the procedure of the unsteady numerical simulation method for aircraft icing is established, including grid generation, the dual-time-step method to realize the unsteady calculation of the air and droplet tightly-coupled mixed flow field, and the improved shallow water icing model. Finally, through the comparative analysis of numerical examples, the effectiveness of the new model in predicting the droplet impact characteristics and the droplet shadow zone are verified. Compared with other icing models, the ice shapes predicted by the unsteady tightly-coupled model were found to be the most consistent with the experiments. In the icing comparison conditions in this manuscript, the prediction accuracy of the ice thickness at the stagnation point of the leading edge was up to 35% higher than that of LEWICE.

Application of various ice accretion simulation approaches in the LOGOS software package

This paper presents results of the ice accretion simulations by the techniques implemented in the LOGOS-Aero module of the LOGOS software package. The results of the Eulerian and the Lagrangian ice accretion simulations are reported for NACA verification problems, which are used to test the software package Lewice. The approaches implemented in the LOGOS-Aero enable simulations of the aircraft icing conditions and the predictions of the shapes and locations of ice deposits on computational models.

Measurements and modelling of the residual mass upon impact of supercooled liquid drops

The mass of liquid remaining on a substrate following a drop impact is a crucial quantity for modelling of numerous phenomena, e.g. spray cooling, spray coating or aircraft icing. In the present study, a method to measure this residual mass after impact of liquid drops is introduced. This method is also applicable to supercooled drops, which may freeze upon impact on cold surfaces. Using the data obtained from extensive measurements in which the size, impact speed and temperature of the drops was varied, a modelling of the residual mass is formulated, following closely the theory of Riboux and Gordillo (Phys Rev Lett 113(2):024507, 2014. 10.1103/PhysRevLett.113.024507). A key adaptation of this model accounts for the deformation of drops immediately prior to impact. This modified theoretical model results in very good agreement with experiments, allowing prediction of residual mass for a given impact situation. Graphical abstract