In-flight Icing Research Articles

Forecasting In-Flight Icing over Greece: Insights from a Low-Pressure System Case Study

Forecasting in-flight icing conditions is crucial for aviation safety, particularly in regions with variable and complex meteorological configurations, such as Greece. Icing accretion onto the aircraft’s surfaces is influenced by the presence of supercooled water in subfreezing environments. This paper outlines a methodology of forecasting icing conditions, with the development of the Icing Potential Algorithm that takes into consideration the meteorological scenarios related to icing accretion, using state-of-the-art Numerical Weather Prediction model results, and forming a fuzzy logic tree based on different membership functions, applied for the first time over Greece. The synoptic situation of an organized low-pressure system passage, with occlusion, cold and warm fronts, over Greece that creates dynamically significant conditions for icing formation was investigated. The sensitivity of the algorithm was revealed upon the precipitation, cloud type and vertical velocity effects. It was shown that the greatest icing intensity is associated with single-layer ice and multi-layer clouds that are comprised of both ice and supercooled water, while convectivity and storm presence lead to also enhancing the icing formation. A qualitative evaluation of the results with satellite, radar and METAR observations was performed, indicating the general agreement of the method mainly with the ground-based observations.

Parametric investigation of aerodynamic performance degradation due to icing on a symmetrical airfoil

Ice accretion on lifting surfaces induces an aerodynamic penalty in lift and drag on an aircraft. This performance degradation depends on the geometric features, type, and surface characteristics of the accreted ice on the airfoil. In the present work, we propose a set of two-parameter, low-order models to represent some of the typical ice topologies: glaze, rime, and horn. The parametric space is swept for all types of ice to isolate the aerodynamic changes causing performance degradation on a canonical symmetrical airfoil, which is the representative airfoil used by the National Research Council of Canada's platform for ice accretion and coatings tests with ultrasonic readings platform for in-flight icing tests. The three ice topologies show a self-similar trend between the stall angle of attack and the ice thickness, with the horn-type of ice imparting the greatest drag and lift penalty due to strong boundary layer separation. The relative effect of ice roughness plays a secondary role in performance degradation, and in some cases, the roughness causes a thicker and more resilient boundary layer, which can, under very specific icing conditions, enhance the aerodynamic performance.

Analysis method and experimental study of ice accumulation detection signal based on Lamb waves

A quantitative identification method for in-flight icing has the capability to significantly enhance the safety of aircraft operations. Ultrasonic guided waves have the unique advantage of detecting icing in a relatively large area, but quantitative identification of ice layers is a challenge. In this paper, a quantitative identification method of ice accumulation based on ultrasonic guided waves is proposed. Firstly, a simulation model for the wave dynamics of piezoelectric coupling in three dimensions is established to analyze the propagation characteristics of Lamb waves in a structure consisting of an aluminum plate and an ice layer. The wavelet transform method is utilized to extract the Time of Flight (ToF) or Time of Delay (ToD) of S0/B1 mode waves, which serves as a characteristic parameter to precisely determine and assess the level of ice accumulation. Then, an experimental system is developed to evaluate the feasibility of Lamb waves-based icing real-time detection in the presence of spray conditions. Finally, a combination of the Hampel median filter and the moving average filter is developed to analyze ToF/ToD signals. Numerical simulation results reveal a positive correlation between geometric dimensions (length, width, thickness) of the ice layer and ToF/ToD of B1 mode waves, indicating their potential as indicators for quantifying ice accumulation. Experimental results of real-time icing detection indicate that ToF/ToD will reach greater peak values with the growth of the arbitrary-shaped ice layer until saturation to effectively predict the simulation results. This study lays a foundation for the practical application of quantitative icing detection via ultrasonic guided waves.

Environmental Chamber Characterization of an Ice Detection Sensor for Aviation Using Graphene and PEDOT:PSS.

In the context of improving aircraft safety, this work focuses on creating and testing a graphene-based ice detection system in an environmental chamber. This research is driven by the need for more accurate and efficient ice detection methods, which are crucial in mitigating in-flight icing hazards. The methodology employed involves testing flat graphene-based sensors in a controlled environment, simulating a variety of climatic conditions that could be experienced in an aircraft during its entire flight. The environmental chamber enabled precise manipulation of temperature and humidity levels, thereby providing a realistic and comprehensive test bed for sensor performance evaluation. The results were significant, revealing the graphene sensors' heightened sensitivity and rapid response to the subtle changes in environmental conditions, especially the critical phase transition from water to ice. This sensitivity is the key to detecting ice formation at its onset, a critical requirement for aviation safety. The study concludes that graphene-based sensors tested under varied and controlled atmospheric conditions exhibit a remarkable potential to enhance ice detection systems for aircraft. Their lightweight, efficient, and highly responsive nature makes them a superior alternative to traditional ice detection technologies, paving the way for more advanced and reliable aircraft safety solutions.

Operational Aviation Icing Forecast Algorithm for the Korea Meteorological Administration

Abstract In this study, we developed and evaluated the Korean Forecast Icing Potential (K-FIP), an in-flight icing forecast system for the Korea Meteorological Administration (KMA) based on the simplified forecast icing potential (SFIP) algorithm. The SFIP is an algorithm used to postprocess numerical weather prediction (NWP) model forecasts for predicting potential areas of icing based on the fuzzy logic formulations of four membership functions: temperature, relative humidity, vertical velocity, and cloud liquid water content. In this study, we optimized the original version of the SFIP for the global NWP model of the KMA through three important updates using 34 months of pilot reports for icing as follows: using total cloud condensates, reconstructing membership functions, and determining the best weight combination for input variables. The use of all cloud condensates and the reconstruction of these membership functions resulted in a significant improvement in the algorithm compared with the original. The weight combinations for the KMA’s global model were determined based on the performance scores. While several sets of weights performed equally well, this process identified the most effective weight combination for the KMA model, which is referred to as the K-FIP. The K-FIP demonstrated the ability to successfully predict icing over the Korean Peninsula using observations made by research aircraft from the National Institute of Meteorological Sciences of the KMA. Eventually, the K-FIP icing forecasts will provide better forecasts of icing potentials for safe and efficient aviation operations in South Korea. Significance Statement In-flight aircraft icing has posed a threat to safe flights for decades. With advances in computing resources and an improvement in the spatiotemporal resolutions of numerical weather prediction (NWP) models, icing algorithms have been developed using NWP model outputs associated with supercooled liquid water. This study evaluated and optimized the simplified forecast icing potential, an NWP model–based icing algorithm, for the global model of the Korean Meteorological Administration (KMA) using a long-term observational dataset to improve its prediction skills. The improvements shown in this study and the SFIP implemented in the KMA will provide more informative predictions for safe and efficient air travel.

Quantitative monitoring of icing on CFRP laminate with guided wave combining forward modeling and inverse characterization

Aircraft icing is one of the critical factors for flight safety. Timely and accurate monitoring of in-flight ice accretion is essential for flight systems to take immediate and effective action to significantly improve the efficiency of subsequent de-icing processes and ensure flight safety. Since carbon fiber reinforced polymer (CFRP) are now widely used in the aviation industry, the study of ice accretion on the surfaces of CFRP with anisotropic properties is of great importance. In this work, a three-dimensional frequency domain finite element model for icing CFRP laminate is first established, via which the mechanism of mode conversion of ultrasonic guided waves (UGWs) at different ice layer thicknesses is quantitatively analyzed. Then, the time-domain finite element simulation was performed, from which the time–frequency domain spectrogram of the acquired UGW signal is obtained by short-time Fourier transform (STFT). The extracted frequency–time-of-flight (ToF) curve of the signal via STFT shows high agreement with the theoretical results, which confirms the influence of icing on UGW propagation. Finally, numerous experiments with bonded lead zirconate titanate wafers to excite and acquire UGWs are conducted with different ice layer thicknesses and lengths on CFRP. The extracted frequency–ToF curves of UGW signals are used as input to a two-layer feedforward artificial neural network (ANN) to accurately evaluate the length and thickness of the ice layer. The high reliability of this method with ANN is confirmed, which shows the potential of the proposed UGW-based method for quantitative monitoring of icing length and thickness on aircraft CFRP laminate.

Climatology of icing conditions over Colombia based onERA5reanalysis and in situ observations

AbstractThis study shows vertical profiles and spatial distribution of upper‐air icing frequency over the tropical Americas. We estimated the in‐flight icing (IFI) over Colombia using the Current Icing Product‐sonde‐A algorithm over two data sets: (1) vertical soundings of temperature and relative humidity and surface station data taken at 12 Coordinated Universal Time or UTC (07 Local Time or LT) on five sites and (2) ERA5 at 00, 06, 12 and 18 UTC (19, 01, 07 and 13 LT). In either case, icing was defined for IFI values exceeding 0.01. Results show that icing tends to occur between 550 and 300 hPa (4.5 and 8.6 km altitude), with a maximum at 500–550 hPa and monotonically decreasing to zero until reaching 300 hPa. Aeronautic reports were used to evaluate the total column IFI and a layer‐based IFI detection with a probability of detection of 87% and 71%, respectively. The annual cycle of IFI is modulated by the meridional migration of the Intertropical Convergence Zone (ITCZ) with a bimodal distribution with peaks during the rainiest seasons. Spatially, IFI hotspots are found in the Pacific, the Andes Mountains and the Amazonia regions of Colombia; the northern Colombia Caribbean region show lower IFI frequency with a relative maximum collocated over the Sierra Nevada de Santa Marta mountains. The IFI exhibits a strong diurnal cycle with a high between night‐time to early morning and a low around noon.

Numerical simulation of shear driven film instability over heterogeneous surfaces via enhanced lubrication theory

The prediction of the transition between continuous film, ensemble of rivulets and moving droplets is crucial in applications such as in-flight icing on airfoil wings or a number of chemical reactors. Here, lubrication theory is used to numerically investigate the stability of a continuous liquid film, driven by shear, over a heterogeneous surface. The disjoining pressure is used to model surface wettability, while the full implementation of the film curvature allows to investigate contact angles up to 60°. Different heterogeneous surface configurations occurring in real problems are investigated. An extended computational campaign records the transition from continuous film to rivulet regime and, if present, the further transition from rivulet to droplets at different flow conditions. A moving grid approach allows for accurate prediction of instability phenomena at low computational cost. The numerical results are successfully validated with experimental evidence in case of critical flow rate leading to a stable dry patch and compared with literature results involving the inherently multiscale in-flight icing phenomenon, providing useful statistical information, required to transfer the present detailed small-scale information into larger scale CFD computational approaches.

Simulation Study on the Performance of Ultrasonic Pulse-Echo Detector for Ice Thickness Identification

In-flight icing detectors are important for the flight safety of aircraft. Detectors based on ultrasonic pulse-echo can be used for detecting ice thickness. To study the influencing factors of ultrasonic pulse-echo detection performance, a simulation model of elastic wave-piezoelectric coupling was established, which was used to analyze the influence of different types of piezoelectric ceramics, matching layers with different acoustic impedances, and different substrate materials on ultrasonic pulse-echo signals. It was found that when aluminum is used as the substrate material, the ultrasonic echo signal has a higher signal-to-noise ratio. Furthermore, the influence of aluminum substrate materials with different thicknesses on ultrasonic pulse-echo was analyzed. The ice thickness can be identified by measuring the time of flight between the aluminum-ice interface echo and the ice-air interface echo. The results indicate that when the thickness of the aluminum substrate is 25mm, the upper detection limit of ice layer thickness can reach about 10mm. Therefore, the detection upper limit of ice layer thickness can be extended by appropriately increasing the thickness of the aluminum substrate material.

Workflow for predictor–corrector simulations of in-flight ice accretion, with applications on swept wings

Workflow for predictor–corrector simulations of in-flight ice accretion, with applications on swept wings

Investigation on Superhydrophobic and Icephobic Coatings For Anti-icing in Aircraft

In-flight ice accumulation on aircraft surfaces is a major concern from safety point of view. Many techniques have been used for decades but finding a low-cost approach without loss of power has attained more focus in recent years. This paper presents the investigation outcomes of superhydrophobic and iccephobic coatings for the anti-icing application. A specimen of 6061 Aluminum Alloy with PTFE coating is analyzed using the Ansys FENSAP-ICE simulation tool and subsequently was subjected to contact angle test. The PTFE coating shows excellent superhydrophobic nature and can serve the aircraft anti-icing requirements at low cost.

Surface Roughness in RANS Applied to Aircraft Ice Accretion Simulation: A Review

Experimental and numerical fluid dynamics studies highlight a change of flow structure in the presence of surface roughness. The changes involve both wall heat transfer and skin friction, and are mainly restricted to the inner region of the boundary layer. Aircraft in-flight icing is a typical application where rough surfaces play an important role in the airflow structure and the subsequent ice growth. The objective of this work is to investigate how surface roughness is tackled in RANS with wall resolved boundary layers for aeronautics applications, with a focus on ice-induced roughness. The literature review shows that semi-empirical correlations were calibrated on experimental data to model flow changes in the presence of roughness. The correlations for RANS do not explicitly resolve the individual roughness. They principally involve turbulence model modifications to account for changes in the velocity and temperature profiles in the near-wall region. The equivalent sand grain roughness (ESGR) approach emerges as a popular metric to characterize roughness and is employed as a length scale for the RANS model. For in-flight icing, correlations were developed, accounting for both surface geometry and atmospheric conditions. Despite these research efforts, uncertainties are present in some specific conditions, where space and time roughness variations make the simulations difficult to calibrate. Research that addresses this gap could help improve ice accretion predictions.

A rotorcraft in-flight ice detection framework using computational aeroacoustics and Bayesian neural networks

This work develops a novel ice detection framework specifically suitable for rotorcraft using computational aeroacoustics and Bayesian neural networks. In an offline phase of the work, the acoustic signature of glaze and rime ice shapes on an oscillating wing are computed. In addition, the aerodynamic performance indicators corresponding to the ice shapes are also monitored. These performance indicators include the lift, drag, and moment coefficients. A Bayesian neural network is subsequently trained using projected Stein variational gradient descent to create a mapping from the acoustic signature generated by the iced wings to predict their performance indicators along with quantified uncertainty that is highly important for time- and safety-critical decision-making scenarios. While the training is carried out fully offline, usage of the Bayesian neural network to make predictions can be conducted rapidly online allowing for an ice detection system that can be used in real time and in-flight.

Experimental Study on Adhesive Characteristics of Aircraft Dynamic Icing

The adhesive properties of aircraft icing play an important role in guiding the design of protection systems, while the formation environment, freezing process, and measurement methods have a great impact on the mechanical characteristics of ice, leading to significant differences in the available experimental results. Therefore, to improve the proximity between the experimental simulation and the actual process of inflight ice shedding, a generation system for the water cloud environment was built and integrated with a set of rotary measuring mechanisms in this paper, allowing the adhesion strength of impact ice to be measured online. In the present test, the appearance characteristics of ice formed under different conditions were observed and analyzed, with the range of its adhesion strength determined. And the effects of freezing mode, ambient temperature, and wind speed on ice adhesion were further discussed. It can be found that the impact ice has a more irregular shape and less adhesion compared to the static ice, and this difference will grow larger with the drop in ambient temperature. In addition, the adhesion of ice first increases and then decreases with the rising ambient temperature, reaching the maximum value (0.254 MPa) around −12 °C. When the flow velocity in the test section increases, the freezing process of water on the substrate will slow down, leading to greater surface adhesion.

UAV icing: Development of an ice protection system for the propeller of a small UAV

Atmospheric icing, also called in-flight icing, is a common hazard for the operation of uncrewed aerial vehicles (UAVs). With the background of a growing commercial and military market of small and medium-sized drones and the developments in the urban air mobility markets, protecting the propellers of UAVs against icing has become a pivotal technology to unlock the potential of these markets. The propellers and rotors accumulate ice faster than the UAVs’ wings and airframe. This ice accumulation leads to aerodynamic degradation, making the protection of the propeller key for the operation of UAVs in conditions with potential icing. In this work, an electro-thermal ice protection system is developed for a propeller of a small UAV, with a propeller diameter of 53 cm or 21 inch. For the design of the system, the required anti-icing heat fluxes were calculated using icing computational fluid dynamics (CFD) analysis. Carbon fibre-based heating elements were integrated into the structure of the propeller. This propeller was tested in an icing wind tunnel at −5 °C, −10 °C, and −15 °C. The tests were performed with a rotation rate representative for a medium-sized UAV of 4200 rpm. The liquid water content of the wind tunnel was 0.44 g/m3. It prevented the performance penalties from ice accretion at temperatures of −5 °C. At lower temperatures, the propeller IPS could limit the ice accretion on the propeller, thus allowing it to retain its ability to create thrust. The results showed a requirement for a significantly higher heat flux than predicted by the CFD analysis. This work is the first step in developing a mature ice protection system for the propellers and rotors of medium-sized UAVs and to enable all-weather operations.

Prediction of ice accretion and aerodynamic performance analysis of NACA 2412 aerofoil

AbstractAdverse meteorological conditions often contribute to the formation of ice on aircraft wing section, engine nacelle and other parts leading to the loss of lift coefficient and increase in drag coefficient affecting aircraft control and stability. This paper addresses the problem of in-flight icing on an asymmetric aerofoil under three different ambient and cloud conditions. The study involves prediction of the leading-edge ice thickness using a numerical model developed from the mass and energy conservation law and Messinger freezing fraction model at the same Reynolds number. Later on, degradation in the aerodynamic performance of the iced aerofoil was also investigated using the computational fluid dynamics (CFD) technique, taking the flow field around a 2D aerofoil geometry into account. The aerodynamic study indicates that cumulus clouds embedded with stratified clouds contribute to the formation of mixed ice on aerofoil leading edge and causes the worst icing scenario reducing the lift coefficient to 90% and increasing the drag coefficient to 800% for the same ambient conditions.

Multi-physics simulation of 3D in-flight ice-shedding

In-flight ice accretion may possibly jeopardize the safety of fixed- and rotary-wing aircraft. Icing can possibly occur if supercooled water droplets in clouds impinge on the aircraft surfaces and freeze upon impact. It may result in instrument failures and degradation of the aerodynamic performances. A major problem related to ice accretion is the possibility of ice shedding from the main body and impacting other parts of the aircraft or being ingested by the engines. In fixed-wing aircraft, shedding is caused by the action of the aerodynamic forces or the activation of an Ice Protection System. In the present work, a multi-physics framework is presented to simulate ice accretion and shedding from wings and engine nacelles. The aerodynamics is computed using the open-source toolkit SU2 (Economon et al., 2015)[1] . Cloud droplet trajectories are computed using the arbitrary-precision Lagrangian in-house solver PoliDrop. Then, the in-house ice accretion toolkit PoliMIce (Gori et al., 2015) is used to determine the ice layer. An algebraic level-set approach with iterative volume mesh refinement has been developed to extract the ice shape from the iced wing geometry. A FEM structural analysis is performed on the accreted ice shape by means of the open-source code MoFEM (Kaczmarczyk et al., 2014, 2020) [2]. Internal stresses within the ice geometry due to aerodynamic forces are computed. Three-dimensional ice accretion simulations are performed to check the validity of the present approach.

Neural Network and Dynamic Inversion Based Adaptive Control for an HALE-UAV against Icing Effects

In the past few decades, in-flight icing has become a common problem for many missions, potentially leading to a reduction in control effectiveness and flight stability, which would threaten flight safety. One of the most popular methods to address this problem is adaptive control. This paper establishes a dynamic model of an iced high-altitude long-endurance unmanned aerial vehicle (HALE-UAV) with disturbance and measurement noise. Then, by combining multilayer perceptrons (MLP) with a nonlinear dynamic inversion (NDI) controller, we propose an MLP-NDI controller to compensate for online inversion errors and provide a brief proof of control stability. Two experiments were conducted: on one hand, we compared the MLP-NDI controller with other typical controllers; on the other hand, we evaluated its robustness and adaptiveness under different icing conditions. Results indicate that the MLP-NDI controller outperforms other typical controllers with higher tracking accuracy and exhibits strong robustness in the presence of icing errors and measurement noise, which has huge potential to ensure flight safety.

Lagrangian and Eulerian algorithms for water droplets in in-flight ice accretion

A particle tracking framework for the computation of the collection efficiency for in-flight ice accretion is presented. Algorithms for the computation of the collection efficiency are presented for both Lagrangian and Eulerian descriptions of the droplets equations. Strengths and weaknesses of each method are analyzed and possible solutions are described and implemented. For the Lagrangian solver, a method for automatic resolution adaptation is introduced, and a strategy for exploiting parallelism is described. In the Eulerian frame a scheme is presented for the solution of the equations on unstructured 3D grids using a relaxation approach. An hybrid Lagrangian Eulerian approach for the computation of the collection efficiency is also introduced which is relevant for Super-cooled Large Droplet condition. All presented algorithms are thoroughly verified, and a comprehensive validation is performed.

Automatic roughness characterization of simulated ice shapes

During in-flight ice accretion, roughness plays an important role since it heavily influences the convective heat transfer and skin friction coefficients. This paper aims to assess the ability of existing ice accretion simulation tools to compute the growing ice’s roughness. To this purpose, a technique based on Self Organizing Maps is applied to numerical simulations of in-flight ice accretion to characterize the roughness. The numerical ice predictions are performed using a standard approach comprising RANS computations, Lagrangian particle tracking, the solution of the unsteady Stefan problem, and a morphogenetic model. Numerical simulations are performed on selected benchmark cases from the 1st AIAA Ice Prediction Workshop. Validation of roughness computation is performed on synthetic test cases, while ice roughness is compared directly to that extracted from ice scans. The results of simulated ice shapes compare reasonably well with experimental data. Computations can replicate the trend of the experimental mean ice shape and roughness distribution for both rime and glaze cases.