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The main purpose of this paper is to investigate the effects of icing on unmanned aerial vehicles (UAVs) at low Reynolds numbers and to highlight the differences to icing on manned aircraft at high Reynolds numbers. This paper follows existing research on low Reynolds number effects on ice accretion. This study extends the focus to how variations of airspeed and chord length affect the ice accretions, and aerodynamic performance degradation is investigated.

A parametric study with independent variations of airspeed and chord lengths was conducted on a typical UAV airfoil (RG-15) using icing computational fluid dynamic methods. FENSAP-ICE was used to simulate ice shapes and aerodynamic performance penalties. Validation was performed with two experimental ice shapes obtained from a low-speed icing wind tunnel. Three meteorological conditions were chosen to represent the icing typologies of rime, glaze and mixed ice. A parameter study with different chord lengths and airspeeds was then conducted for rime, glaze and mixed icing conditions.

The simulation results showed that the effect of airspeed variation depended on the ice accretion regime. For rime, it led to a minor increase in ice accretion. For mixed and glaze, the impact on ice geometry and penalties was substantially larger. The variation of chord length had a substantial impact on relative ice thicknesses, ice area, ice limits and performance degradation, independent from the icing regime.

The implications of this manuscript are relevant for highlighting the differences between icing on manned and unmanned aircraft. Unmanned aircraft are typically smaller and fly slower than manned aircraft. Although previous research has documented the influence of this on the ice accretions, this paper investigates the effect on aerodynamic performance degradation. The findings in this work show that UAVs are more sensitive to icing conditions compared to larger and faster manned aircraft. By consequence, icing conditions are more severe for UAVs.

Atmospheric in-flight icing is a severe risk for fixed-wing UAVs and significantly limits their operational envelope. As UAVs are typically smaller and operate at lower airspeeds compared to manned aircraft, it is important to understand how the differences in airspeed and size affect ice accretion and aerodynamic performance penalties.

Earlier work has described the effect of Reynolds number variations on the ice accretion characteristics for UAVs. This work is expanding on those findings by investigating the effect of airspeed and chord length on ice accretion shapes separately. In addition, this study also investigates how these parameters affect aerodynamic performance penalties (lift, drag and stall).

The purpose of this paper is to analyse an actual representation of ice accretions, which are important during the certification process.

Ice accretion experiments are conducted in a low-speed subsonic wind tunnel testing facility to evaluate the influence of various ice shapes around the airfoil sections. Ice accumulation changes the shapes of local airfoil sections and thereby affects the aerodynamic performance characteristics of the considered NACA 23012 profile. The ice profiles are impregnated using balsa wood with glace, horn and mixed ice accretion cases for the detailed experimental investigation.

Computational fluid dynamics analysis is done to compute the influence of different ice shapes on the aerodynamic coefficients (C_l and C_d) while ice accretion occurs at the leading edge of the airfoil sections. It is observed that the C_l and C_d modified immediately more than 40% as compared to the clean wing configuration. In the same fashion, the skin friction coefficient also abruptly changes for different ice shapes that have the potential to induce flutter at the critical speed of the airplane. The computational solutions are further validated through wind tunnel experiments and recent literature concerning certification for flight in icing conditions.

The ice accretion study on the aerodynamic surfaces can also be extended for wind turbine blades installed at different cold regions around the globe. Further, the propeller icing influences the entire rotorcraft aerodynamics at low temperature conditions and the findings of this study are strongly connected with such problems.

The aerodynamic characteristics of the baseline airfoil are greatly affected by the ice accretion problem. Although flight through icing condition endures for a short duration, the takeoff path and decision speed are determined based on airplane drag as per federal aviation regulations. Hence, the proposed study is focussed on a cost-effective approach to predict the effect of ice accretion to achieve optimum performance.

The purpose of this paper is to present a new technique based on the combination of wavelet packet transform (WPT) and artificial neural networks (ANNs) for predicting the ice accretion on the surface of an airfoil.

Wavelet packet decomposition is used to reduce the number of input vectors to ANN and to improve the training convergence. An ANN is developed with five variables (velocity, temperature, liquid water content, median volumetric diameter and exposure time) taken as input data and one dependent variable (the decomposed ice shape) given as the output. For the purpose of comparison, three different ANNs, back-propagation network (BP), radial basis function network (RBF) and generalized regression neural network (GRNN), are trained to simulate the wavelet packet coefficients as a function of the in-flight icing conditions.

The predicted ice accretion shapes are compared with the corresponding results from previously published NASA experimentation, LEWICE and the Fourier-expansion-based method. It is found that the BP network has an advantage on predicting the rime ice, and the RBF network is relatively suitable for the glaze ice, while the GRNN can be applied for both without classifying the specimens. Results also show an advantage of WPT in performing the analysis of ice accretion information and the prediction accuracy is improved as well.

The proposed method is open to further improvement and investment due to its small computational resource requirement and efficient performance.

The simulation method combining ANN and WPT outlined here can lay the foundation for further research relating to ice accretion prediction under different ice cloud conditions.

Numerical simulation of icing has become a standard. Once the iced shape is known, however, the analyst needs to update the computational fluid dynamics (CFD) grid. This paper aims to propose a method to update the numerical mesh with ice profiles.

The present paper concerns a novel and fast radial basis functions (RBF) mesh morphing technique to efficiently and accurately perform ice accretion simulations on industrial models in the aviation sector. This method can be linked to CFD analyses to dynamically reproduce the ice growth.

To verify the consistency of the proposed approach, one of the most challenging ice profile selected in the LEWICE manual was replicated and simulated through CFD. To showcase the effectiveness of this technique, predefined ice profiles were automatically applied on two-dimensional (2D) and three-dimensional (3D) cases using both commercial and open-source CFD solvers.

If ice accreted shapes are available, the meshless characteristic of the proposed approach enables its coupling with the CFD solvers currently supported by the RBF4AERO platform including OpenFOAM, SU2 and ANSYS Fluent. The advantages provided by the use of RBF are the high performance and reliability, due to the fast application of mesh smoothing and the accuracy in controlling surface mesh nodes.

As far as authors’ knowledge is concerned, this is the first time in scientific literature that RBF are proposed to handle icing simulations. Due to the meshless characteristic of the RBF mesh morphing, the proposed approach is cross solver and can be used for both 2D and 3D geometries.

The purpose of this paper is to describe a methodology for predicting the effects of glaze ice geometry on airfoil aerodynamic coefficients by using neural network (NN) prediction. Effects of icing on angle of attack stall are also discussed.

The typical glaze ice geometry covers ice horn leading‐edge radius, ice height, and ice horn position on airfoil surface. By using artificial NN technique, several NNs are developed to study the correlations between ice geometry parameters and airfoil aerodynamic coefficients. Effects of ice geometry on airfoil hinge moment coefficient are also obtained to predict the angle of attack stall.

NN prediction is feasible and effective to study the effects of ice geometry on airfoil performance. The ice horn location and height, which have a more evident and serious effect on airfoil performance than ice horn leading‐edge radius, are inversely proportional to the maximum lift coefficient. Ice accretions on the after‐location of the upper surface of the airfoil leading edges have the most critical effects on the airfoil performance degradation. The catastrophe of hinge moment and unstable hinge moment coefficient can be used to predict the stall effectively.

Since the simulation results of NNs are shown to have high coherence with the tunnel test data, it can be further used to predict coefficients at non‐experimental conditions.

The simulation method by using NNs here can lay the foundation of the further research about the airfoil performance in different ice cloud conditions through predicting the relations between the ice cloud conditions and ice geometry.

FLYING, in common with all means of transport, is affected by adverse weather conditions, but the necessity of aeroplanes maintaining flying speed introduces a major difficulty of its own. The older forms of transport are able, in the last resort, to evade their difficulties by coming to a dead stop. An aeroplane must, literally, fly in the face of its difficulties. It must fly blind in clouds and perhaps land in fog. Over and above this, flight under certain meteorological conditions introduces a danger unique to aircraft. Ice may deposit at all leading edges and grow to windward, at critical regions of the relative airflow, in shapes which increase drag and seriously decrease lift. The accumulated ice adds to the weight. Unsymmetrical ice deposits on the airscrew blades cause dangerous engine vibrations which can only be kept in check, if at all, by throttling back at the expense of thrust. Venturis and pressure head orifices become blocked with ice, rendering the instruments they serve useless. External controls may become jammed. In short, many adverse factors to prevent flight may be brought into play simultaneously by the mere fact that particular meteorological conditions have been encountered.

This paper aims to investigate the anti-icing performance of the nanosecond dielectric barrier discharge (NSDBD) plasma actuator.

With the Lagrangian approach and the Messinger model, two different ice shapes known as rime and glaze icing are predicted. The air heating in the boundary layer over a flat plate has been simulated using a phenomenological model of the NSDBD plasma. The NSDBD plasma actuators are planted in the leading edge anti-icing area of NACA0012 airfoil. Combining the unsteady Reynolds-averaged Navier–Stokes equations and the phenomenological model, the flow field around the airfoil is simulated and the effects of the peak voltage, the pulse repetition frequency and the direction arrangement of the NSDBD on anti-icing performance are numerically investigated, respectively.

The agreement between the numerical results and the experimental data indicates that the present method is accurate. The results show that there is hot air covering the anti-icing area. The increase of the peak voltage and pulse frequency improves the anti-icing performance, and the direction arrangement of NSDBD also influences the anti-icing performance.

A numerical strategy is developed combining the icing algorithm with the phenomenological model. The effects of three parameters of NSDBD on anti-icing performance are discussed. The predicted results show that the anti-icing method is effective and may be helpful for the design of the anti-icing system of the unmanned aerial vehicle.

This study aims to couple two codes, one able to perform icing simulations and another one capable to simulate the performance of an electrothermal anti-icing system in an integrated fashion.

The classical tool chain of icing simulation (aerodynamics, water catch and impact, mass and energy surface balance) is coupled to the thermal analysis through the surface substrate and the ice thickness. In the present approach, the ice protection simulation is not decoupled from the ice accretion simulation, but a single computational workflow is considered.

A fast approach to simulate advanced anti-icing systems is found in this study.

This study shows the validation of present procedure against literature data, both experimental and numerical.

This paper aims to reports the further developments of an optical sensing technique, relying on Mie scattered and reflected light, from the ice surface and volume, to determine the ice accretion rate as well as the ice type.

By measuring the optical intensity of the backscattered and reflected light, the paper demonstrates that it is possible to obtain information on the onset of icing as well as determine the thickness and type of ice accreted on the leading edge of a wing in real time.

This work is important in the design and development of optical direct ice detection sensors for aerospace applications.

This work is aimed at showing a new approach to ice detection.

Original concept follow on paper from pervious publication.

This paper aims to propose a method of the safety boundary protection for unmanned aerial vehicles (UAVs) in the icing conditions.

Forty icing conditions were sampled in the continuous maximum icing conditions in the Appendix C of the Federal Aviation Regulation Part 25. Icing numerical simulations were carried out for the 40 samples and the anti-icing thermal load distribution in full evaporation mode were obtained. Based on the obtained anti-icing thermal load distribution, the surrogated model of the anti-icing thermal load distribution was established with proper orthogonal decomposition and Kriging interpolation. The weather research and forecasting (WRF) model was used for meteorological simulations to obtain the icing meteorological conditions in the target area. With the obtained icing conditions and surrogated model, the anti-icing thermal load distribution in the target area and the variation with time can be determined. According to the energy supply of the UAVs, the graded safety boundaries can be obtained.

The surrogated model can predict the effects of five factors, such as temperature, velocity, pressure, median volume diameter (MVD) and liquid water content (LWC), on the anti-icing thermal load quickly and accurately. The simulated results of the WRF mode agree well with the observed results. The method can obtain the graded safety boundaries.

The method has a reference significant for the safety of the UAVs with the limited energy supply in the icing conditions.