Search results

The purpose of this paper is to maintain safe flight and to improve existing deicing (in‐flight removal of ice) and anti‐icing (prevention of ice accretion) systems under in‐flight icing conditions.Design/methodology/approach – A recent academic research on aircraft icing phenomenon is presented. Several wind tunnel tests of an experimental aircraft provided by NASA are used in the neural network training. Five ice‐affected parameters are chosen in the light of these experiments and researches. An offline artificial neural network is used as an identification technique. The Kalman filter is used to increase the state measurement's accuracy such that neural network training performance gets better. A linear A340 dynamic model is selected in cruise conditions. This linear model is simulated in time varying manner in terms of changing icing parameters in a system dynamic matrix. The obtained data are used in neural network training and testing.Findings – Airframe icing can grow in many ways and many points on aircraft. In this research, wing leading edge ice occurrence is only considered at the same level in both left and right wings. During ice growth other faults or anomalies are ignored.Originality/value – Existing icing sensors can only provide an indication about possible ice presence. They cannot give information of the exact level of ice. However, the efficiency of current control system of changed model decreases. The proposed technique offers a method to find out the model changes under icing conditions.

The purpose of this paper is to advance the multiphysics analysis of helicopter rotors under icing conditions by coupling the iced rotor’s aerodynamics, analyzed by CFD, with the rotor’s structural characteristics, analyzed by CSD.

The current work introduces supercomputer-based computational approaches capable of assessing the impact of ice accretion on the aerodynamics, blade dynamics, vibrations and loading of a rotorcraft. The rigid and elastic motions of the blades are accounted for through a loose coupling of the flow solver to a multibody dynamics solver. The coupling framework allows for comprehensive aeroelastic simulations of iced rotors in hover and in forward flight.

The flow and structural modules were validated on a full helicopter configuration in forward flight using the ROBIN experimental model. The tip structural deflections were in very close agreement with the experimental measurements.

The results of the CFD analyses are limited by the available experimental results they can be compared to. In dry air CFD, three-dimensional (3D) experiments occur first and CFD is then compared to them; in icing, the opposite is true: 3D experiments (if they are ever done, as they are very expensive) chase CFD and sometimes never occur.

This paper presents an outline of how CFD and computational stress dynamics (CSD) analyses can be linked and provides a toolbox for deeper investigation of the complex flows over helicopters operating under difficult in-flight icing conditions.

More and more helicopters are designed to be able to operate in hostile environments such as rescuing and saving lives over the oceans or mountains, conditions under which icing encounters cannot be avoided.

A loosely coupled CFD/CSD framework that accounts for the rotor blades structural response to aerodynamic loading and ice accretion in hover and forward flight has been presented. This versatile and cost-effective framework provides a more accurate estimation of the helicopter rotor performance and its degradation due to icing encounters during the early design stages than traditional CFD tools.

When comparing and contrasting different types of fixed-wing military aircraft on the basis of an energetic efficiency figure-of-merit, unmanned aerial vehicles (UAVs) dedicated to tactical medium-altitude long-endurance (MALE) operations appear to have significant potential when hybrid-electric propulsion and power systems (HEPPS) are implemented. Beginning with a baseline Eulair drone, this paper aims to examine the feasibility of retro-fitting with an Autarkic-Parallel-HEPPS architecture to enhance performance of the original single diesel engine.

In view of the low gravimetric specific energy performance attributes of batteries in the foreseeable future, the best approach was found to be one in which the Parallel-HEPPS architecture has the thermal engine augmented by an organic rankine cycle (ORC). For this study, with the outer mould lines fixed, the goal was to increase endurance without increasing the Eulair drone maximum take-off weight beyond an upper limit of +10%. The intent was to also retain take-off distance and climb performance or, where possible, improve upon these aspects. Therefore, as the focus of the work was on power scheduling, two primary control variables were identified as degree-of-hybridisation for useful power and cut-off altitude during the en route climb phase. Quasi-static methods were used for technical sub-space modelling, and these modules were linked into a constrained optimisation algorithm.

Results showed that an Autarkic-Parallel-HEPPS architecture comprising an ORC thermal energy recovery apparatus and high-end year-2020 battery, the endurance of the considered aircraft could be increased by 11%, i.e. a total of around 28 h, including de-icing system, in-flight recharge and emergency aircraft recovery capabilities. The same aircraft with the de-icing functionality removed resulted in a 20% increase in maximum endurance to 30 h.

Although the adoption of Series/Parallel-HEPPS only solutions do tend to generate questionable improvements in UAV operational performance, combinations of HEPPS with energy recovery machines that use, for example, an ORC, were found to have merit. Furthermore, such architectural solutions could also offer opportunity to facilitate additional functions like de-icing and emergency aircraft recovery during engine failure, which is either not available for UAVs today or prove to be prohibitive in terms of operational performance attributes when implemented using a conventional PPS approach.

This technical paper highlights a new degree of freedom in terms of power scheduling during climbing transversal flight operations. A control parameter of cut-off altitude for all types of HEPPS-based aircraft should be introduced into the technical decision-making/optimisation/analysis scheme and is seen to be a fundamental aspect when conducting trade-studies with respect to degree-of-hybridisation for useful power.

The aim of this paper is to present a Eulerian–Lagrangian model of aircraft ground deicing that avoids the scale’s dispersion problem caused by the great distance between the spray nozzle and the surface to be deiced. Verification is done using the case of a hot particle liquid spray impinging on a horizontal flat plate. The impinged particles flow outwards radially from the impingement zone and form a hot film wall. The computed wall heat distribution is verified. In the end, an inclination spray’s angle study is presented.

The problem is divided into two regions. First, a 3D region is created for the evolution of the Lagrangian particles spray. A second 2D region is provided for the formation of a liquid film. The two regions exchange mass, momentum and energy through an interface. Heat losses are modelled through particles and liquid-film cooling and evaporation, particles splash and heat transfer to a fixed temperature plate.

For a chamber pressure of 1 bar, the predicted spray penetration is within 10 per cent of the experimental results. For this study case, the heat transfer is maximized with an inclination angle of approximately 30° of the spray.

The model presented makes it possible to simulate the impingement and heat transfer of a large-scale liquid spray with a reasonable computational cost. To the best of the authors’ knowledge, this model is a first attempt of the computational fluid dynamics simulation of ground deicing.

The purpose of this work is to develop an in-flight icing risk assessment methodology by quantification of changing flight dynamic characteristics under icing conditions.

This paper develops an approach for the quantitative assessment of flight risk under icing conditions. Using the six degree-of-freedom simulation model, the icing effects model is used to obtain the extreme values of the key parameters relevant to fight safety, allowing calculation of accident probability based on extreme value theory. The risk portion of the flight risk index is designed to account for different levels of flight risk and to provide criteria to allow pilots’ decision-making. Numerical examples are carried out by a series of simulated elevator overshoots of various levels and different distributions of ice accretion to compare the risk index under different icing conditions.

Case results show that the proposed methodology is able to analyze conditions of different severity and distribution of icing and assess quantitatively how these different parameters affect flight safety.

The quantification of flight risk in icing conditions demonstrated here can be applied to provide an objective and intuitive instrument to facilitate decisions by the aircrew or air traffic controller, especially prior to the aircraft entering into areas with adverse meteorological conditions.

Existing flight risk assessments under icing conditions are typically guided by aerodynamic changes, ice accumulation process or the subjective feeling of the pilot. Here, it is proposed to use the probability of flight risk event to measure different icing intensity levels in a quantitative way. This quantitative metric combines the alteration of aerodynamic characteristics, flight dynamic characteristics and limitation of critical parameters, providing a new and comprehensive viewpoint to measure in-flight icing risk. This may be a promising and more reasonable way to assess the risk.

Ice formation constitutes a hazard to aircraft operation both on the ground and in flight. This article deals with the protection of aircraft against ice formation in flight, but does not consider the counter measures which must be taken on the ground in winter conditions. The first part of the paper deals with the atmospheric conditions which give rise to ice accretion on forward facing surfaces and the types of ice which form at various ambient temperatures. A general survey is then made on methods of solving the problem and the weight and power penalties which they entail. Finally some recent developments in the electrical deicing systems arc reviewed.

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 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.

THE National Advisory Committee for Aeronautics is conducting a programme of research intended to reduce the risks now attendant on aeroplane operation during icing conditions. A part of this programme is concerned with the prevention of ice on the windshield. The methods investigated involve the use of: (1) heat from an electric source, (2) heat from the engine exhaust, and (3) an alcohol‐dispensing, rotating wiper‐blade. Inasmuch as the problem of ice prevention exists in several forms, it is anticipated that several different methods may find application on the aeroplane. The obstructions of vision through a windshield may result from ice or snow formations on the exterior surface or from the formation of frost on the interior. The object of the present investigation, therefore, was to determine the extent to which the several methods could preserve vision. Observations were also made to determine the capacity of the rotating wiper‐blade to remove rain from the windshield.