In January 2017, a business jet flew in Norway on a short repositioning flight with two pilots onboard, no passengers or cargo. Initially, the take-off proceeded as normal but as the landing gear was retracted both pilots observed that the airspeed was rapidly approaching the flap limiting speed of 200kts. When the flaps were fully retracted at a height of approximately 2,100ft above ground level, the crew experienced a violent nose-down pitch motion. Control was regained at a height of approximately 170ft above ground level and, following the accident, data from the flight data recorder showed that the aircraft experienced –2.62G during the pitch upset. A tailplane stall due to icing was suspected; however, the flight data recorder, being limited to 36 parameters, was not able to confirm this. For expediency during the accident investigation process, a simplified, linear flight dynamics model was developed using Matlab/Simulink to assess static and dynamic stability for a range of tailplane efficiency factors to simulate the effects of tailplane icing.

A distributed UAV (unmanned aerial vehicle) flocking control method based on vision geometry is proposed, in which only monocular RGB (red, green, blue) images are used to estimate the relative positions and velocities between drones. It does not rely on special visual markers and external infrastructure, nor does it require inter-UAV communication or prior knowledge of UAV size. This method combines the advantages of deep learning and classical geometry. It adopts a deep optical flow network to estimate dense matching points between two consecutive images, uses segmentation technology to classify these matching points into background and specific UAV, and then maps the classified matching points to Euclidean space based on the depth map information. In 3D matching points, also known as 3D feature point pairs, each of their classifications is used to estimate the rotation matrix, translation vector, velocity of the corresponding UAV, as well as the relative position between drones, based on RANSAC and least squares method. On this basis, a flocking control model is constructed. Experimental results in the Microsoft Airsim simulation environment show that in all evaluation metrics, our method achieves almost the same performance as the UAV flocking algorithm based on ground truth cluster state.

Although a coaxial compound helicopter can takeoff without propeller in the normal condition, the distance should be as short as possible for obstacle avoidance when the vehicle operates in a confined area with heavy loads. Therefore, a suitable propeller control is required to improve the takeoff performance while the total power consumption is no more than the available power. The path is predicted by applying trajectory optimisation. Several varying takeoff parameters, including attitude, liftoff speed and obstacle height, are considered for optimum global performance. Three path indicators are proposed. Apart from typical distance and pilot workload, path sensitivity is quantified based on deviation from takeoff parameter variation. Results indicated that low propeller thrust at hover and moderate allocation on the propeller through flight is recommended. The aircraft achieves significantly improved takeoff performance compared to flight with pure rotors while maintaining the maximum takeoff weight. The distance is shortened by 12.6%, and the longitudinal pilot workload is alleviated by 9.8% and 7.3% from mean and maximum power frequency aspects. Besides, the path is less sensitive to takeoff parameter variations, such as speed, altitude and height.

The advancement of technology on the modern commercial flight deck has allowed flight crew members to utilise multiple sources of information to maintain the safety of their flight. Having multiple sources of flight deck information, capable of displaying the same type of information, can lead to a situation in which a pilot encounters conflicting information. Understanding how a pilot makes a decision when faced with an information conflict on the flight deck is important to ensure appropriate design of flight-deck information systems and effective pilot training. This effort utilised data collected from 25 airline pilots who experienced information conflicts on a simulated B-737 flight deck, in conjunction with a theoretical review of how information conflicts impact decision making, to develop a theoretical model of pilot decision-making in the presence of an information conflict. This manuscript describes the model, along with the theory-driven and data-driven approaches utilised to develop the model.

The accuracy of several numerical schemes for solving the lifting-line equation is investigated. Circulation is represented on discrete elements using polynomials of varying degree, and a novel scheme is introduced based on a discontinuous representation that permits arbitrary polynomial degrees to be used. Satisfying the Helmholtz theorems at inter-element boundaries penalises the discontinuities in the circulation distribution, which helps ensure the solution converges towards the correct, continuous behaviour as the number of elements increases. It is found that the singular vorticity at the wing tips drives the leading-order error of the solution. With constant panel widths, numerical schemes exhibit suboptimal accuracy irrespective of the basis degree; however, driving the width of the tip panel to zero at a rate faster than the domain average enables improved accuracy to be recovered for the quadratic-strength elements. In all cases considered, higher-order circulation elements exhibit higher accuracy than their lower-order counterparts for the same total degrees of freedom in the solution. It is also found that the discontinuous quadratic elements are more accurate than their continuous counterparts while also being more flexible for geometric representation.

This study presents a mathematical model that schedules arrival aircraft regarding RECAT-EU that is new categorisation for applying separation minima and analyses its effect on the performance of the Point Merge System (PMS) at Sabiha Gökcen International Airport (LTFJ). There are two main scenarios: one of them uses RECAT-EU and the other employs the ICAO wake turbulence category. Both scenarios have ten different test problems to examine the mathematical model. The model applies RECAT-EU wake turbulence categories and compares the outcome with the ICAO wake turbulence categories. The model aims to minimise flight duration on the sequencing leg and ground delay in the departure queue using the RECAT-EU and ICAO wake turbulence categories individually. The results were analysed to reveal the PMS performance using the two different approaches to turbulence categories. Statistical analysis was also carried out to compare the means of the two groups in the model.

Whirl flutter is an aeroelastic instability that affects aircraft with propellers/rotors. With their long and flexible rotor blades, tiltrotor aircraft are particularly susceptible. Whirl flutter is known to have destroyed aircraft and in the best case it constitutes a fatigue hazard. The complexity of whirl flutter analysis increases significantly with the addition of nonlinearities, due to the more complex dynamical behaviours that emerge as a result. Most whirl flutter stability analyses in current literature are grounded in linear theory, preventing the full discovery of the nonlinearities’ effects. Continuation and bifurcation methods (CBM) may instead be used to fully appreciate and analyse the effects of the presence of nonlinearities. Previous CBM-based work on nonlinear gimballed hub rotor-nacelle models, representing those found on tiltrotor aircraft, are capable of whirl flutter in parametric regions declared safe by linear analysis. Furthermore, it was found that they are capable of complex behaviours including limit cycle oscillations, quasi-periodic behaviour and even chaos, though the whirl flutter implications of such behaviours has not been explored. This paper investigates the impact of a smooth structural nonlinearity on the whirl flutter stability of a basic gimballed rotor-nacelle model, compared to its baseline linear stiffness version. A 9-DoF model with quasi-steady aerodynamics, a flexible wing and blades that can move both cyclically and collectively in both flapping and lead-lag motions, producing gimbal flap-like behaviour, was adopted from existing literature. A smooth stiffness nonlinearity was introduced in the blade flapping stiffness and CBM was used to find the new whirl flutter behaviours created by the presence of the nonlinearity. Time simulations, Poincaré sections and spectral analysis were then used to investigate the various behaviours found. This in turn allowed recommendations to be made concerning preferable and/or hazardous parameter combinations of use to the tiltrotor designer.

There are many factors causing the shimmy of the aircraft landing gear and structural clearance of landing gear is a typical factor. Some aircraft in service or operation did not shimmy before, but suddenly appeared after a period of use. To solve the problem of clearance shimmy during the service of a certain aircraft, we established a dynamic model of rotating gear with clearance based on the flexible multi-body dynamics model of landing gear and L-N contact theory. We defined different types of clearance and established a mechanical model of aircraft pendulum vibration considering the clearance of landing gear structure for dynamic simulation, and studied the effects of different clearance types, clearance size of motion pair and different clearance positions on the stability of pendulum. The results show that the axial clearance has little effect on the shimmy performance of landing gear; the radial clearance has a certain effect on the shimmy performance of medium speed running, which slightly improves the shimmy damping required by medium speed running; the rotational clearance affects the shimmy performance of the nose landing gear by affecting the force transmission of structural components. The required shimmy damping coefficient increases at low speed and decreases at high speed. The main reason for the return clearance is that during the return, the shimmy damper does not work, which leads to the decrease of the shimmy damping performance and the increase of the required shimmy damping coefficient in the whole speed range. Meanwhile, the structural clearance will increase the shimmy frequency of the nose landing gear. By analysing the yaw angle of the nose landing gear and the time domain curve of the yaw angle of the yaw damper, we can determine which structure of the landing gear and which type of clearance is the cause of the yaw. Finally, the coupling effect caused by the main structural parameters of the landing gear in “gap shimmy” was analysed according to different mechanical stability distances and strut stiffness of the nose landing gear, providing reference for aircraft anti-shimmy design, nose landing gear fault diagnosis and nose landing gear maintenance support.

In this paper, the identification of a time domain model of a helicopter main rotor lead-lag damper is discussed. Previous studies have shown that lead-lag dampers have a significant contribution to the overall aircraft dynamics, therefore an accurate damper model is essential to predict complex phenomena such as instabilities, limit cycles, etc. Due to the inherently nonlinear dynamics and the complex internal architecture of these components, the model identification can be a challenging task. In this paper, a hybrid physical/machine-learning-based approach has been used to identify a damper model based on experimental test data. The model, called grey box, consists of a combination of a white box, i.e. a physical model described by differential equations, and a black box, i.e. regression numerical model. The white box approximates the core physical behaviour of the damper while the black box improves the overall accuracy by capturing the complex dynamic not included in the white box. The paper shows that, at room temperature, the grey box is able to predict the damper force when either a multi-frequency harmonic or a random input displacement is imposed. The model is validated up to 20Hz and for the entire damper dynamic stroke.

This paper presents the results of the experimental study carried out to address the issues of base heating and smooth separation of the stage of launch vehicles. The pressure at the base of a convergent-divergent circular nozzle, from which Mach 1.8 jet emanates, attached to an annular shroud of larger area is controlled by providing air vents on the shroud. On the shroud, vent holes were made at different azimuthal locations, to entrain the surrounding air mass at a higher pressure, pa, to increase the low-pressure, pb, at the base region, caused by the suction creating large-scale vortices formed owing to the sudden expansion of the jet emerging from the nozzle into the shroud. For different number and size of the vents on the shroud, the base pressure was measured. This measurement was done at five levels of overexpansion of the nozzle in the range from –64% to –58%. It is found that increase in vent area results in increase of base pressure, up to some limiting level of the area. Also, the increase of base pressure for the case of vents closer to the nozzle exit is found to be marginally more than the increase caused by vents at distances away from the nozzle exit. Increase of base pressure can be regarded as an advantage not only from base heating point of view but also from the point of view of deflection of the plume to the shroud wall for uniform melting of the pyro layer bonding the stages of the launch vehicle, leading to a smooth separation of the launch vehicle stages.

Many adaptations of the lifting-line theory have been developed since its conception to aid in preliminary aerodynamic wing design, but they typically fall into two main formulations, named $\alpha $- and $\Gamma $-formulation, which differ in terms of the control points chordwise location and the variable updated during the iterative scheme. This paper assess the advantages and drawbacks of both formulations through the implementation of the respective methods and application of standard verification and validation procedures. Verification showed that the $\Gamma $-method poorly converges for wings with nonstraight quarter-chord lines, while the $\alpha $-method presents adequate convergence rates and uncertainties for all geometries; it also showed that the $\Gamma $-method agrees best with analytic results from the cassic lifting-line theory, indicating that it tends to overpredict wing lift. Validation and comparison to other modern lifting-line methods was done for similar geometries, and not only corroborated the poor converge and lift overprediction of the $\Gamma $-method, but also showed that the $\alpha $-method presented the closest results to experimental data for almost all cases tested, concluding that this formulation is typically superior regardless of the wing geometry. These results indicate that the implemented $\alpha $-method has a greater potential for the extension of the lifting-line theory to more geometrically complex lifting surfaces other than fixed wings with straight quarter-chord lines and wakes constrained to the planform plane.

This paper presents progress towards a transition modelling capability for use in the numerical solution of the Reynolds-averaged Navier-Stokes equations that provides accurate predictions for transonic flows and is thus suitable for use in the design of wings for aircraft flying at transonic speeds. To this end, compressibility corrections are developed and investigated to extend commonly used empirical correlations to transonic flight conditions while retaining their accuracy at low speeds. A compressibility correction for Tollmien-Schlichting instabilities is developed and applied to a smooth local correlation-based transition model and a stationary crossflow instability compressibility correction is included by adding a new crossflow source term function. Two- and three-dimensional transonic transition test cases demonstrate that the Tollmien-Schlichting compressibility correction produces substantially improved agreement with the experimental transition locations, particularly for higher Reynolds number applications where the effects of flow compressibility are expected to be more significant, such as the NASA CRM-NLF wing-body configuration, while the crossflow compressibility correction prevents an inaccurate, upstream transition front. The compressibility corrections and modifications do not significantly affect the numerical behaviour of the model, which provides an efficient alternative to non-local and higher-fidelity approaches, and can be applied to other transport-equation-based transition models with low-speed empirical correlations without affecting their predictive capability in the incompressible regime.

Aerodynamic characterisation from flight testing is an integral subroutine for evaluating a new flight vehicle’s aerodynamic performance, stability and controllability. The estimation of aerodynamic parameters from flight test data has extensively been explored, in the past, using estimation methods such as the equation error method, output error method and filter error method. However, in the current era, non-gradient-based estimation techniques are gaining attention from researchers due to their inherent data-driven optimisation capability to find the global best solution. In this paper, a novel non-gradient-based estimation method is proposed for the aerodynamic characterisation of unmanned aerial vehicles from flight data, which relies on the maximum likelihood method augmented with particle swarm optimisation. Flight data sets of a wing-alone unmanned aerial vehicle are used to demonstrate the capabilities of the proposed method in estimating aerodynamic derivatives. Estimates from the proposed method are corroborated with the wind tunnel test and output error method results. It has been observed that simulated flight vehicle responses using estimated parameters are in good agreement with measured data in most of the manoeuvers considered. Confidence in the estimates of linear and nonlinear aerodynamic parameters is well established with the lower limit of Cramer-Rao bounds, which are minimal. The proposed method also demonstrates good predictability of the quasi-steady stall aerodynamic model by estimating stall characteristic parameters such as aerofoil static stall characteristics parameter, hysteresis time constant and breakpoint. The overall performance of the proposed estimation method is on par with the output error method and is validated with the proof-of-match exercise.

With the aviation industry facing increasing environmental and energy challenges, there has been a growing demand for sustainable aviation fuel (SAF). Previous studies have shown the role of ice accretion, release and blockage in aviation-related incidents and accidents with conventional jet fuel. However, there is no available data that establishes the magnitude of influence new fuel compositions will pose on ice formation and accretion in aircraft fuel systems. A recirculating fuel test rig capable of cooling fuel from ambient to −30°C within 4h was built by Airbus to simulate conditions in an aircraft wing tank and allow characterisation of ice accretion. The key characteristic was the pressure drop across an inline fuel strainer for the different SAF explored but visual analysis of ice accretion on the strainer mesh (filters used in protecting fuel feed pumps) was also performed for individual experimental runs for comparison. Measurements revealed that 100% conventional fuel exhibited a higher propensity to strainer blockage compared to the SAF tested. However, all SAF blends behaved differently as the blending ratio with Jet A-1 fuel had an impact on the pressure differential at different temperatures. Data from this work are essential to establish confidence in the safe operation of future aircraft fuel systems that will potentially be compatible with 100 % SAF.

The prediction and characterisation of the limit cycle oscillation (LCO) behaviour of non-linear aeroelastic systems has become of great interest recently. However, much of this work has concentrated on determining the existence of LCOs. This paper concentrates on LCO stability. By considering the energy present in different limit cycles, and also using the harmonic balance method, it is shown how the stability of limit cycles can be determined. The analysis is then extended to show that limit cycles can be controlled, or even suppressed, by the use of suitable excitation signals. A basic control scheme is developed to achieve this, and is demonstrated on a simple simulated non-linear aeroelastic system.

A multiple-vehicles time-coordination guidance technique based on deep learning is suggested to address the cooperative guiding problem of hypersonic gliding vehicle entry phase. A dual-parameter bank angle profile is used in longitudinal guiding to meet the requirements of time coordination. A vehicle trajectory database is constructed along with a deep neural network (DNN) structure devised to fulfill the error criteria, and a trained network is used to replace the conventional prediction approach. Moreover, an extended Kalman filter is constructed to detect changes in aerodynamic parameters in real time, and the aerodynamic parameters are fed into a DNN. The lateral guiding employs a logic for reversing the sign of bank angle, which is based on the segmented heading angle error corridor. The final simulation results demonstrate that the built DNN is capable of addressing the cooperative guiding requirements. The algorithm is highly accurate in terms of guiding, has a fast response time, and does not need inter-munition communication, and it is capable of solving guidance orders that satisfy flight requirements even when aerodynamic parameter disruptions occur.

An onboard three-dimensional (3D) trajectory generation approach based on the reinforcement learning (RL) algorithm and deep neural network (DNN) is proposed for hypersonic vehicles in glide phase. Multiple trajectory samples are generated offline through the convex optimisation method. The deep learning (DL) is employed to pre-train the DNN for initialising the actor network and accelerating the RL process. Based on the offline deep policy deterministic actor-critic algorithm, a flight target-oriented reward function with path constraints is designed. The actor network is optimised by the end-to-end RL and policy gradients of the critic network until the reward function converges to the maximum. The actor network is considered as the onboard trajectory generator to compute optimal control values online based on the real-time motion states. The simulation results show that the single-step online planning time meets the real-time requirements of onboard trajectory generation. The significant improvement in terminal accuracy of the online trajectory and the better generalisation under biased initial states for hypersonic vehicles in glide phase is observed.

This paper considers the problem of a three-axis flexible satellite attitude stabilisation subject to the vibration of flexible appendages and external environmental disturbances, which affect the rigid body motion. To solve this problem, a disturbance observer is proposed to estimate and thereby reject the flexible appendage vibration. Based on the H∞ and Linear Matrix Inequality (LMI) approach, a controller for spacecraft with flexible appendages is proposed to ensure robustness as well as attitude stability with high precision. Stability analysis of the overall closed-loop system is provided via the Lyapunov method. The simulation results of three-axis flexible spacecraft demonstrate the robustness and effectiveness of the proposed method.