Accurately evaluating the aerodynamic performance of the missile with damaged structures is very important for the subsequent flight control strategy. At present, few researchers have studied the aerodynamic characteristics of damaged supersonic cruise missiles. Based on CFD (computational fluid dynamics) solutions and the dynamic derivative identification method, the differences in static and dynamic characteristics between the damaged and undamaged models are compared. The results indicate that when the extent of damage increases, the change rate of drag coefficient at larger AoA (angle-of-attack) is greater than that at the smaller AoA. On the contrary, the change rate of lift coefficient at larger AoA is smaller than that at smaller AoA. Meanwhile, the absolute value of the static pitch moment decreases, but the absolute value of the roll moment increases. Damage causes a change in the absolute values of the pitch and roll dynamic derivatives, and the dynamic derivatives do not vary monotonically with the increase of AoA. The turning point occurs at about $\alpha$ = 5°. The areas of the hysteresis loops of the pitch-roll coupling moment increase, which makes the dynamic coupling characteristic between the pitch and roll directions increase. Finally, the maximum allowable damage extent of the missile wing that can achieve static trim is obtained and validated by controlling the deflection of the four rudders.

Runway overruns (ROs) are the result of an aircraft rolling beyond the end of a runway, which is one of the accident’s types that most frequently occurs on aviation. The risk of an RO arises from the synergistic effect among its precursors, such as unstable approaches, long touchdowns and inadequate use of deceleration devices. To analyse this complex socio-technical system, the current work proposes a customised functional resonance analysis method, called FRAM-FDM, as traditional techniques of risk and safety assessment do not identify the interactions and couplings between the various functional aspects of the system itself, especially regarding human and organisational components. Basically, FRAM-FDM is the coupling of a traditional FRAM with flight data monitoring (FDM) techniques, used here to quantify the variabilities of the flight crew performance while executing the required activity (i.e. the landing). In this proposal, these variabilities (i.e. the FRAM functions aspects) are aggregated by the addend of a logistic regression, resulting in a model to evaluate the flare operations and the brake application profile effect on the remaining distance to the end of the runway, used as a reference to classify the landing as acceptable or not. The present application of the FRAM-FDM assesses the operational risk of a sample fleet in overrunning the runway during landing, highlighting the brake pedal application profile as the most relevant contributor. The model improves the knowledge about the system behaviour, being useful to direct flight crew training.

This study examines the pursuit-evasion game involving unmanned aerial vehicles (UAVs), with a specific focus on the scenario of N-pursuers-one-escapee. The primary objective is to develop an optimal strategy for the escapee when the pursuers possess superior capabilities. To obtain this objective, we conduct the following study. Firstly, to enhance realism, a non-cooperative differential game model is formulated, incorporating multiple motion characteristics, including aerodynamics, overloading, and imposed constraints. Secondly, the end-value performance index is subsequently converted to an integral one, simplifying the solution process of the Hamilton-Jacobi-Bellman (HJB) equation. An iterative method is utilised to determine the covariates using the Cauchy initial value problem, and its convergence and uniqueness are established. The optimal avoidance strategy is subsequently derived from the covariates. Finally, the superiority of the proposed strategy is validated through simulation experiments and compared to three advanced optimal avoidance strategies. A total of 1,000 anti-jamming simulation experiments are conducted to verify the robustness of the proposed strategy.

The aviation industry’s efforts to reduce carbon emissions have driven the rapid development and scale-up of sustainable aviation fuels (SAFs). SAFs have the potential to significantly reduce CO2 lifecycle emissions by up to 80% in comparison to Jet A and other conventional fossil-derived jet fuels. For multiple logistical and practical reasons, it is preferable to ensure that SAFs are ‘essentially identical’ (also referred to as ‘drop-in SAF’) to conventional jet fuel in terms of their performance, durability and compatibility with existing hardware systems. Because the majority of SAFs are not identical (non-drop-in) to conventional jet fuel, they have not been approved for use in their neat (100%) form. Instead, these non-identical SAFs are named synthetic blend components (SBC) as they are blended with conventional fuels to different extents per ASTM D7566-23a. It should be noted that there are on-going efforts to develop non-drop in SAF specifications to broaden their proliferation and maximise the aviation industries’ ability to reduce CO2 lifecycle emissions. One very important area of focus is the compatibility of SAFs with engine and fuel system seals, specifically understanding the dynamics of elastomeric seals. To address this, a novel approach has been developed to measure seal dynamics in flowing fuel. This technique has been applied to study the dynamic seal behaviour of four industrially relevant elastomer seals commonly employed in aviation fuel systems. The study involved three test fuels: (i) conventional fossil-derived Jet A, neat hydroprocessed esters and fatty acids (HEFA) SAF, and neat alcohol to jet (ATJ) SAF. Notably, both HEFA and ATJ fuels contain 0% aromatics, in contrast to Jet A, which typically contains around 17% aromatics by volume. The novel fuel-elastomer test rig used in this study was designed to simulate a practical scenario in which fuel flows through the inner surface of a pre-loaded static O-ring. The results of these tests demonstrate that the behaviour of different nitrile elastomers is unique to their formulation, and in all cases, the behaviour in HEFA and ATJ SAF differs significantly from that in Jet A. However, new fuel approval tests may only list one type of elastomer for evaluation, for example the ‘Fit-for-Purpose’ test in ASTM D4054-22 Tier 2 lists one specific nitrile. The findings of this study highlight the complexities of fuel-elastomer interactions within nominally identical chemical families and emphasise the potential risks of assessing compatibility based on tests conducted with a single member of a chemical family.

Due to the safety threats caused by icing, the de-icing system is essential in the aviation industry. As an effective method, the electromechanical de-icing system (EDS) is a new ice-protection system based on mechanical vibration principles. For the majority of the current research on system de-icing capability estimation, the effect of impedance-matching is not considered. Impedance matching plays a very important role in improving the performance of the electromechanical system, so we must also consider the impact of impedance matching when designing the EDS. In the present study, a de-icing capability prediction method considering the impact of an impedance-matching device is established based on experimental and numerical methods. The results indicate that the impedance-matching effect has no impact on the mechanical vibration of the structure for the same load power. Meanwhile, impedance-matching devices can significantly improve the power factor and increase the interface shear stress/strain for de-icing. Eight different vibrational modes were tested, and the experimental results showed that the actual interface shear strain after impedance matching is inversely proportional to the de-icing time. The verification experiments were conducted and the accuracy of the proposed prediction method was verified.

In the present work, a folding wing system (FWS) was developed for guided ammunitions, so that the swept-back angle could be adjusted during both gliding and diving phases. Unlike previous designs, the FWS does not have any fixing mechanisms or brake elements, and it provides folding functionality to reduce the drag force during the terminal phase. We conducted mechanism design, manufactured the FWS, performed system identification and designed various controllers including linear quadratic regulator (LQR), linear quadratic integrator (LQI), sliding mode control (SMC) and second-order sliding mode control (SOSMC) to adjust and hold the desired swept-back angles. Then, the performance of the FWS was tested experimentally under two different flight scenarios, with and without aerodynamic loads. While all controllers operated with almost zero steady-state error (SSE) in the absence of aerodynamic loads, the SOSMC was the most effective controller under aerodynamic loads, considering SSE, delay, chattering, and energy consumption.

It is a simple method to identify the hub dynamic loads of rotor by measuring the vibration responses on helicopter fuselage. However, the identification accuracy of the hub dynamic loads is related to the layout or placement of measuring points on the fuselage. The identification will be inaccurate if the layout of measuring points on the fuselage is unreasonable to result in the “ill-conditioned” frequency response function (FRF) matrix measured on the fuselage. In order to avoid the inaccurate identification due to the “ill-conditioned” measured FRF matrix, an accurate method for identifying the hub dynamic loads of rotor by vibration measurement on helicopter fuselage is proposed in this paper. In the proposed method, the reasonable layout of the measuring points on the fuselage for the “well-conditioned” measured FRF matrix can be obtained according to the condition number of the measured FRF matrix on the fuselage, and then the hub dynamic loads of rotor can be accurately identified. The simulation and experiment of the identification of the hub dynamic loads on a dynamically similar frame structure of a helicopter cockpit floor have verified the effectiveness and accuracy of the proposed method.

Sandwich composites are widely used in aerospace materials thanks to their low weight and high strength properties. The purpose of this study is to observe the effects of polyurethane foam filling on honeycomb core structures produced by additive manufacturing in terms of mechanical strength and moisture absorption properties. Within the scope of the study, honeycomb structures were produced by a 3D printer using polylactic acid (PLA) filament. Then, the honeycomb core was filled with polyurethane foam, which is supplied in liquid form. After the core material was given its final form, it was combined with an epoxy and carbon fibre facesheet material using the vacuum infusion technique. After the sandwich composite production was completed, in-plane compression, three-point bending, shear, and moisture absorption tests were applied. The polyurethane foam filling greatly increased the mechanical strength, but slightly more moisture absorption occurred in this structure compared to a hollow honeycomb structure.

There are many deviation sources in the assembly process of aircraft complex thin-walled structures. To get important factors that affect quality, it is crucial to diagnose the key deviation resources. The deviation transfer between deviation sources and assembly parts has the characteristics of small sample size, nonlinearity, and strong coupling, so it is difficult to diagnose the key deviation sources by constructing assembly dimension chains. Therefore, based on the deviation detection data, transfer entropy and complex network theory are introduced. Integrating the depth-first traversal algorithm with degree centrality theory, a key deviation diagnosis method for complex thin-walled structures is proposed based on weighted transfer entropy and complex networks. The application shows that key deviation sources that affect assembly quality can be accurately identified by the key deviation source diagnosis method based on complex networks and weighted transfer entropy.

The camber morphing of an aerofoil in ground effect was investigated using the FishBAC method and Detached Eddy Simulations with the k-omega SST turbulence model at a Reynolds number of 320,000. The aerofoil was periodically morphed at a start location of 25% chord from the leading edge with a trailing edge deflection range of 0.1% to 3% and morphing frequencies between a Strouhal number of 0.45 to 4 at a constant ground clearance of 10%. Periodically morphing the aerofoil using a sinusoidal function showed that lift and drag increased on the downstroke and decreased on the upstroke in the cycle, resulting in periodic values of lift and drag throughout the cycle. The amplitude of lift and drag increased as the morphing frequency and/or trailing edge deflection increased. It was found that the wake characteristics varied as a function of trailing edge deflection and morphing frequency. For small trailing edge deflections below 0.4% and frequencies below a 2.2 Strouhal number, Kelvin Helmholtz shedding was observed, and above this the wake became chaotic. Large trailing edge deflections showed Von-Karman shedding, where the interaction between the lower counter-clockwise vortex and the ground plane resulted in a jet-like flow that caused forward thrust. For the maximum deflection and morphing frequency tested in this study, reversed Von-Karman shedding was observed, which caused forward thrust from the interaction of the two-shedding counter-rotating vortices. Von-Karman or reversed Von-Karman shedding shows positive thrust generation, however, chaotic shedding should be avoided due to large drag gains. Varying the Reynolds number caused the Strouhal number to change as they depend on the same variables. It was found that the Strouhal number variation had a large effect on the wake, however, the Reynolds number had a minimal effect.

The usage areas of rotary or fixed wing unmanned aerial vehicles (UAV) have become very widespread with technological developments. For this reason, UAV designs differ in terms of aerodynamic design, flight performance and endurance depending on the intended use. In this study, maximising of the autonomous flight performance of the unmanned helicopter produced at Erciyes University using an optimisation algorithm is discussed. For this purpose, the input parameters of the dynamic model are chosen as blade length, blade mass density, blade chord width and blade twist angle of the unmanned helicopter and the proportional, integral, derivative gain coefficients of the lateral axis of the autopilot. The output parameters of the dynamic model are selected as settling time, rise time and maximum overshoot, which are autonomous performance parameters. The dynamic model consisting of helicopter and autopilot parameters is integrated into the back-tracking search optimisation (BSO) algorithm as an objective function. In the optimization process, where mean squared error (MSE) is used as the performance criterion, optimum input and output values were determined. Thus, helicopter and autopilot parameters, which are among the factors affecting autonomous performance, are taken into account with equal importance and simultaneously. Simulations show that the obtained values are satisfactory. With this approach based on the optimisation method, complex and time-consuming dynamic model calculations are reduced, time and cost are saved, and practicality is achieved in applications. Therefore, this approach can be an innovative and alternative method to improve UAV designs and increase flight performance compared to classical methods.

This paper studies the aeroelasticity of a stiffened cantilever plate using composite material and novel structural layouts. A comprehensive parametric study is conducted to determine the influence of different design parameters on the aeroelastic boundaries. Design parameters include plate sweep angle, ply orientation, stringer cross-section and stringer sweep angle. Nastran is used to run the aeroelastic analysis, and the process is automated using ${\rm{Matla}}{{\rm{b}}^{}}$. The structure of the plate is modelled using laminate elements whereas the stringers are modelled using the Euler-Bernoulli beam elements. The unsteady aerodynamic loads are modelled using doublet-lattice method (DLM) and the structural and aerodynamic meshes are connected using an infinite plate surface (IPS) spline. A mesh sensitivity analysis is conducted to ensure fine meshes for the aerodynamics and structure. The study’s findings demonstrate the benefits of employing forward swept (Fw) stringers since it increases flutter speed by almost 38% compared to the unswept stringers case and prevents divergence. Moreover, the static aeroelastic analysis illustrates that the utilisation of Fw swept stringers can reduce the average tip displacement and tip twist effectively. T-shaped stringers are recommended to stiffen the plate due to their lower impact on the total mass of the plate. In some configurations, the structural layout has a much higher effect on the aeroelastic instabilities when compared to the material effect (ply orientation). However, results suggest combining both for some cases to get balanced washin and washout effects.

Evaluation of the power required in level flight is essential to any new or modified helicopter performance flight-testing effort. The conventional flight-test method is based on an overly simplification of the induced and profile power components required for a helicopter in level flight. This simplistic approach incorporates several drawbacks that not only make execution of flight sorties inefficient and time consuming, but also compromise the level of accuracy achieved. This paper proposes an alternative flight-test method for evaluating the level-flight performance of a conventional helicopter while addressing and rectifying all identified deficiencies of the conventional method. The proposed method, referred to as the corrected-variables screening using dimensionality reduction (CVSDR), uses an original list of 36 corrected variables derived from basic dimensional analysis principles. This list of 36 corrected variables is reduced using tools of dimensionality reduction to keep only the most effective level-flight predictors. The CVSDR method is demonstrated and tested in this paper using flight-test data from a MBB BO-105 helicopter. It is shown that the CVSDR method predicts the power required for level flight about 21% more accurately than the conventional method while reducing the required flight time by an estimate of at least 60%. Unlike the conventional method, the CVSDR is not bounded by the high-speed approximation associated with the induced power estimation, therefore it is also relevant to the low airspeed regime. This low-airspeed relevancy allows the CVSDR method to bridge between the level-flight regime and the hover. Although demonstrated in this paper for a specific type of helicopter, the CVSDR method is applicable for level-flight performance flight testing of any type of conventional helicopter.

In this work, a three degrees-of-freedom (3-DoF) static quadcopter unmanned aerial vehicle (UAV) test-rig of a pendulum-type configuration is custom-designed, developed, instrumented, and interfaced with a PC. The rig serves as a test bed to develop high-fidelity mathematical models as well as to investigate autopilot designs and real-time closed-loop controllers’ performances. The Simulink Desktop Real-Time software is employed for the quadcopter’s attitude signals acquisition and real-time implementation of closed-loop controllers on a target microcontroller hardware. The mathematical models for pitch, roll, and yaw axes are derived via the first principle and validated with the experimental linear system identification (SI) techniques. Subsequently, employing the multi-parameter root contour technique, the classical proportional integral derivative (PID) controllers are designed and implemented in real-time on the quadcopter UAV test rig. This served as a benchmark controller for comparing it with an integral-based linear quadratic regulator (LQR) controller. Further, to improve the transient response of the LQR controller, a novel robust integral-based LQR controller with a feedforward term (LQR-FF) is implemented, which shows much superior performance than the benchmark and basic LQR controller. This work thus will act as a precursor for a more complex 3-DoF autopilot design of an untethered quadcopter.

Unmanned aerial vehicles (UAVs), which are available in our lives in many areas today, bring with them new expectations and needs along with developing technology. In order to meet these expectations and needs, main subjects such as reducing energy consumption, increasing thrust and endurance, must be taken into account in UAV designs. In this study, Backtracking search optimisation (BSO) algorithm-based adaptive neuro-fuzzy inference system (ANFIS) model is proposed for the first time to improve UAV thrust. For this purpose, first, different batteries and propellers were tested on the thrust measuring device and a data set was obtained. Propeller diameter and pitch, current, voltage and the electronic speed controller (ESC) signal were selected as input, and UAV thrust was selected as output. ANFIS was used to relate input and output parameters that do not have a direct relationship between them. In order to determine the ANFIS parameters at the optimum value, ANFIS was trained with the obtained data set by using BSO algorithm. Then, the objective function based on the optimum ANFIS structure was integrated into BSO algorithm, and the input values that gave the optimum thrust were calculated using BSO algorithm. Simulation results, in which parameters such as engine, battery and propeller affecting the thrust are taken into account equally, emphasise that the proposed method can be used effectively in improving the UAV thrust. This hybrid method, consisting of ANFIS and BSO algorithm, can reduce the cost and time loss in UAV designs and allows many possibilities to be tested.

Air route networks can no longer meet operational efficiency requirements because of the rapid growth of complex traffic flows. Machine learning is employed to investigate the evolutionary mechanism of congestion in such networks in view of their high complexity and high density, and a reasonable network optimisation scheme is presented. First, deviations between nominal and actual routes are investigated with reference to radar track data, and a network reflecting actual route operations is constructed using adversarial neural networks. Second, flight time is used to characterise congestion in route networks. Actual network operations are considered, and congestion is defined from the perspective of road traffic engineering. The effects of the operational properties of traffic flows on flight times are analysed to establish various congestion indicators. A gradient boosting model is used to select indicator characteristics and analyse patterns in the variations of indicator values for each flight segment in distinct periods. The indicator–time relationship is leveraged to explore the evolutionary mechanism of congestion in the route network. Third, on the basis of this mechanism, a multiobjective optimisation model of congestion is formulated, and a particle swarm optimisation algorithm is executed to adjust the route passage structure, thereby solving the optimisation model. Finally, calculation validation is conducted using radar track data from the control sector of the Yunnan region. The average flight time in a route segment is 10% shorter in the optimised route network than in the nonoptimised route network, which confirms that the optimisation solution is practicable.

The deformable wing structure can change its aerodynamic shape according to the change of flight mission and flight environment, so as to obtain better lift-drag, stability and control characteristics, which is considered as one of the future research directions of aviation technology. Considering the current technology maturity and reliability, a gradient corrugated fin is designed to realise the bending deformation of the wing. The structure of the skin is optimised to keep the skin smooth during deformation. In addition, a progressive push and pull rod is proposed to drive the wing deformation, and the fluid-structure interaction simulation is carried out for the wing deformation. At the same time, the changes of wing aerodynamic characteristics under different angles of leading and trailing edges and different push rod action schemes are analysed. Finally, a dry wind tunnel simulation test of the designed progressive flexible variable bending wing is carried out. The results of fluid-structure interaction simulation and dry wind tunnel test show that the progressive flexible variable bending wing proposed in this paper has a simple and reliable structure and remarkable deformation effect. It has advantages in increasing lift and reducing drag, ensuring high lift-drag ratio and providing wing trim moment. The deformable wing dry wind tunnel test platform designed by this method is structurally reliable, easy to operate, and can accurately reflect the influence of wing deformation on its aerodynamic force, which provides a verification means for the development of the design method and the design of practical aircraft in the future.

Hydrogen is a promising energy carrier to decarbonise aviation. However, many challenges regarding its storage or handling still have to be solved to successfully utilise hydrogen in aircraft and at airport infrastructures. The increasing use of hydrogen also generates opportunities for disruptive improvements, like the possibility to integrate metal hydrides (MHs) into the hydrogen powertrain and its infrastructure. Besides their ability to store hydrogen, MHs enable a wide range of potential secondary functions such as high-power thermal applications or compression. This way, MHs may contribute to achieve the goal of sustainable hydrogen-powered aviation. Hence, potential MH application options and their current state-of-the-art are presented. Based on that overview, the following seven use cases for aviation are selected for evaluation: ‘hydrogen emergency storage’, ‘cabin air-conditioning’, ‘thermal management of fuel cells’, ‘gas gap heat switches’, ‘hydrogen boil-off recovery’, ‘onboard hydrogen compression’ and ‘hydrogen safety sensors’. Four of these use cases are investigated to achieve comparable degrees of detail to avoid misevaluations in the subsequent weighted point rating. The results reveal the high potential of MHs for ‘hydrogen boil-off recovery’, ‘hydrogen safety sensors’ and ‘cabin air-conditioning’. For the three most promising use cases, outlooks to their potential future implementation are provided in order to outline the ability of MHs to empower sustainable aviation. These investigations highlight the huge potential of MHs for boil-off treatment.

The minimum flight time of spacecraft rendezvous is one of the fundamental indexes for mission design. This paper proposes a rapid trajectory planning method based on convex optimisation and deep neural network (DNN). The time-optimal trajectory planning problem is reconstructed into a double-layer optimisation framework, with the inner being a convex optimisation problem and the outer being a root-finding problem. The thrust properties corresponding to time-optimal control are analysed theoretically. A DNN-based rapid planning method (DNN-RPM) is put forward to improve computational efficiency, in which the trained DNN provides a high-quality initial guess for Newton’s method. The DNN-RPM is extended to search for the optimal entering angle of natural-motion circumnavigation orbit injection problem and the minimum reconfiguration time of spacecraft swarm. Numerical simulations show that the proposed method can improve the computational efficiency while ensuring the calculation accuracy.

In this paper, we investigate the attitude manoeuver planning and tracking control of the flexible satellite equipped with a coilable mast. Due to its flexible beamlike structure, the coilable mast experiences bending and torsional modal vibrations in multi-direction. The complex nonlinear coupling and other external disturbances significantly impact the achievement of high-precision attitude control. To overcome these challenges, a robust attitude tracking controller is proposed for easy implementation by the Attitude Determination and Control System (ADCS). The controller consists of a disturbance compensator, feedforward controller and output feedback controller. The compensator, based on a Nonlinear Disturbance Observer (NDO), effectively compensates for the cluster disturbances caused by vibrations, environmental factors and parameter perturbations. The feedforward controller tracks the desired path in the nominal satellite model. Furthermore, the output feedback controller enables large-angle manoeuver control of the satellite and evaluates the suppression effect of the controlled output on the observation error of cluster disturbances used the ${L_2}$-gain. Simulation results demonstrate that the proposed controller successfully achieves high-precision attitude tracking control during large-angle manoeuvering.