Unstable approaches contribute significantly to accidents during the critical approach and landing phases of flight, many of which could have been prevented by executing a go-around. This review investigates cognitive lockup, a tendency to adhere to task completion despite shifting priorities, and its role in aviation incidents. Specifically, we explore the psychological underpinnings of cognitive lockup, the influence on pilot decision-making and potential mitigation strategies. We examine factors such as task completion bias, framing effects and the perceived cost of task switching, and provide recommendations for training and policy modifications to reduce cognitive lockup. Aviation safety in critical flight phases can be improved through enhanced pilot training, mindfulness techniques, positive policy framing and AI-based alert systems.

This study presents the design and evaluation of an autonomous landing system for rotary-wing unmanned aerial vehicles (UAVs) targeting moving platforms. The proposed system leverages the UAV’s onboard positional data and the moving platform’s position, velocity and orientation information to execute high-precision landings. By incorporating the GPS coordinates provided by the mobile platform, the operational envelope of the landing procedure is significantly extended. A Kalman filter is employed to fuse the platform’s GPS data with the UAV’s inertial orientation measurements, enabling accurate estimation of a dynamic rendezvous point along the platform’s trajectory. This facilitates the generation of an optimised landing trajectory that minimises path length and enhances energy efficiency.

A YOLOv8-based object detection model is integrated into the system to detect the landing pad in real time. The effectiveness of the proposed method is validated through scenario-based simulations designed to evaluate landing performance under variable altitudes, crosswind disturbances and limited visibility due to fog.

Across 30 independent runs, the proposed method reduced total autonomous landing time by 12% (191 ± 2.0 s → 168 ± 1.6 s, p < 0.001), halved the landing phase (22.9 ± 0.7 s → 11.1 ± 0.7 s), shortened the path by ≍152 m (2035 ± 6.8 m → 1883 ± 3.1 m), and lowered battery consumption from 5.0 ± 0.1% to 4.0 ± 0.1%. The system maintained successful landings under variable wind (up to 6 m/s) and fog with a 7 m detection range, achieving sub-meter touchdown accuracy (RMSE ≍ 0.15 m); at a 5 m detection limit, landings failed, indicating a robustness boundary.

Compared to existing literature, the developed system introduces a novel 3D trajectory planning approach involving altitude variations and dynamic target prediction. The framework is modular and compatible with various UAV and ground vehicle platforms, making it suitable for diverse mission profiles in both civilian and defense applications.

The increase in activities related to unmanned aircraft systems and the implementation of this new ecosystem have introduced new hazards, impacting the operational safety of air traffic, particularly near airports, creating risks and disruptions in the flow of aircraft. The establishment of airspace for unmanned traffic management has required the integration of this new airspace with the existing one, bringing the potential for issues from this integration. A method was identified as needed to guide the detection of hazards posed to air traffic control activities and the consequent implementation of required mitigation measures. The aim of this work is to propose a framework for identifying hazards introduced to air traffic control, with a view to ensure the safe transition of this process. The method involved consulting air traffic operational safety specialists via a questionnaire, presenting the hazards highlighted in the literature concerning the integration of new airspace concepts within air traffic control activities. The results, obtained through a Delphi consultation, were analysed based on the most frequently assigned scores (mode) to reflect expert consensus. The results were organised into the proposed framework, establishing a guide to risk management activities aimed at implementing the change. The resulting structure was re-submitted to specialists and validated based on the Delphi method. Contributions to society include a guide for this process and potential future implementations, while the literature gap was addressed by adding knowledge to the scientific process.

Recently, autonomous aerial systems have received unparalleled popularity and applications as varied as they are innovative in the civil domain. The unmanned aerial vehicle (UAV) is now the subject of intensive research in both aeronautical and automotive engineering.

This paper presents a new, robust gain-scheduled adaptive control strategy for a class of UAV with linear parameter varying (LPV) models. The proposed controller synthesis involves a set of pre-tuned linear quadratic regulator (LQR) combined with fractional-order PID controllers supervised with an adaptive switching law. The main innovation in this work is the enhancement of the classical gain-scheduling adaptive control robustness for systems with LPV models by combining a set of robust LQR + fractional-order PID compensators. The stability of the resulting controller is demonstrated and its efficiency is validated using a numerical simulation example on a civilian UAV system airspeed and altitude control to illustrate its practical efficiency and achieved robustness.

In the field of parafoil airdrop path planning, the inherent complexity and time-sensitive nature of mission requirements necessitate rapid path generation through low-order mathematical models that approximate the system’s true dynamics. This study presents a novel sparse identification framework for constructing a parafoil path planning approximate model. Leveraging high-fidelity 9-degree-of-freedom (9 DOF) dynamic simulation data as training inputs, our method identifies simple nonlinear relationships between 3D positional coordinates (for spatial targeting) and yaw angle (for directional control), which are critical path planning parameters. Compared to conventional 4 DOF models, experimental validation using field airdrop data reveals that the proposed sparse model achieves enhanced predictive accuracy while maintaining computational efficiency. Quantitative analysis demonstrates reductions in root mean square error (RMSE) by approximately 12.96% (horizontal position), 54.44% (height) and 37.96% (yaw angle). The efficacy is further confirmed through successful fixed-point homing across diverse initial deployment scenarios, underscoring its potential for parafoil path planning.

This study proposes a geometric solution to the norm differential game design problem in target-attacker-defender (TAD) engagements, addressing key limitations of conventional zero-effort-miss approaches. By leveraging the geometric analogy between guidance-law-generated trajectories and Dubins paths, we reformulate the derivation of zero-effort-miss-based guidance laws as a Nash equilibrium optimisation problem, with optimal strategies determined through reachable set analysis of Dubins path frontier. The resulting model is a non-convex optimisation problem, which prevents the derivation of traditional state-feedback control laws. To overcome this limitation and enable real-time implementation, we develop a custom back propagation neural network, enhanced with a relaxation factor method for output filtering, a Holt linear trend model for outlier compensation and a saturation function for oscillation suppression. Extensive simulations demonstrate that the proposed framework significantly outperforms baseline methods. These results validate the effectiveness and robustness of our approach for high-performance TAD applications.

This paper studies a distributed fixed-time dynamic event-triggered formation control framework for a group of hypersonic gliding vehicles (GHGVs) suffering from internal uncertainties and non-affine properties. The main challenge is strong coupling of non-affine nonlinear dynamic with hypervelocity characteristics and multi-source uncertainties make it difficult to design the control protocol. Firstly, by integrating the distributed consensus control strategy, fractional order control theory and dynamic event-triggered mechanism, a framework of fixed-time formation control for GHGVs system is constructed. Secondly, to mitigate the issue of ‘explosion of complexity’ (EI), a fixed-time command filter (FCF) is proposed and a compensative strategy is formulated to tackle the impact of filtering errors. Thirdly, an additional auxiliary differential equation (ADE) is developed to decouple the control input from the status variable. Several radial base function neural networks (RBFNN) are utilised to handle the unknown internal uncertainties. Furthermore, a unique dynamic event-triggered mechanism (DTEM) is introduced for each follower, facilitating seamless transitions between two distinct dynamic threshold strategies. Analysis based on Lyapunov function illustrates that the output tracking error of followers exponentially converges to a small range within a fixed time, and Zeno behaviour is prevented. Finally, several numerical simulations are presented to demonstrate the practicability and meliority of the suggested approach.

This paper provides a preliminary investigation into the use of a novel passive aircraft flight loads alleviation device called the Superelastic Monostable Spoiler. The work focuses primarily on understanding the behaviour of such a device and the related loads alleviation performance during dynamic gust events. A number of different design parameters are explored, such as the trigger condition and the activation speed. The main aim of the paper is to define the preliminary operational requirements of such a device in order to guide the future detailed design, which is not addressed here. It was found that the Superelastic Monostable Spoiler could potentially provide loads alleviation performance comparable with typical gust loads alleviation technologies currently used in modern civil aviation based on the use of ailerons and spoilers.

The present work investigates the thermochemical non-equilibrium effect in the DLR combustor using a two-temperature model combined with vibration-chemistry coupling model. Two operating conditions with inflow Mach 2 and 6 are selected for study. The simulation results illustrate that translational-vibrational non-equilibrium is related to energy transfer behaviour and the translational-vibrational relaxation time. When kinetic energy and chemical energy are converted into internal energy, there is a significant difference in the degree of conversion to translational and vibrational energy. If the translational-vibrational relaxation time is larger than the flow time, such as the relaxation time of the mainstream aftershock wave is 0.25 s for the condition with inflow Mach 2, and the flow time is 3 × 10−5 s, non-equilibrium will occur. Significant differences exist between the flow fields with Mach 2 and 6. A clear boundary layer separation occurs at Mach 6. Combustion occurs at the shear layer, which is in translational-vibrational equilibrium, and there are varying degrees of non-equilibrium in other locations. The dissociation of N2 and production of NO primarily occur on the strut walls and the upper/lower walls of the combustor. The mass fraction of NO is higher than the value at Mach 2. The combustion performance is influenced by the thermochemical non-equilibrium effect. At the condition of Mach 2, it increases the combustion efficiency by 10% near the injector and 0.27% at outlet relatively. Non-equilibrium inhibits the initial upstream combustion while slightly promoting downstream combustion under inflow Mach 6 condition.

Standard quadrotors exhibit limited mobility due to inherent underactuation: they only have four independent control inputs, whereas their position and attitude in space are defined by six degrees of freedom (DOF). Consequently, a quadrotor’s pose cannot track an arbitrary trajectory over time. To address this limitation, a novel actuation concept has been proposed, wherein the quadrotor’s propellers can tilt around their axes relative to the main body–forming a vector quadrotor. To achieve more accurate trajectory tracking tailored to the specific characteristics of this vector quadrotor model, we propose a novel control strategy. First, we integrate special orthogonal group SO(3) theory with model compensation control: SO(3) theory enables accurate modeling of the aircraft’s rotational dynamics, while model compensation control mitigates unmodeled dynamics and external disturbances, thereby ensuring robustness across diverse operating conditions. Second, we introduce the sequential quadratic programming (SQP) method for control allocation; this method not only enables efficient computation of control inputs but also optimises the allocation of control resources, which enhances system performance–particularly in complex manoeuvering scenarios. Finally, we integrate the SO(3)-based controller with the SQP-based control allocation module to form a unified control system. The effectiveness of this proposed approach is validated via simulation results. These results demonstrate improved trajectory tracking accuracy and enhanced robustness against disturbances, thus confirming the potential of our method for practical applications.

This review examines the critical role of meteorological data in optimising flight trajectories and enhancing operational efficiency in aviation. Weather conditions directly influence fuel consumption, delays and safety, making their integration into flight planning increasingly vital. Understanding these dynamics becomes essential for risk mitigation as climate change drives more frequent and severe weather events. Synthesising insights from 57 studies published between 2001 and 2024, this article highlights key variables – such as wind, temperature and convective weather – significantly impacting flight operations. A framework is proposed to improve air traffic management’s safety, efficiency and cost-effectiveness. The findings emphasise the need for systematically incorporating meteorological inputs into trajectory optimisation models, such as wind shear, convective storms and temperature gradients. This integration improves operational predictability and safety while advancing sustainability goals by reducing fuel consumption and CO2 emissions – an increasingly important priority amid rising climate variability and global air traffic demand.

The role of pylon-induced vortex structures on flame stabilisation within a supersonic pylon-cavity flameholder is numerically investigated. The study examines how the fuel jet interacts with the vortices produced by three distinct pylon-cavity flameholder geometries labelled as P0, P1 and P2. P0 represents the pyramidal-shaped baseline pylon configuration, whereas P1 and P2 consist of parallel and slanted grooves on the pylon slant surfaces with respect to the supersonic crossflow for the generation of instream vortices. The selection criteria for P1 and P2 are based on reduced effective blockage area compared with P0. The inlet flow Mach number used for the investigation is 2.2. A sonic ${{\rm{H}}_2}$ fuel injection at 2.5 bar and 250 K is used for all the test cases. Steady RANS reactive flow simulations are used for the assessments. An 18-step Jachimowski chemical kinetic scheme is used to model ${{\rm{H}}_2}$-air reaction mechanism. The flowfield structures within the pylon-cavity flameholder are categorised into two, (i) pylon-cavity geometry-induced vortex structures (II, III, and IV) and (ii) fuel jet vortex pairs (FJVP and SFJVP). The study shows that the interaction between these two decides the reactant mixture formation within the flameholder and the flame stabilisation. This study identifies four different flame-holding locations – L1, L2, L3, and L4 – and their strength depends on the pylon configuration. Overall the P2 configuration is found to perform better than the others in terms of high heat release magnitude and flame spread within the combustor.

Cellular structures provide lightweight, high-strength and excellent structural stability due to their repetitive modular unit design. By integrating cutting and folding Kirigami techniques with composite and plastic substrates, cellular configurations can significantly enhance the aero-mechanical performance of wing designs. This innovative structural technology shows great promise for unmanned aerial vehicles (UAVs), enabling flexible control and dynamic flight capabilities to meet varying operational conditions. This study presents an analysis and optimisation of the aeroelastic behaviour of cellular Kirigami wingbox (CKW) structures for multifunctional operations of micro-UAV wings to ensure stability and resilience in various dynamic flight conditions. The effect of thickness and internal cell angle of the cellular structure on static and dynamic aeroelastic behaviour is assessed through finite element analysis. By incorporating Bayesian optimisation, the multi-disciplinary design space of the cellular UAV wings has been efficiently explored to achieve optimal structural performance for adaptive UAV wings. The results show that Bayesian optimisation effectively identifies optimal design parameters for different multi-objective design weights, which improves the aeroelastic performance of the CKW structure.

Bio-inspiration can be used to improve the aerodynamic performance of commercial multirotor propellers. In the present study, insect wings are used as a source of inspiration, and the effects of inspiration from insect’s wing shape on the propeller performance–, especially this effect on parameters like thrust, torque, and propeller efficiency, are investigated. Six insect species have been selected as inspiration: Hemiptera, Orthoptera, Neuroptera, Mantodea, Odonata and Hymenoptera. The analyses have been done using the numerical simulation of flow and the moving reference frame (MRF) method alongside the SST k-ω turbulence model. The simulations were carried out over a range of rotational speeds, varying from 4,000 to 8,000 rpm, for propellers with a diameter of 0.24 m. All propellers utilised the Eppler E63 airfoil. To ensure the accuracy of the present numerical simulation results, validation was done by comparing them with experimental data from the DJI Phantom-3 propeller. The results of validation showed significant agreement with the experimental data. The results indicated that the insect-inspired propellers generate higher thrust compared to conventional propellers. Additionally, for a constant thrust force, the inspired propellers exhibit lower rotational speeds. Moreover, in terms of thrust, the Hemiptera insect-inspired propeller outperforms the DJI Phantom-3 propeller, achieving a notable average improvement of 34.182%.

This paper presents a study in which modelling and simulation have been used to assess the effect of the aircraft lifts on the air flow over the flight deck of the Queen Elizabeth Class (QEC) aircraft carriers and the subsequent impact on helicopter operations. The aircraft lifts can be either raised or lowered, and they can also have aircraft on them. They can therefore significantly alter the geometry of the starboard side of the ship and, potentially, the air flow over the flight deck. The air flow over the flight deck of the QEC was investigated using experimental and Computational Fluid Dynamics (CFD) techniques. To assess how the air flows for the different lift configurations affected a helicopter landing on the flight deck, piloted flight simulation trials were performed in which a test pilot conducted helicopter deck landings in CFD-simulated Green 60 winds with speeds from 10 kt to 40 kt. Pilot assessment showed the operational wind speed limits, across all spots and lift configurations, were 30 kt or 35 kt and that the different lift configurations produced a 5 kt change in the maximum tolerable wind speeds. While the distribution of the workload experienced by the pilot along the flight path was different for the three lift configurations, it was judged that the difficulty of the overall landing task was not sufficiently affected to require different limiting wind speeds for the different lift configurations.

This paper presents a detailed robustness analysis of three nonlinear filtering algorithms: the unscented Kalman filter, the cubature Kalman filter, and the ensemble Kalman filter, applied to aircraft state estimation for fixed-wing flight dynamics. The study focuses on estimating critical longitudinal flight parameters such as true airspeed, angle-of-attack, pitch angle and pitch rate using pitch angle measurements. A nonlinear aircraft model is formulated, and each filtering technique is implemented and evaluated under multiple scenarios, including sensor noise, initial state mismatches and plant-model uncertainties. Simulation results across four cases, ranging from ideal conditions to $95{\mathrm{\% }}$ mismatch, demonstrate that the unscented Kalman filter consistently delivers the most accurate and robust estimates, especially for velocity and pitch rate. The cubature Kalman filter offers a trade-off between estimation accuracy and computational efficiency, while the ensemble Kalman filter shows significant sensitivity to uncertainties but performs relatively better in estimating the angle-of-attack under severe mismatch conditions. This comparative study provides valuable insights for selecting appropriate filtering strategies in aerospace applications, particularly where robustness and reliability under uncertainty are crucial.

Blade ice accumulation is a serious problem that changes turbine aerodynamics and dynamics, leading to lower power output and higher structural loading. Different from the literature, this paper investigates the performance effectiveness of baseline wind turbine controllers: the generator torque and collective blade pitch controllers against rotor blade ice accumulation. The NREL 5-MW turbine is utilised, and simulations of baseline controllers are conducted with the MS (Mustafa Sahin) Bladed Model for clean and iced blade cases. The performance of the controllers is examined in below (Region 2) and above (Region 3) rated regions under 1 m/s step rising wind speeds. Results are presented through various parameters, including turbine controllers’ gain(s), blade pitch angle, rotor speed, power, etc. Rotor speed response is used to evaluate the controllers’ performance. Even slight blade ice accumulation is estimated to affect turbine efficiency and characteristics, decreasing ${C_{pmax}}$ by 13.27%, slightly varying optimum blade pitch angle and tip speed ratio, altering the control input gain by up to 14.68%. Blade ice accumulation is observed to adversely affect baseline controllers’ performance. In Region 2, the torque controller exhibits reduced transient and steady-state performance, with rotor speed reaching the steady-state approximately 2 s later and showing a steady-state error of 1.86%. In Region 3, the pitch controller’s transient performance deteriorates at low wind speeds, particularly near the rated wind speed, leading to an increased decay time of up to 5.2 s. However, beyond 16 m/s, pitch controller performance gradually recovers, becoming nearly identical to the clean blade case at 21 m/s, while the controller steady-state performance remains unaffected.

The effect of the bio-inspired leading-edge modifications on the aerodynamic performance of non-slender delta wing models was investigated in a low-speed wind tunnel using force and surface pressure measurements. The measurements were performed at a Reynolds number of $Re = 1 \times {10^5}$ over an angle-of-attack range from $ - 4^\circ $ to $30^\circ $. Seven different sharp-edged delta wing models with a 45-degree sweep angle (${\rm{\varLambda }}$), including a base wing, were used to study the effect of sinusoidal and saw-tooth leading-edge modifications. Sinusoidal leading-edge wing designs were inspired by the leading-edge tubercles of the humpback whale’s pectoral fins. The results indicate that the bio-inspired wing modifications resulted in a delay in the stall angle by 4 degrees, smoother stall characteristics, a higher maximum lift coefficient, and increased post-stall lift. The drag coefficient of the modified wings was observed as higher than that of the base wing model. Regarding the longitudinal static stability, leading-edge modifications decreased the stability of the wing as the angle-of-attack surpassed $\alpha = 17^\circ $.

The Monte Carlo methods are frequently employed to evaluate the overall characteristics of non-monotonic, non-linear, non-superpositional performance functions. However, the multi-parameter, multi-objective spacecraft separation dynamics model is not amenable to decoupling to produce a result. This paper presents a parametric objective function that can be sampled. It combines the reliability analysis of the complex non-linear spacecraft separation model with Automated Dynamic Analysis of Mechanical Systems (ADAMS) and uses the Monte Carlo method to obtain the separation performance of the spacecraft separation system reliability profile, that is to say, the distribution of separation performance. The performance distribution of the spacecraft separation system was determined and parameters such as spring separation force, spring line of action, module mass and module centre of mass position were found to have a significant effect on the spacecraft separation dynamics by Adaboost machine learning regression.

Electrical contacts are critical components in all connector systems, as they enable the flow of electrical current. However, power contacts are increasingly subjected to various forms of degradation due to the high input power demands of modern electrical circuits. One of the primary causes of damage is the electrical arc, which can lead to erosion and oxidation of contact surfaces, ultimately resulting in electrical insulation failure. In industries such as aerospace, this type of failure can be mission-critical, especially in scenarios where in-orbit repair is not possible. Therefore, the design and choice of contact material must be carefully considered. Based on theoretical studies of arc-related phenomena, we conducted experimental tests focusing on the optimisation of hemispherical contact using samples made from various pure and coated materials. The contact surfaces in these tests were composed of high-conductivity base such as copper (Cu) and aluminum (Al), and were also coated with noble metals such as gold (Au) and silver (Ag). These materials are commonly used in sectors including aerospace, automotive and general industrial applications. To ensure a fair comparison, all contact samples were manipulated and tested under consistent conditions that reflect their real-world operational environments. The resulting arc parameters were identified and analysed through modeling to determine the most suitable contact design and material most capable of withstanding arc-related degradation over the mission duration, thus ensuring longer service life in applications were a continuous monitoring and repair are not feasible. The results show that repetitive exposure to high input power significantly damages contacts surfaces. Furthermore, the use of coated materials effectively extends the lifespan of the electrical contacts. Scanning electron microscope (SEM) and energy-dispersive X-ray spectroscopy (EDX) analyses support these findings, revealing that high-power input increases erosion rates and leaves pronounced marks on the contact surfaces.