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.

The aeroelastic behaviour of a flapped-wing with freeplay and reduced stiffness is highly nonlinear. The optimal control of a nonlinear system is desired to optimise a given structural performance. In this paper, two novelties (a new method to solve state dependent Riccati equation, and inclusion of damage effects on aero-servo-elastic system) are developed to optimally control the nonlinear aeroelastic behaviour of a flapped-wing section including freeplay and reduced stiffness. To design the optimal controller, the State Dependent Riccati Equation (SDRE) is utilised based on a combination of the Hamiltonian matrix and the Schur method. A three degree of freedom (DoF) aeroelastic wing structure with a control surface is mathematically modelled, including freeplay in control surface, cubic nonlinear spring for description of the torsional stiffness and reduced stiffness factor in torsional spring due to damage. The effect of freeplay, reduced stiffness and concentrated nonlinearity in torsional spring are analysed on aeroelastic response. The system response is determined by time marching of the governing equations using a Matlab code. Various simulations results for multiple flow velocities and nonlinear parameters prove the effectiveness of this control method in flutter suppression. It is also shown that the control surface freeplay leads to limit cycle oscillation at speeds less than flutter speed. Furthermore, the simulation results show that the presence of a damage – which reduces the stiffness in torsional spring – leads to an increase in the oscillation amplitudes.

The conceptual design of mission-tailored aircraft is increasingly shifting towards system of systems (SoS) perspectives that account for system interactions using a holistic view. Agent-based modelling and simulation (ABMS) is a common approach for analysing an SoS, but the behaviour of its agents tends to be defined by rigid behaviour trees. The present work aims to evaluate the suitability of a prompt-engineered large language model (LLM) acting as the Incident Commander (IC), replacing the fixed behaviour trees that govern the agents’ decisions. The research contributes by developing a prompting framework for operational guidelines, constraints, and priorities to obtain an LLM commander within a wildfire suppression, SoS capable of replicating human decisions. By enabling agents in a simulation model with decision-making capabilities closer to those expected from humans, the commander’s decisions and potential emergent patterns can be translated into more defined requirements for aircraft conceptual design (ACD) (e.g., endurance, payload, sensors, communications, or turnaround requirements). Results showed that an LLM commander facilitated adaptive and context-aware decisions that can be analysed via decision logs. The results allow designers to derive aircraft requirements for their specific roles from operational outcomes rather than a priori assumptions, linking SoS mission needs and ACD parameters.

To investigate the advantages and disadvantages of two multi-swirl fuel-rich dome configurations, namely the triple-swirler and double-swirler, for a novel high-temperature rise centre-staged combustor, this study employed ANSYS Fluent software. Utilising the Reynolds-averaged Navier-Stokes (RANS) equation as the governing equation, three-dimensional numerical simulations were conducted using the Realisable k-ε turbulence model and non-premixed probability density function (PDF) combustion model to analyse the flow and combustion characteristics of both configurations. A comparative study was then performed to evaluate the performance differences between the two dome configurations under take-off and idle conditions. The results demonstrate that, under both conditions, the fuel-air mixing in the triple-swirler combustor occurs faster and more uniformly. Specifically, during takeoff, the primary zone temperature distribution in the triple-swirler combustor is more uniform, while during idle, the fuel-rich combustion region is more symmetrical. Furthermore, across both conditions, the outlet temperature distribution of the triple-swirler combustor is of superior quality, albeit with equivalent combustion efficiency. Notably, the formation of NOx and soot in the triple-swirler combustor, during takeoff conditions, exceeds that of the double-stage combustor along the flow path, whereas the generation of CO and UHC, during idle conditions, is lower in the former.

Systems are holistic that represent complex structures in which different components interact. Systems thinking plays an important role as a methodology used to solve and analyse these complex problems. This approach emphasises addressing problems holistically rather than simply breaking them down into parts, providing a deeper understanding of identifying and resolving root causes. The article aims to explain the conceptual framework of systems thinking by discussing the basic concepts and principles of systems thinking in detail. In this context, the literature focuses on reaching a common definition of the term ‘systems’ and discusses practical approaches to the use of systems thinking in aircraft design. It also includes analysis of the application of systems thinking through examples of catastrophic accidents resulting from the misunderstanding or mismanagement of complex systems in engineering studies. The change in aircraft design process over the years has been examined, and a new categorisation method is proposed. By integrating systems thinking into the aircraft design process, it examines the advantages it will provide in understanding and optimising the interaction of components, saving time and costs. This study aims to deal with the systems thinking perspective of aircraft design. The importance of the system concept in aviation is emphasised with concrete examples, and its applicability is examined. Thus, a base is formed for its use in aviation.

Flow separation in highly loaded axial compressors remains a major barrier to performance, motivating the search for active flow control strategies. This study investigates air injection to energise low-momentum endwall flow in a tandem stator configuration, representing the first investigation of its kind for tandem vanes. A numerical investigation was conducted, starting with a smooth-casing reference case and progressing to parametric studies of slot geometry (inclination $\alpha $, jet angle $\beta $, radius of curvature ${R_c}$, circumferential width ${w_c}$), relative injection mass flow rate ${\dot m_{inj}}/{\dot m_{stall}}$ and axial location $\zeta $. The results show how each parameter influences efficiency and pressure ratio, yielding design guidelines: shallow $\alpha $, moderate $\beta $ towards the separation zone, relatively large ${R_c}$ and a balanced ${w_c}$–${\dot m_{inj}}/{\dot m_{stall}}$ combination, best captured through the momentum coefficient ${C_u}$ and velocity ratio ${u_{inj}}/{u_\infty }$. Injection near $\zeta \approx 1.2$ (just upstream of separation) proved most effective, and off-design simulations showed larger efficiency gains towards de-throttled conditions, although stall margin was unaffected. Robustness was confirmed through turbulence-model comparisons and injector turbulence variations, which consistently reproduced suppression of suction-side separation. An integrated analysis of aerodynamic losses further showed that injection strategies remain beneficial when loss penalties are considered. The study thus establishes transferable guidelines for injector design in tandem stators, providing a foundation for future optimisation and experimental validation.

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.

As electric vertical takeoff and landing (eVTOL) aircraft technology advances, the focus has shifted towards hybrid electric power systems to overcome battery-specific energy limitations. This study introduces a deterministic hybrid power ratio to develop a series gas turbine hybrid electric propulsion system for a generic quad tiltrotor aircraft. First, the failure modes were categorised into two groups based on the primary power component arrangement, and the risks associated with each other were assessed. Three failure modes were identified in typical eVTOL layouts, i.e. one engine inoperative (OEI), one battery pack inoperative (OBI) and one proprotor inoperative (OPI). In addition, for configurations where a single nacelle contained both the battery and motor, a combined OPI+OBI case was considered, thereby acknowledging interconnected risks and extending the scope to four potential failure modes. The study determined the minimum weight of hybrid power systems using tailored deterministic hybrid power ratios based on five proposed sizing rules. In conclusion, the paper proposes an efficient battery layout for lightweight hybrid power systems and an optimal hybrid power system for the eVTOL aircraft, aligned with current battery technology levels.

The penetration strategy of hypersonic vehicles in hostile environments is a critical factor in determining their effectiveness in completing reconnaissance or strike missions. Reinforcement learning (RL), as an end-to-end method, exhibits inherent advantages in addressing complex problems. However, existing research indicates that to enhance the efficiency of RL-based strategies, further advancements are necessary to reduce training costs and improve generalisation capabilities. This paper introduces a RL-based cooperative guidance law for multi-hypersonic vehicles, incorporating the estimated remaining time-of-flight and the absolute value of the bank angle obtained through a predictor-corrector method. The observation space and reward function are specifically designed to simplify the complex decision-making problem into a single-value decision problem, thereby reducing computational complexity and training costs. The proposed guidance law integrates the observation space, reward function and action space within the reinforcement learning framework to control flight trajectories, flight time and penetration of no-fly zones, ensuring compliance with multiple constraints. Model training and simulation tests conducted under multiple constraints demonstrate that the proposed approach reduces the training iterations required for the reinforcement learning agent and improves decision-making efficiency. Furthermore, simulations under different no-fly zone distributions confirm the proposed guidance approach’s high generalisation ability.

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.

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.

This paper addresses the attitude control challenge of hypersonic morphing vehicles (HMVs) with uncertainties and actuator saturation. The primary contribution of this work lies in achieving a predefined settling time while ensuring robust control performance under morphing effects, actuator saturation and disturbances. Firstly, a control-oriented model is established based on the dynamics of HMVs. Subsequently, a nonsingular multivariable sliding mode manifold, utilising a switching function, is designed to attain predefined-time convergence and prevent singularity issues. A disturbance observer with an adaptive law is developed to precisely and swiftly estimate uncertainties and error states, while a predefined-time anti-saturation compensator is implemented to alleviate actuator saturation. Furthermore, closed-loop stability is guaranteed through rigorous Lyapunov synthesis. Extensive numerical simulations confirm the algorithm’s superiority in terms of control effectiveness.

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.

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.

In this paper, a sliding mode guidance law for impact angle control without violating a seeker’s field-of-view limits is proposed against targets with various motions and unknown acceleration, including stationary, constant-velocity moving and manoeuvring targets. To develop the guidance law, the kinematic conditions for engagement geometry are defined, and the sliding mode control is applied to satisfy the homing constraint and impact angle control. Then, the relation between look angle, the desired line-of-sight angle and desired impact angle is established to guarantee the target in the field of the missile’s view. The stability of the proposed approach is analysed using Lyapunov theory. Furthermore, the look angle is examined to verify the field-of-view constraint, and a capturability analysis is conducted. To evaluate the performance of the proposed law, numerical simulations demonstrate that the proposed approach achieves satisfactory miss distance and impact angle error while adhering to the field-of-view limit.