Liquid hydrogen (LH2) is a promising energy carrier to decrease the climate impact of aviation. However, the inevitable formation of hydrogen boil-off gas (BOG) is a main drawback of LH2. As the venting of BOG reduces the overall efficiency and implies a safety risk at the airport, means for capturing and re-using should be implemented. Metal hydrides (MHs) offer promising approaches for BOG recovery, as they can directly absorb the BOG at ambient pressures and temperatures. Hence, this study elaborates a design concept for such an MH-based BOG recovery system at hydrogen-ready airports. The conceptual design involves the following process steps: identify the requirements, establish a functional structure, determine working principles and combine the working principles to generate a promising solution.

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 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 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.

Airbreathing waveriders often use the fuselage forebody as the pre-compression surface of the inlet, which tends to encounter complex internal-external flow coupling issues. First, the osculating cone method is employed, and a wide-speed-range airbreathing waverider is designed by partitioning it into the waverider forebody, elongated body and waverider aft body, achieving full waverider characteristics. Next, the configuration is optimised to address the internal-external flow coupling issue. The calculations show that the optimised configuration improves the lift-to-drag ratio by more than 20% and the total pressure recovery coefficient by more than 30% in both operating conditions compared to the baseline configuration. Finally, data mining techniques are applied to analyse the data from the optimisation process. It reveals the interdependent relationship between the vehicle’s internal and external flow performance, with the cone shock wave angle and wing extension line length having the most significant impact on aerodynamic performance, thereby generating design knowledge. The content of this paper covers configuration design, optimisation and data mining. The entire process is highly generalisable and can serve as a reference for other aircraft configuration design optimisation tasks. The resulting design knowledge can also provide valuable insights for researchers in future airbreathing waverider designs.

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.

Considering the performance of the standard KF (Kalman filter)degrades significantly when subjected to a hybrid attack, this paper investigates the state estimation problem for a class of stochastic systems under randomly occurring hybrid cyber attacks, which involves denial-of-service (DoS) attack and deception attack obeying unknown Gaussian distribution. First, to consider the DoS attack and deception attack in a unified model, a categorical distributed vector is employed to establish a new measurement model including hybrid cyber attacks. Next, the conjugate prior distributions for the unknown attack parameters are determined, in which the attack probabilities are modeled as Dirichlet distribution, and the deception attack is described by Gaussian-inverse-Wishart distribution. Then, based on variational Bayesian (VB) inference, a RKF (robust Kalman filter) is designed to simultaneously estimate the state and unknown attack parameters. Finally, the estimation performance of the proposed filter is illustrated through a simulation example.

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.

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.

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.

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.

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 $.

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.

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.

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 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 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 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.