A conventional 1D beam structural model from numerically obtained cross-sectional data was compared to a 2D/3D finite element (FE) model from geometry and material data for weakly fluid and structure-coupled rotor blade analysis. The commercial structural solver MSC NASTRAN was used to compare the static and dynamic structural properties of both approaches. Model blades with available experimental data were used to verify the employed computational framework. Piezoelectric actuator patches for active control were modelled with FEs, using a thermal analogy method. A framework for direct loads and deformation interpolation between structural and fluid flow solvers was used. This achieved a high-fidelity simulation of the aerodynamic, structural and servo-structural components. Degradation of actuator effectiveness under centrifugal force was demonstrated. Hovering rotor results for beam and FE method (FEM) models are shown, building towards an accurate simulation of periodic and non-periodic flight conditions with 3D piezoelectric structural models in the near future. FEM–CFD coupling will accelerate blade design by additionally considering the structural stresses in the simulation phase and the potential integration of on-blade actuators and sensors.

Slotted blade technology is a passive flow control strategy that can effectively suppress the boundary layer separation within compressors. To reduce the iteration time of the traditional Design-Experiment-Design method, this study innovatively proposes a fast and universal three-dimensional design method for the slotted blade technology, enabling slot modeling completion within 1 s. Furthermore, combined with machine learning (ML), the mapping relationships between eight design parameters and two key aerodynamic performances – compressor design point efficiency ($\eta$DE) and stator total pressure recovery coefficient at the near-stall point ($\sigma ^{*}_{NS}$) – were pioneeringly established. In this study, the prediction performances of six models were compared: one-dimensional convolutional neural network (1D-CNN), random forest (RF), support vector regression (SVR), Gaussian process regression (GPR), multi-layer perceptron (MLP) and long short-term memory network (LSTM). The results indicate that 1D-CNN achieves the highest prediction accuracy: for the $\eta$DE, the mean absolute error (MAE) and coefficient of determination (R2) are 0.041 and 0.987, respectively; for the $\sigma ^{*}_{NS}$, the MAE and R² are 0.479 × 10−3 and 0.955, respectively. Notably, the computational time of the 1D-CNN model is 99.11% less than that of the computational fluid dynamics (CFD). The Shapley Additive exPlanations (SHAP) method was employed to reveal the effects of design parameters on the compressor aerodynamic performance. Notably, the slot outlet axial position (Zout) exerts the most significant influence on the $\eta$DE, while the slot outlet radial position close to the casing (R1_out) has the strongest impact on the $\sigma ^{*}_{NS}$. This study provides theoretical support and valuable references for the intelligent design of slotted blade technology.

This paper demonstrates a method for quantifying the unmitigated mid-air collision (MAC) rate (${\lambda _{{\textrm{MAC}}}}$) between crewed aircraft and uncrewed aircraft (UA) above different congested area operating environments, to support broadening the definition of an atypical air environment (AAE) within the United Kingdom (UK). The underlying principle of this work is that all crewed aircraft should be operating in accordance with UK Standardised European Rules of the Air (SERA), which dictate minimum operating heights over built-up areas, specifically 1,000 ft in the majority of cases, except during take-off and landing. It is unrealistic, however, to assume that this rule is never breached; therefore, we present a method for objectively evaluating the likely encounter rate. We systematically consider the exclusion of runway protection zones (RPZs), aerodrome traffic zones (ATZs) and helicopter landing sites (HLSs) from the operating areas and evaluate the effect on ${\lambda _{{\textrm{MAC}}}}$. Results are presented that apply the methodology to over 33,000 hours worth of air traffic data recorded at three different sites across the UK. It is concluded that the operation of UA overhead congested areas, outside of RPZs and HLSs, likely satisfies an appropriate target level of safety (TLS) to be considered an AAE up to a height of 100 m above ground level (AGL) both inside and outside of controlled airspace.

Landing gear door locking mechanisms are commonly actuated using hydraulic/pneumatic or electromechanical systems. However, due to their complex structures, these systems are prone to failure and are not efficient in terms of weight and cost. This study presents the design, optimisation and experimental evaluation of a novel locking mechanism unprecedented globally driven by shape memory alloy (SMA) elements, specifically developed for hook-type landing gear door locking systems used in unmanned aerial vehicles (UAVs). The unlocking action is achieved via a NiTi-based SMA spring heated through electrical resistance, while automatic locking is ensured by preloaded tension springs. Two-dimensional kinematic analysis was then conducted to determine the pin locations of the mechanism and optimise the stroke, guaranteeing stable locking/unlocking. Subsequently, a 3D model with a minimal number of components was created, and the force requirements were evaluated through dynamic performance analyses. In prototype tests conducted on a 3D-printed model, the austenite and martensitic phase forces of the SMA over a range of extensions were measured, and the activation–recovery times were refined through iterative testing, which enabled stable locking performance. The system demonstrated competitive activation times compared to conventional solutions, re-locked via assisted cooling, and exhibited reliable switching behaviour. The dynamic analysis results of the designed system aligned well with data obtained from physical testing, validating the stability of the design. Overall, the results indicate that SMA-based actuators offer a lighter, more compact and energy-efficient alternative to traditional actuation methods in aerospace applications.

To enhance the aerodynamic performance of hypersonic nozzles, a three-dimensional method of characteristics (3D MOC) is proposed for designing single expansion ramp nozzles (SERN). The flowfield structures and aerodynamic performances of nozzles designed using the 3D and conventional two-dimensional (2D) MOC approaches are compared through three-dimensional numerical simulations. Results indicate that the major geometric differences occur along the circumferential wall. Under typical flight conditions, the nozzle designed by 3D MOC achieves over 0.45% higher axial thrust coefficient and more than 8% higher lift coefficient than the 2D MOC design. Furthermore, based on the 3D MOC, both rectangular nozzle (RN) and circular nozzle (CN) configurations are designed and analysed. The CN exhibits slightly superior aerodynamic performance compared with the RN. By further modifying the upper and lower wall infill surfaces of the RN, three new nozzle variants are obtained. Comparative results show that these geometric infills have a pronounced influence on lift and pitching moment, while the axial thrust coefficient remains nearly constant. Finally, the effect of the tracing radius on the RN and CN configurations is examined. Increasing the tracing radius notably reduces the lift coefficient but has minimal impact on the thrust and pitching moment. These findings highlight the potential of the 3D MOC-based design method to flexibly balance aerodynamic moment and lift in hypersonic nozzle optimisation.

This study presents a bespoke hardware platform for indoor navigation, featuring a quadrotor equipped with an FZ3 card incorporating the AMD (formerly Xilinx) Zynq UltraScale+ ZU3EG MPSoC as the onboard computer. A core component of this platform is a field programmable gate array (FPGA) module specifically designed to efficiently compute Delaunay triangulations, enabling enhanced spatial awareness and real-time surface reconstruction. The onboard computer communicates with the flight controller, inertial measurement unit (IMU), ultra-wideband (UWB) localisation system, stereo camera, light detection and ranging (LiDAR) and ultrasonic sensors via robotic operating system (ROS) 2. The primary objective is to develop a cost-effective, modular unmanned aerial vehicle (UAV) system that can be adapted for a range of indoor navigation applications. The modular design supports different onboard computer platforms and sensor configurations, allowing researchers to easily customise the system for various experiments. By providing a practical framework for precise indoor navigation, this platform addresses the limitations of simulated, simplified laboratory setups, accelerating prototyping and supporting the deployment of UAVs in complex real-world environments. This work explores the UAV’s hardware architecture, the implementation of the Delaunay triangulation core on the FPGA system-on-chip (SoC), the ROS 2-based communication system and includes a detailed mass analysis and power estimation.

The droop-nose leading-edge morphing wing offers promising potential for reducing aerodynamic drag and noise during take-off and landing, thereby helping to lower aircraft fuel consumption and align with greener aviation goals outlined in Flightpath 2050 by the EU and ICAO declarations. Despite technological challenges and current technology readiness levels (TRL), droop-nose leading-edge (DNLE) wings are primarily tested and evaluated in unmanned aerial systems to reduce costs and risks. The literature proposes various optimisation methods for airfoil skin and morphing mechanisms; however, additional research contributions are needed to develop an effective design methodology. High actuator forces required for morphing, the trade-off between skin flexibility and load-bearing capacity, and the difficulty of obtaining smooth and continuous airfoil deformations are still under investigation. The present research introduces an optimisation methodology tailored for DNLE composite laminate skin and morphing mechanism structures. Its application to the UAS-S45 unmanned vehicle is utilised as a case study. Applying this design and optimisation methodology can lead to an 88% reduction in actuator mechanism force for a DNLE optimised for 6° angle-of-attack, considering an airfoil. This approach significantly enhances airfoil shape smoothness across sections and spanwise direction during morphing conditions. The proposed approach reduces the computational effort, as non-linear finite element method (FEM) analyses are not required within the optimisation loop, except at selected verification stages. A mechanism prototype was constructed to validate the FEM analyses and understand the limits of the simulation. Further investigations are required to achieve a morphing shape closer to aerodynamically optimised shapes.

The demand for renewable energy is increasing rapidly due to the need for environmental sustainability and the reduction of energy costs. Solar energy, with its high potential and minimal environmental impact, has become a key energy source, particularly in innovative applications such as unmanned aerial vehicles (UAVs). The integration of solar cells into fixed-wing UAVs enables extended flight durations and enhances operational efficiency, making them a viable solution for long-endurance missions. In this study, the effects on flight performance, energy consumption and battery management of a fixed wing UAV equipped with solar cells are investigated. Two UAV models with the same aerodynamic characteristics, one with solar cells and the other powered only by the battery, are comparatively analysed. Using a simulation model, the effects of solar irradiation, temperature and environmental factors on the energy management of the UAV were evaluated. The findings indicate that the solar-powered UAV has the capability to sustain uninterrupted 24-hour flight by recharging its battery during daylight hours, whereas the battery-only model is restricted to approximately 14 hours of flight time. In the solar-powered model, dynamic altitude management strategies were employed to extend flight duration, utilising excess energy to determine optimal operational scenarios. Furthermore, the integration of solar cells was found to optimise battery consumption, thereby enabling more sustainable flight operations. These results demonstrate that solar-powered fixed-wing UAVs offer significant advantages for long duration missions and present an efficient solution for energy management.

Fluidic propulsion based on bladeless fan technology has shown strong potential to generate sufficient thrust for lightweight commuter aircraft. Bladeless fans work by entraining and directing ambient air, a feature that can be harnessed not only for thrust generation but also to augment lift. This research investigates the integration of bladeless fans over aircraft wings through both two-dimensional and three-dimensional computational simulations, supplemented by wind tunnel experiments. Multiple configurations were examined – varying fan height, spanwise and chordwise placement, orientation and the number of fan units – and compared against the aerodynamic performance of a baseline wing. The results demonstrate that leading-edge fan placement outperforms trailing-edge configurations, particularly in the post-stall regime. For 2D cases, a maximum of 71% lift increment in the post-stall region with 25% increase in the stall angle was observed. Additionally, the bladeless fans effectively reshape the flow field over the wing, increasing lift at the cost of higher drag relative to the baseline. For 2D cases, a 50% increase in zero lift drag was observed; however, 39% reduction was also observed in post-stall region. Among all configurations, the triple-bladeless-fanjet arrangement delivered the best performance, with further gains observed when a positive incidence angle was applied to the fans. An increase of 45% in lift coefficient was observed for triple fan configuration. These computational findings were validated through wind tunnel tests on a propeller-driven aircraft model, where the bladeless fan-equipped version exhibited superior aerodynamic performance compared to the baseline.

Effectively improving flight fuel efficiency and optimising operational management while ensuring environmentally sustainable and safe operations is crucial for the global aviation to achieve a successful sustainability transition. Addressing the imperative shift from conventional air traffic flow management (ATFM) to trajectory-based operation (TBO), this paper proposes a large-scale flight trajectory optimisation framework under TBO. The study integrates influencing factors including meteorological conditions, airspace capacity and aircraft performance. With the assistance of an air traffic operation simulation system, flight characteristic information is extracted to construct the optimisation model. The model addresses a multi-objective optimisation problem, balancing sector excess traffic flow against cruise fuel consumption within a priority-based framework, to generate global flight plans with optimal altitude profile and waypoint overflight times. Experiment in Chinese airspace shows the TBO scenario achieves substantial reductions of 66.0% in excess sector traffic and 7.8% in cruise fuel consumption versus baseline scenario. This provides a methodological framework for airspace resource allocation supporting energy conservation and emission reduction.

This paper develops and compares four distinct constraint-aware and adaptive matheuristic approaches based on tabu search, simulated annealing, bacterial foraging optimisation and multi-ant colony optimisation. By integrating metaheuristic search with a mixed-integer linear programming (MILP) model, a hybrid framework is designed to optimise aircraft departure sequencing with rigorous precision. The core novelty lies in how this integration reconciles the exactness of mathematical programming with the interpretability of metaheuristics. Standard MILP models offer precise solutions but function as opaque ‘black boxes’, while standard metaheuristics operate via understandable moves but often rely on simplified feasibility checks. The proposed solution merges these strengths, employing adaptive metaheuristics to generate candidate sequences using interpretable moves while a restricted MILP acts as a high-fidelity evaluator. Fixing the sequence enables the MILP to focus solely on optimising continuous timings and holds. This ensures that every candidate step is strictly feasible and optimally timed, turning the solution process into a sequence of human-readable queue adjustments backed by the numerical precision of an exact solver. In a calibrated Antalya Airport case study with 40 aircraft, all algorithms attain the MILP optimum or remain within 1% of it, achieving a 29% reduction in hold fuel compared to first-come-first-served (FCFS). In denser 50-aircraft scenarios, the approach maintains high solution quality within feasible time limits, proving that explainability does not require sacrificing computational efficiency.

This paper proposes a hierarchical super-twisting sliding mode control (ST-SMC) scheme incorporating a fixed-time extended state observer (FT-ESO) to address the bipartite time-varying formation control (BTVFC) problem of multiple quadrotors under wind disturbances. First, a coupled six-degree-of-freedom (6-DoF) dynamic model incorporating wind-induced aerodynamic effects is developed. Then, an FT-ESO is designed to estimate wind-induced disturbances. Subsequently, a hierarchical control strategy is designed: a finite-time state observer (FTSO) estimates the desired position and velocity, while an ST-SMC strategy achieves high-precision position tracking. The desired attitude angles are obtained via nonlinear dynamic inversion (NDI), and an additional ST-SMC strategy is adopted to ensure robust attitude tracking. The global finite-time convergence of the closed-loop system is rigorously proven by stability analysis. Finally, 6-DoF simulation results demonstrate the effectiveness and strong disturbance rejection capability of the proposed control framework.