This article presents a systematic review on the use of eye-tracking technology to assess the mental workload of unmanned aircraft system (UAS) operators. With the increasing use of unmanned aircraft in military and civilian operations, understanding the mental workload of these operators has become essential for ensuring mission effectiveness and safety. The review covered 26 studies that explored the application of eye-tracking to capture nuances of visual attention and assess cognitive load in real-time. Traditional methods such as self-assessment questionnaires, although useful, showed limitations in terms of accuracy and objectivity, highlighting the need for advanced approaches like eye-tracking. By analysing gaze patterns in simulated environments that reproduce real challenges, it was possible to identify moments of higher mental workload, areas of concentration and sources of distraction. The review also discussed strategies for managing mental workload, including adaptive design of human-machine interfaces. The analysis of the studies revealed a growing relevance and acceptance of eye-tracking as a diagnostic and analytical tool, offering guidelines for the development of interfaces and training that dynamically respond to the cognitive needs of operators. It was concluded that eye-tracking technology can significantly contribute to the optimisation of UAS operations, enhancing both the safety and efficiency of military and civilian missions.

Unmanned aerial vehicle (UAV) formations for bearing-only passive detection are increasingly important in modern military confrontations, and the array of the formation is one of the decisive factors affecting the detection accuracy of the system. How to plan the optimal geometric array in bearing-only detection is a complex nondeterministic polynomial problem, and this paper proposed the distributed stochastic subgradient projection algorithm (DSSPA) with layered constraints to solve this challenge. Firstly, based on the constraints of safe flight altitude and fixed baseline, the UAV formation is layered, and the system model for bearing-only cooperative localisation is constructed and analysed. Then, the calculation formula for geometric dilution of precision (GDOP) in the observation plane is provided, this nonlinear objective function is appropriately simplified to obtain its quadratic form, ensuring that it can be adapted and used efficiently in the system model. Finally, the proposed distributed stochastic subgradient projection algorithm (DSSPA) combines the idea of stochastic gradient descent with the projection method. By performing a projection operation on each feasible solution, it ensures that the updated parameters can satisfy the constraints while efficiently solving the convex optimisation problem of array planning. In addition to theoretical proof, this paper also conducts three simulation experiments of different scales, validating the effectiveness and superiority of the proposed method for bearing-only detection array planning in UAV formations. This research provides essential guidance and technical reference for the deployment of UAV formations and path planning of detection platforms.

A demonstration of a fully onboard method for generating background oriented schlieren (BOS) data on a jet exhaust is presented. Readily available commercial camera equipment is used to capture in-flight imagery of a miniature jet engine exhaust mounted on a custom-built model aircraft. The setup for image acquisition and processing algorithms are described. A new process for registration of images to reduce the degrading effects of vibration and flexure of the airframe are developed and presented along with the underpinning BOS algorithm. Results show that jet flows can be visualised using this technique using a contained system on a single aircraft and demonstrate how a simple technique, such as BOS, can be democratised to such an extent that the cost of conducting in-flight jet measurements can be reduced to the budget of any model aircraft flyer.

The experimental 7AD rotor blade is assessed for flutter stability in hover to identify the influence of aerodynamic contributions related to blade aerofoil, rotor inflow and wake periodicity on flutter onset. For the aeroelastic analyses, the multibody model is tightly coupled with an unsteady aerodynamic model based on Wagner’s function and related enhancements for the general motion of an aerofoil section considering heave and pitch. The mathematical setup of the approximated Wagner function in state space is extended for axial flow to include unsteady effects related to rotor inflow and wake periodicity. Since the aerodynamic model is based on indicial response functions, a separation of these contributions is possible and allows for the study of their impact on rotor blade flutter. The according flutter results are extracted in terms of frequency and damping behaviour for three test cases that differ in the unsteady aerodynamic model for circulation comprising blade aerofoil, rotor inflow and wake periodicity. As known for articulated rotor blades, also the 7AD blade exhibits a classical bending-torsion coupling. The lowest flutter onset is found for unsteady aerodynamics limited to blade aerofoil, whilst the cases with added rotor inflow and wake periodicity show both the same flutter onset at a 5% larger rotor speed. Here, the influence of rotor inflow plays the major role, since it increases the torsion damping within the critical flutter coupling. Added wake periodicity neither changes frequency nor damping and, hence, does not affect the aeroelastic coupling.

The objective of this study was to investigate the effects of different cockpit primary flight display (PFD) interface designs on pilot cognitive efficiency and cognitive load. This study designed five optimised PFD interfaces and conducted interface cognition experiments to assess cognitive responses across six different PFD interface designs, including the original design. It compared various subjective and objective metrics across different interface designs and evaluated the impact of each design factor on cognitive task performance. The experimental results show that the PFD interface in the original interface design performs better under different flight symbol designs, and the interface with 50% increase in font size performs better among interface designs with different font sizes with relatively lower cognitive load. This study provides experimental support and optimization suggestions for the optimal design of cockpit PFD interface, which can help improve pilots’ perception and operational capabilities, and thus enhance task performance efficiency and flight safety. Future research can investigate the effects of various design factors on the cognitive effects of the interface to enhance the ongoing improvement and optimisation of interface design.

This paper describes a reverse engineering methodology so as to accomplish an aero-propulsive modelling (APM) through implementing a drag polar estimation for a case study jet aircraft in case of the absence of the thrust data of the aircraft’s engine. Since the available thrust force can be replaced by the required thrust force for the sustained turn, this approach allows the elimination for the need of the thrust parameter in deriving an aero-propulsive model utilising equations of motion. Two different modelling approaches have been adopted: (i) implementing the 6-DOF model data for sustained turn and climb flight to achieve induced drag model; and then incorporating the glide data to obtain the total drag polar model; (ii) using the 6-DOF model data together with introducing the effect of CL-α dependency. The error assessments showed that the derived CSA models were able to predict the drag polar values accurately, providing linear correlation coefficient (R) values equal to 0.9982 and 0.9998 for the small α assumption and CL-α dependency, respectively. A direct comparison between the trimmed CD values of 6-DOF model and the values predicted by the CSA model was accomplished, which yielded highly satisfactory results within high subsonic and transonic CL values.

The fault-tolerant control issue of aircraft engines with actuator dynamics and faults is investigated in this paper. By proposing a novel intelligent sliding mode fault-tolerant control (ISMFTC) method, which combines an adaptive dynamic programming (ADP) sliding surface with Grey Wolf Optimizer (GWO) for controller parameter optimisation, the goal is to achieve quality steady-state and dynamic performance in aircraft engines while maintaining strong fault-tolerance properties. Firstly, by considering not only actuator dynamics but also actuator faults, an uncertain nonlinear cascaded model of aircraft engines is developed according to characteristic of aircraft engines and their actuators. Secondly, an ADP-based sliding surface is proposed for considered aircraft engine uncertain nonlinear cascaded system. It can obtain a certain sense of optimised performance, and could be solved by ADP strategy off-line as well. Thirdly, fault-tolerant controller is obtained on the basis of sliding mode theory and adaptive fault estimation law, namely, ADP-based ISMFTC controller. Meanwhile, GWO is integrated into the investigation of ADP-based ISMFTC controller, optimised designable control parameters are obtained subsequently. Besides, robustness analysis is elaborated according to Lyapunov theory, fault estimation error is bounded and states of closed-loop system are uniformly ultimately bounded. Simulation on a twin-shaft turbofan aircraft engine, indicates the effect of proposed ADP-based ISMFTC method.

In a competitive market, airlines continually seek solutions that can reduce their operational costs. Flight path optimisation is a commonly pursued approach to this but requires a large amount of data about the flight environment including the weather information, the aircraft performance and the air traffic control (ATC) requirements. Existing programmes require the user to provide this aircraft performance data in advance and are incapable of generating the information on their own. In this study, using a multidisciplinary approach and numerical optimisations, a novel standalone flight path optimiser (SAFPO) solution is proposed and developed to choose the best flight path for a flight between two points in accordance with the cost objectives. SAFPO uses its own performance calculator, predefined ATC routes, and known weather information to find the optimum flight path which minimises fuel consumption and/or flight time. The aerodynamic characteristics of the aircraft are determined using a validated semi-empirical programme called MAPLA, previously developed for light aircraft analysis. Furthermore, the optimisation process consists of a multidisciplinary-feasible (MDF) framework that employs a genetic algorithm (GA) optimiser. The resulting performance characteristics of the aircraft and the optimisation process are compared with the actual information provided within the flight manual of a Beechcraft Baron G58 aircraft. The optimisation results show that SAFPO can be used to make advances in the daily operations of small and local airlines suffering from a lack of aircraft performance data and help them to choose the scenario that best accomplishes their cost objectives.

Current literature offers limited mass estimation methodologies and their application in the conceptual or preliminary design stages of moderate to high aspect ratio wings with electric, hydrogen or distributed propulsions. This study presents the development and application of a quasi-analytical wing mass estimation method to address this limitation. The proposed method is distinguished from the existing mass estimation methods by its expanded realistic load cases, sensitivity to several design parameters, improved accuracy with short computational time and capabilities for future applications. To achieve these features, new geometric models are introduced; 483 load cases including symmetric manoeuvre, rolling, and combined cases are covered following airworthiness requirements; the structural elements are idealised and sized with strength and buckling criteria; existing methods are evaluated and integrated cautiously for secondary structures and non-optimum masses. A computation time of 0.1s is accomplished for one load case. The developed method achieved the highest accuracy with an average error of -2.2% and a standard error of 1.8% for wing mass estimates compared with six existing methods, benchmarked against thirteen wings of different aircraft categories. The effects of engine numbers with dual- to 16-engine setups and the dry wing concepts on the wing mass are investigated. The optimised number of engines and their locations decreased the wing mass of the high aspect ratio wing significantly. In contrast, the dry wing design increased the wing masses of all baseline aircraft. The future applications and improvements of the presented method in novel configurations and multidisciplinary designed optimisation studies are explained.

With the development of overall design methodologies for hypersonic vehicles and their propulsion systems, nozzles should expand airflow in a short length and provide sufficient thrust. Therefore, the large expansion ratio single expansion ramp nozzle (LSERN) is widely used. The form of the overexpanded flow field in the nozzle is complex, under the conditions of nozzle start-up, low speed and low nozzle pressure ratio (NPR), thereby negatively influencing the entire propulsion system. Thus, the nozzle flow separation pattern and the key factors affecting the flow separation pattern also deserve considerable attention. In this study, the design of SERN is completed using the cubic curve design method, and the model is numerically simulated for specific operating conditions to study the flow separation patterns and the transition processes of different patterns. Furthermore, the key factors affecting the various flow separation patterns in the nozzle are investigated in detail. Results show that the LSERN in different NPRs appeared in two types of restricted shock separation (RSS) pattern and free shock separation (FSS) pattern, as well as their corresponding flow separation pattern transition processes. The initial expansion angle and the nozzle length affect the range of NPRs maintained by the FSS pattern. The initial expansion angle affects the pattern of flow separation, whereas the nozzle length remarkably influences the critical NPR during transition.

In this paper the performance of an internal strut-based thrust vector control (TVC) system has been studied at different expansion conditions of propulsion nozzle. The TVC system uses a cylindrical strut inserted through the diverging wall of a supersonic nozzle. This TVC system can be construed as an alternative to secondary injection TVC method. The nozzle had an expansion ratio of 1.545 and nozzle pressure ratio (NPR) of 6.61 for optimum expansion. Numerical simulations were performed at over-expansion (NPR = 3.94) and under-expansion (NPR = 7.89) conditions for four strut locations (xs) and five strut heights (hs). The strut location from the nozzle throat corresponded to 33%, 50%, 66.7% and 80% of the diverging length (Ld) of the nozzle. The schlieren images of the nozzle exhaust and nozzle internal wall pressure distribution from experiments were compared with the results from numerical simulation and the agreement was quite good. Computational results show that introduction of the strut caused a maximum total pressure loss of 1.5% at its maximum height. The calculations also show that $ \pm $4${}^{\circ}$ thrust deflection angle could be achieved using combinations of strut location and strut height over a range of nozzle operational conditions. Thrust vectoring performance of strut insertion TVC was evaluated using a parameter called vectoring performance index (VPI) defined as thrust deflection angle per unit percentage of pressure loss. The maximum VPI was observed when xs=0.5Ld at ${\bar{h_s}} = 0.429$ in both over-expansion and under-expansion conditions. The study reveals that an internal strut based TVC has a good future potential to be developed as an alternate TVC system obviating the requirement of carrying a fluid tank for a system like secondary injection TVC.

Propulsive fuselage aircraft complement the two under-wing turbofans of current aircraft with an embedded propulsion system within the airframe to ingest the energy-rich fuselage boundary layer. The key design features of this embedding are examined and related to an aero-propulsive performance assessment undertaken in the absolute reference frame which is believed to best evaluate these effects with intuitive physics-based interpretations. First, this study completes previous investigations on the potential for energy recovery for different fuselage slenderness ratios to characterise the aerodynamics sensitivity to morphed fuselage-tail design changes and potential performance before integrating fully circumferential propulsors. Its installation design space is then explored with macro design parameters (position, size and operating conditions) where an optimum suggests up to 11% fuel savings during cruise and up to 16% when introducing compact nacelles and re-scaling of the under-wing turbofans. Overall, this work provides valuable insights for designers and aerodynamicists on the potential performance of their concepts to meet the environmental targets of future aircraft.

Aiming at the problems of poor coordination effect and low positioning accuracy of unmanned aerial vehicle (UAV) formation cooperative navigation in complex environments, an adaptive time-varying factor graph framework UAV formation cooperative navigation algorithm is proposed. The proposed algorithm uses the factor graph to describe the relationship between the navigation state of the UAV fleet and its own measurement information as well as the relative navigation information, and detects the relative navigation information at each moment by the double-threshold detection method to update the factor graph model at the current moment. And the robust estimation is combined with the factor graph, and the weight function measurements are used in the construction of the factor nodes for adaptive adjustment to make the system highly robust. The simulation results show that the proposed method realises the effective fusion of airborne multi-source sensing information and relative navigation information, which effectively improves the UAV formation cooperative navigation accuracy.