In the past few decades, substantial work has been directed towards the design of aircraft structures that maximise fuel efficiency, improve performance and curtail emissions. Aeroelastic optimisation offers an effective way to devise lightweight and fuel efficient structures, with structural stability constraints often driving the design. To date, the aeroelastic optimisation community has relied mostly on linear buckling predictions for the evaluation of structural stability constraints, mainly because of their conservativeness, computational efficiency and simplicity of implementation. This approach typically leads to overly conservative buckling margins, and this over-conservativeness places a glass ceiling over the load carrying capacity of wing structures, consequently restricting the exploration of regions within the design space where considerable weight savings could be achieved.

By contrast to previous works that predominantly rely on linear buckling constraints, the present paper introduces a method to incorporate nonlinear structural stability analysis into aeroelastic optimisations of wingbox-like structures. The method relies on the evaluation of the positive-definiteness of the tangent stiffness matrix, which is an indicator of structural stability. The sign of the stiffness eigenvalues is monitored while tracing the load-displacement equilibrium paths by means of the arc-length method, thus pinpointing the onset of instability. The proposed constraint is tested in a proof of concept structural optimisation of an idealised version of the CRM wingbox. This optimisation shows a $10.9{\rm{\% }} $ reduction in mass with respect to a baseline design that is optimal with a linear buckling approach, promising great potential for application to more realistic aeroelastic optimisations.

Aiming at the problem of fast and consensus obstacle avoidance of multiple unmanned aerial systems in undirected network, a multi-quadrotor unmanned aerial vehicles UAVs (QUAVs) finite-time consensus obstacle avoidance algorithm is proposed. In this paper, multi-QUAVs establish communication through the leader-following method, and the formation is led by the leader to fly to the target position automatically and avoid obstacles autonomously through the improved artificial potential field method. The finite-time consensus protocol controls multi-QUAVs to form a desired formation quickly, considering the existence of communication and input delay, and rigorously proves the convergence of the proposed protocol. A trajectory segmentation strategy is added to the improved artificial potential field method to reduce trajectory loss and improve the task execution efficiency. The simulation results show that multi-QUAVs can be assembled to form the desired formation quickly, and the QUAV formation can avoid obstacles and maintain the formation unchanged while avoiding obstacles.

Friction stir welding (FSW) is a method of solid-state welding used to connect difficult-to-weld materials, such as aluminium alloy and magnesium alloy that cannot be joined using conventional welding techniques. This paper investigates the impact of FSW parameters on the corrosion characteristics of friction stir-welded AA2014-T6 aluminium alloy. Experiments were conducted in accordance with the Taguchi L9 orthogonal array by varying tool rotation speed, weld speed, and axial force across three levels. The FSW joints of the aluminium alloy AA2014-T6 were subjected to corrosion test using the electro-chemical workstation CHI660C. The Tafel plots and the corrosion rates were obtained from the corrosion tests. It was observed from the analysis of variance (ANOVA) results of the corrosion rates, that the tool rotation speed is the most persuading factor in controlling the corrosion rate. The scanning electron microscope (SEM) images of the corroded samples were analysed for the presence of pitting spots and its density.

This paper aims to explore the feasibility of providing boundary layer propulsion and flow control by means of embedded aerofoils that are oscillating in the pure plunge mode. To this end, Navier-Stokes calculations of the low-speed flow over a flat plate with an oscillating small foil in close vicinity to the plate were performed to determine the influence of the wall distance, Reynolds number, and reduced frequency on the aerofoil thrust. The simulations were extensively validated against water tunnel experiments at Reynolds numbers between 440 to 5,940. Good agreement was obtained in terms of mean streamwise velocity profiles and the vortical wake patterns. Results indicate that the thrust increases from its value in unbounded flow with decreasing distance from the plate. The propulsive efficiency exhibits a consistent peak at a non-dimensional plunge velocity of about 0.55. For wall distances between one-half to one chord lengths, vortex pairs are shed in a slightly upward deflected direction independent of the starting motion of the aerofoil. As the wall distance increases further, these vortex pairs change into the well-known reverse Karman vortex street. Example calculations for a flat plate with two foils mounted close to the plate trailing edge and oscillating in counterphase confirm the device’s efficacy.

This study addresses the Aircraft Reactive Scheduling Problem (ARSP) on multiple parallel runways in response to operational disruptions. We specifically consider three disruptive event types; flight cancelations, delays and unexpected arrivals. Interruptions to aircraft schedules due to various reasons (e.g. bad weather conditions) may render the initial schedule not optimal or infeasible. In this paper, the ARSP is conceptualised as a multi-objective optimisation problem wherein considerations encompass not only the quality of the schedule but also its stability, defined as its conformity to an initial schedule, are of interest. A mixed-integer linear programming (MILP) model is introduced to obtain optimal solutions under different policies. Repair and regeneration heuristic approaches are developed for larger instances for which optimal solutions are time-consuming to obtain. While prevailing literature tends to concentrate on individual disruption types, our investigation diverges by concurrently addressing diverse disruption types through multiple disruptive events. We introduce alternative reactive scheduling methodologies wherein the model autonomously adapts by dynamically choosing from a range of candidate solution methods, considering conflicting objectives related to both quality and stability. A computational study is conducted, and we compare the solutions of heuristics to optimal solutions or the best solution found within a time limit, and their performances are assessed in terms of schedule stability, solution quality and computational time. We compare the solutions of heuristics and optimal solutions (i.e. the best solution found so far), and their performances are assessed in terms of schedule stability, solution quality and computational time.

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.

The current emphasis in aerospace component development is on creating safe, reliable and cost-effective technologies. However, the intricate design of stage separation systems renders component reliability a critical factor in determining mission success or failure. One of the technical challenges involves the development of various aerospace mechanisms, such as payload separation, heavy propulsion system separation, ejection of auxiliary components and detachment of rigid components. These stage separation mechanisms commonly employ pyrotechnic devices, which, by their operational nature, impart shock to the spacecraft, potentially causing damage or adverse effects on flight instruments. Therefore, it is imperative to explore multiple viable concepts aimed at reducing shock and experimentally ascertain the impact of shock using diverse shock attenuation techniques. While existing literature primarily addresses shock attenuation with distance from the shock source, limited attention has been given to diminishing shock at the location of the shock-generating element. This study employed various shock-attenuating devices, including dampers, metallic foam structures, viscous materials and dampeners, to assess the effectiveness of shock reduction. Furthermore, the study investigated shock reduction resulting from the elimination of rigid connections, such as bolted joints, from pyro-actuated mechanisms. Through a series of experiments, a conclusive analysis was conducted to determine the approach for achieving a substantial reduction in pyro shock.

The world is currently undergoing a technological transformation with numerous innovative concepts emerging. This shift is driven by remarkable advancements in artificial intelligence and the urgent need for decarbonisation. With this comes a growing demand for skilled engineers who can actively contribute at any stage within the life cycle of a product. This can be the generation of new concepts at low Technology Readiness Levels or contributing actively to their development and operational safety. This paper explores the integration of a 1-day practical activity to reinforce theoretical concepts learned within a classroom-based environment. Small groups of students were given the opportunity of engaging with a small helicopter engine (Rolls-Royce Gnome engine) through the disassembly and reassembly of the exhaust and power turbine section while following the manufacturer’s manual and ensuring industrial norms for safe practice. This hands-on activity included an introduction to tooling, a Gnome familiarisation activity, and an introduction to inspection techniques. Based on the feedback recorded, the students experienced a notable improvement in their basic understanding by effectively reinforcing knowledge acquired within the classroom through active engagement with an actual gas turbine engine.

With developing technology, the usage areas of aircraft are constantly expanded. In aircraft designed for different missions, it is an important issue to evaluate many design possibilities and make optimum designs by taking into account many parameters that are not directly connected to each other with equal importance. In this context, issues such as safety and performance come to the fore in aircraft designs. One of the critical situations affecting flight safety is the takeoff and landing phases of the aircraft. The speed changes that occur in these stages are an important issue. In this study, takeoff speed was predicted with different machine learning algorithms using takeoff speed data of the Boeing B-737-300 type aircraft. Linear regression, support vector regression, classification and regression trees, random forest regression, Extreme Gradient Boosting algorithms were selected from machine learning algorithms for takeoff speed prediction. Base models were created with these selected algorithms and the takeoff speed was predicted by training the data. Considering the obtained results, feature engineered was applied to minimise the error values of the proposed base models. In models developed by applying feature engineered, error values were reduced and better performance was observed in takeoff speed prediction. Takeoff speed values obtained with the developed models and actual flight speed values are presented comparatively for the first time in the literature. The simulation results emphasise that the developed models can be used as an effective and alternative method for takeoff speed prediction.

A simplified configuration was developed to facilitate the mode transition process within an over-under Turbine-Based Combined Cycle (TBCC) inlet. Leveraging dynamic mesh technology, an unsteady numerical simulation of the mode transition was conducted, emphasising the flow characteristics of the mode transition and the impact of key similarity criteria numbers. The findings indicate that at an incoming Mach number of 2.0, the mode transition is paired with a continuous alteration in the capture mass flow of the high-speed duct. This continual change instigates the inlet unstarting, with subsequent flow characteristics being contingent on the historical effect, exhibiting a degree of hysteresis characteristics. When the scale effect is considered, it is observed that a larger model scale results in higher Reynolds (Re) and Strouhal (St) numbers. This directly contributes to a notable delay in the unstart moment, a decrease in the unstart interval, and an enlargement of the hysteresis loop. An examination of control variables reveals that the Re number marginally influences mode transition characteristics, while the St number’s effect constitutes approximately 90% of the scale effect. This conclusively demonstrates that the St number is the predominant similarity criterion number in the mode transition process.

Aiming to address the issue of low accuracy in model predictions obtained from fitting frequency domain response curves for small unmanned helicopters during the process of modeling their flight dynamics, this study proposes a system identification algorithm based on the combination of weighted least squares and improved grey wolf optimisation algorithm. The algorithm utilises the weighted least squares method to obtain the initial model structure, optimises the initial model parameters using the improved grey wolf optimisation algorithm, and enhances the local search and global optimisation ability of the grey wolf optimisation algorithm by introducing an improved grey wolf subgrouping rule, nonlinear convergence factor and dynamic cooperative rule. Ultimately, this approach establishes a dynamic model for small, unmanned helicopters. The identified model is validated using flight test data, with findings demonstrating that this method achieves higher accuracy in model identification and better fits to frequency domain response curves, thus providing a more accurate reflection of the flight dynamics of small unmanned helicopters.

In this article, we delve into the optimal scheduling challenge for many-to-many on-orbit services, taking into account variations in target accessibility. The scenario assumes that each servicing satellite is equipped with singular or multiple service capabilities, tasked with providing on-orbit services to multiple targets, each characterised by distinct service requirements. The mission’s primary objective is to determine the optimal service sequence, orbital transfer duration and on-orbit service time for each servicing satellite, with the ultimate goal of minimising the overall cost. We frame the optimal scheduling dilemma as a time-related colored travelling salesman problem (TRCTSP) and propose an enhanced firefly algorithm (EFA) to address it. Finally, experimental results across various scenarios validate the effectiveness and superiority of the proposed algorithm. The principal contribution of this work lies in the modeling and resolution of the many-to-many on-orbit service challenge, considering accessibility variations — a domain that has, until now, remained unexplored.

Interlaminar delamination damage is a common and typical defect in the context of structural damage in carbon fiber-reinforced resin matrix composites. The technology to identify such damage is crucial for improving the safety and reliability of structures. In this paper, we fabricated carbon fiber-reinforced composite laminates with different degrees of delamination damage, conducted static load experiments on them and used femtosecond fiber Bragg grating sensors (fsFBG) to determine their structural state to investigate the effects of delamination damage on their performance. We constructed a model to identify damage based on the deep residual shrinkage network, and used experimental data to enable it to identify varying degrees of delamination damage to carbon fiber-reinforced composites with an accuracy of 97.98%.

Critical space assets require continuous monitoring to prevent potential losses. Auxiliary satellites protect these assets by observing and tracking approaching targets. Although observation satellites can make rapid autonomous onboard decisions, they face challenges due to limited computational capacity. The two mainstream command and control methods currently available do not meet the demands of onboard decision-making. Highly procedural decision-making methods require extended decision times, while rapid-response intuitive or heuristic methods carry significant error risks. To address this, this paper proposes a multi-granularity decision-making method for optical space surveillance satellites. First, multi-granularity relative orbit determination algorithm models and multi-granularity impulsive orbit manoeuver algorithm models were developed. Based on these models, a granularity selection method for sequential three-way decisions is proposed. In non-emergency situations, fine-granularity models are preferred to conserve fuel, while in emergency situations, coarse-granularity models are used to enhance decision-making speed and reduce positional deviations caused by the manoeuvering game. In random multi-scenario tests, the proposed method demonstrates lower average terminal positional deviations and fuel consumption compared to single-granularity (highly procedural or rapid-response) and random-granularity methods.

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.

This paper develops a novel full-state-constrained intelligent adaptive control (FIAC) scheme for a class of uncertain nonlinear systems under full state constraints, unmodeled dynamics and external disturbances. The key point of the proposed scheme is to appropriately suppress and compensate for unmodeled dynamics that are coupled with other states of the system under the conditions of various disturbances and full state constraints. Firstly, to guarantee that the time-varying asymmetric full state constraints are obeyed, a simple and valid nonlinear error transformation method has been proposed, which can simplify the constrained control problem of the system states into a bounded control problem of the transformed states. Secondly, considering the coupling relationship between the unmodeled dynamics and other states of the controlled system such as system states and control inputs, a decoupling approach for coupling uncertainties is introduced. Thereafter, owing to the employed dynamic signal and bias radial basis function neural network (BIAS-RBFNN) improved on traditional RBFNN, the adverse effects of unmodeled dynamics on the controlled system can be suppressed appropriately. Furthermore, the matched and mismatched disturbances are reasonably estimated and circumvented by a mathematical inequality and a disturbance observer, respectively. Finally, numerical simulations are provided to demonstrate the effectiveness of the proposed FIAC strategy.

This paper presents the concept of a lifting-wing quadcopter unmanned aerial vehicle (UAV), a vertical take-off and landing vehicle (VTOL) with a rear wing, a canard at its front and four propellers. The aerodynamic surfaces are designed so that their mounting angle can be adjusted and fixed before flight, so its performance in transition flight can be studied for a combination of wing and canard mounting angles. A dynamic model using rigid-body equations of motion is presented, which is used to compute the transition flight trajectory from hover to cruise in horizontal flight. The trim conditions were computed for a range of fixed wing and canard mounting angles to study the effects of these variables on transition trajectory parameters such as required power, body pitch angle and propeller rotation speeds as a function of flight speed. Furthermore, a transition flight control algorithm is presented, which has a cascaded PID controller and a reference scheduler to switch between the proper reference states, controls and control allocation matrix. Finally, the transition control algorithm of the conceptual UAV is numerically simulated. Results show that this configuration can perform a fast and smooth transition from hover to cruise flight using the proposed flight control algorithm, substantially reducing required propulsive power in cruise of up to 64%. The application of the control algorithm made notable a transition manoeuver that consists of negatively inclining the aircraft at a negative pitch angle, initially at high intensity, and as the final cruising speed approaches, the inclination is attenuated until the equilibrium pitch angle is reached. Simultaneously with the negative inclination of the pitch angle, there is a slight drop in altitude, which is quickly resumed as the trajectory develops until the final cruising speed. Lastly, this aircraft configuration can be widely used in applications where performance gains in operations currently carried out by multicopters, which cover large distances and need long flight time, would bring great operational advantages.

In this study, measurements and numerical analyses of the temperature distribution of exhaust gas passing through two types of mixers using a micro turbojet engine were performed to investigate the flow mixing performance based on the shape of the mixer, which mixes the bypass air and core air in a gas turbine turbofan engine. To study the mixing characteristics of the mixer, compressed air was supplied through an external duct mounted on a micro turbojet engine to simulate bypass flow, and a system in which hot gas and compressed air were mixed and ejected into the atmosphere was fabricated. A confluent-type mixer and a mixer with 8-lobed mixer channels in the form of a sine wave were used for the experiment. The exhaust gas temperature was measured based on the distance from the nozzle outlet at bypass ratios of 0.5, 1.0 and 1.4. The results showed that the lobed mixer is more effective than the confluent mixer in lowering the exhaust gas temperature as the bypass ratio increased. Numerical analysis results indicated that, in the case of the confluent mixer, flow mixing is primarily performed by shear flow owing to the velocity difference between the core gas and the bypass air. In contrast, in the case of a lobed mixer, flow mixing is achieved through rotational motion and transverse flow. In addition, when the number of lobe channels increased from 8 to 12, the rotational motion increased and the mixing performance improved. Furthermore, infrared signal calculation results confirmed that, as the number of lobe channels increased, improved flow mixing effectively reduced the infrared signal. We conclude that this study helps understand the mixing characteristics of the flow according to the shape of the mixer at various bypass ratios and determine their effect on the characteristics of the infrared signal.

Status information from avionics systems is typically transmitted to airlines, but aircraft cabin systems remain largely disconnected and frequently reliant on manual, paper-based logbooks for defect recording. This results in error-prone processes that compromise data consistency and complicate maintenance planning. Digitalisation offers solutions to these challenges by enabling predictive maintenance, real-time monitoring and streamlined data sharing, improving operational reliability and efficiency. However, developing such systems is inherently complex due to operational constraints and stringent safety and security regulations. Model-based Systems Engineering (MBSE) effectively manages complexity, provide standardised system visualisation and enhance multidisciplinary communication. From a methodological perspective, approaches from literature suitable for addressing aviation maintenance systems were selected and enhanced with allocation techniques and subsequently applied to create system models for both current and digitalised aircraft cabins. This paper showcases MBSE’s relevance to develop digitalised aircraft cabin systems by using the Systems Modeling Language (SysML) enabling stakeholders to visualise system architectures and to make better-informed design decisions. The analysis of the presented SysML models highlights the error-prone structure of current non-digitalised aircraft cabin systems while illustrating new use cases unlocked by digitalisation. A model-based comparison underscores the improved efficiency, reliability and predictive capabilities achieved through digital transformation. This study demonstrates that MBSE provides qualitative advantages in system development by enhancing stakeholder collaboration, clarifying complex system architectures, and providing actionable insights into system behaviour and improvements.

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.