Composite materials are enjoying an increasing use in aircraft structures. As more fleets transition from metal to more composite aircraft, the practice of maintenance is also adjusting. Handling, inspection and repair of aircraft composites following non-visible or barely visible damage are among the areas of concern, due to associated cost and safety implications. A pilot study was performed to explore the level of awareness and understanding of aviation maintenance practitioners around these issues. In addition, this research project sought to identify factors related to the technical/engineering judgement capacity of the personnel working with composites and to gauge the need for specialised education and training. A questionnaire survey was administered to a group of 40 professionals working for an aircraft maintenance, repair and overhaul (MRO) organisation. Descriptive statistics in conjunction with analysis of variance (ANOVA) were used to analyse the results. The sources of impact and common areas affected on the aircraft have been identified, with situational awareness suggested as the most important mitigator against impact damage. Over 70% of the participants would refer to their engineering manager for instructions on how to handle composite damage. The need for higher standardisation for composites’ maintenance, repair and handling issues emerged as a common theme across different sections of the survey. Almost all respondents agree on the need for specialised knowledge and training for the handling, repair and inspection of composites.

The spray characteristics significantly affected the combustion performance. The injection pressure and fuel properties are factors that affect the spray cone angle, penetration, and droplet distribution. Although substantial research has been conducted on spray attributes, understanding the complex biofuel spray dynamics in real nozzles and injectors is crucial. This study examines hydro-processed esters and fatty acid (HEFA) spray characteristics of used cooking oil and palm oil biodiesel in a constant-volume chamber. The study was performed by varying the injection pressures ranging from 30 to 120psi for pure fuels and Jet A-1 blends. Experiments were conducted at standard sea-level atmospheric pressure and an ambient temperature of ±297K using an airblast fuel injector. The initial fuel temperature was set at ±302K. Jet A-1 was used as the baseline fuel for the comparative analysis. Particle image velocimetry (PIV) was employed to visualise the microscopic and macroscopic characteristics of the fuel spray. The results revealed a progressive increase in the penetration length corresponding to an increase in the injection pressure. Lower pressures yielded non-uniform particle distributions across the spray area, whereas cone angle augmentation stabilised at elevated pressures. A blend of 60% Jet A-1 and 40% HEFA closely matched Jet A-1 characteristics, indicating alternative aviation fuel potential. These real-time insights into spray behaviour are critical for enhancing the fuel efficiency and mitigating the generation of particulate emissions resulting from spray combustion.

This work presents a numerical investigation targeting to simulate the slice of a small aircraft cabin as an experimental facility with a controlled environment, to assess passenger comfort when exposed to high volatile organic compound (VOC) concentrations. The mixing and transport of chemical species are evaluated using computational fluid dynamics for 800 s of in-cabin actual flow time and measurements are taken every 10 s from selected computational nodes close to the passengers’ noses. The results are used to create a dataset that trains four different machine learning classifiers, namely, the Random Forest, Support Vector Machine, Logistic Regression and Naive Bayes, and their performance is compared. Moreover, an additional simulation of the cabin with a filtering system utilising high-efficiency particulate air and activated carbon filters is conducted, to evaluate the impact of the molecular weight of the compounds on their residence time, and compare it to the simulation without the filters. Results indicate that the model is insensitive to the inlet air mass flow variation and that the mass of the VOCs measured in the monitored computational nodes remains relatively unaffected, meaning that the impact of the air-conditioning system setting is minor. Additionally, a Boruta feature selection algorithm is used to determine the importance of each measurement of the simulation and to form a dataset that will train the four machine learning classifiers. Furthermore, the comparison of the two simulations, the one with and the one without the filters, indicates that the residence time (RT) of the compounds is independent of their molecular weight, as they all show equivalent percentile reductions, with the naphthalene and styrene showing a 28.5% and 28.3% reduction respectively, compared to the simulation without the filters. Finally, in-cabin flow irregularities are present, disrupting the flow symmetry and suggesting that not all passengers share the same traveling experience.

Coupling of clearance joint and harsh aerodynamic heating environment is an inevitable nonlinear factor in folding mechanism of the fin of high-speed aircrafts that remarkably modifies natural frequencies and modes of vibration from the initial design state. However, accurately predicting dynamic properties of deployable fin with full consideration of these effects is not common industry practice. A practical semi-analytical model based on Hertz contact theory and ESDU-78035 model is proposed in this study to investigate high-temperature connection stiffness of local hinged–locked mechanisms. Material property degradation and clearance variation caused by thermal expansion are comprehensively considered and quantified in this model. Vibration characteristics of the assembled deployable fin are then solved using finite element method (FEM). The real-time evolutionary process of thermal mode of the fin is discussed. And natural frequencies of fixed-value and time-varying connection stiffness are compared. The simulation results of this study demonstrate that the relative error of structure temperature between the sequential approach and fully coupled simulations is less than 6.98%. The connection stiffness (slope of the load-displacement curve) of the folding mechanism under high temperature conditions decreases by 3.52%, and the variation is mainly caused by the degradation of the elastic modulus of the material, while the clearance change due to the thermal expansion has no significant effect on the slope. The natural frequency of the deployable fin exhibits an inverse correlation with the temperature change trend, and the first three frequencies decrease by 1.67, 7.75, and 16.28 Hz compared to the initial value, respectively.

In recent years, there has been an increasing interest in the research and development of hybrid airships for various applications. Airship design involves multiple design parameters from various disciplines that interact mutually. Existing design methodologies, however, are often limited to fixed shapes and geometry. This paper provides a comprehensive parametric design approach for the sizing of multi-lobed hybrid air vehicles for low- and high-altitude applications. The proposed design techniques are robust so that the designer has the freedom to change the number of lobes, the relative location of lobes, the envelope profile, and the optimiser for the design optimisation process. The outcomes of the proposed methodology are envelope volume, wetted surface area, length and span of the envelope, sizing and layout of the solar array, and sizing and layout of the fins. The modeling techniques highlighted in this paper are very efficient for the design and optimisation of multi-lobed airships in the conceptual design phase with a large design exploration space. The robustness of the shape generation algorithms is tested on some of the standard envelope profiles of airships. The effect of the shape and geometry of the multi-lobed envelope on added mass is demonstrated through the added mass estimation using Boundary Element Method.

This paper investigates the effect of the optimised morphing leading edge (MLE) and the morphing trailing edge (MTE) on dynamic stall vortices (DSV) for a pitching aerofoil through numerical simulations. In the first stage of the methodology, the optimisation of the UAS-S45 aerofoil was performed using a morphing optimisation framework. The mathematical model used Bezier-Parsec parametrisation, and the particle swarm optimisation algorithm was coupled with a pattern search with the aim of designing an aerodynamically efficient UAS-45 aerofoil. The $\gamma - R{e_\theta }$ transition turbulence model was firstly applied to predict the laminar to turbulent flow transition. The morphing aerofoil increased the overall aerodynamic performances while delaying boundary layer separation. Secondly, the unsteady analysis of the UAS-S45 aerofoil and its morphing configurations was carried out and the unsteady flow field and aerodynamic forces were analysed at the Reynolds number of 2.4 × 106 and five different reduced frequencies of k = 0.05, 0.08, 1.2, 1.6 and 2.0. The lift (${C_L})$, drag (${C_D})$ and moment (${C_M})\;$coefficients variations with the angle-of-attack of the reference and morphing aerofoils were compared. It was found that a higher reduced frequencies of 1.2 to 2 stabilised the leading-edge vortex that provided its lift variation in the dynamic stall phase. The maximum lift $\left( {{C_{L,max}}} \right)$ and drag $\left( {{C_{D,max}}} \right)\;$coefficients and the stall angles of attack are evaluated for all studied reduced frequencies. The numerical results have shown that the new radius of curvature of the MLE aerofoil can minimise the streamwise adverse pressure gradient and prevent significant flow separation and suppress the formation of the DSV. Furthermore, it was shown that the morphing aerofoil delayed the stall angle-of-attack by 14.26% with respect to the reference aerofoil, and that the ${C_{L,max}}\;$of the aerofoil increased from 2.49 to 3.04. However, while the MTE aerofoil was found to increase the overall lift coefficient and the ${C_{L,max}}$, it did not control the dynamic stall. Vorticity behaviour during DSV generation and detachment has shown that the MTE can change the vortices’ evolution and increase vorticity flux from the leading-edge shear layer, thus increasing DSV circulation. The conclusion that can be drawn from this study is that the fixed drooped morphing leading edge aerofoils have the potential to control the dynamic stall. These findings contribute to a better understanding of the flow analysis of morphing aerofoils in an unsteady flow.

Accurate and reliable computation of the aerodynamic characteristics of wind turbines is very important for the development of new efficient designs. The flow around a wind turbine is modeled by a permeable disc (PD), solved through the Unsteady Reynolds-Averaged Navier–Stokes equations (URANS), here named PD/URANS method. The finite volume method and a total variation diminishing (TVD) scheme solve numerically the flow governing equations. The turbulent flow in the wake of the wind turbine is simulated utilising a one-equation turbulence model. The Glauert correction calculation considers a uniform normal force distribution (CT) on the virtual permeable disc applied to the flow, while the axial induction factor is obtained directly from the numerical solution of the URANS equations. The numerical axial induction factor obtained agrees fairly well with Glauert correction, except if the flow behind the turbine is highly unsteady and Reynolds number dependent.

A sliding mode corrector is presented for disturbance rejection in position sensing using relatively accurate velocity measurement. The corrector design is based on a robust second-order sliding mode (2-sliding mode), which makes the fusion of position and velocity on a sliding surface to reject disturbance. Even when the frequency bands of disturbance and actual position signal overlap, or large-magnitude disturbance exists, the corrector can still provide the accurate and smoothed estimate of position. The proposed corrector is applied to a jet UAV navigation and control. In the unmanned aerial vehicle (UAV) system, the disturbances exist in position and attitude measurements, and the uncertainties exist in the system dynamics. For the UAV trajectory tracking control, the system model is constructed in the earth-fixed frame, and the constructed model is fit for observer design to estimate system uncertainties. The control laws are designed according to the correction of position and attitude by the correctors and the estimation of system uncertainties by an existing observer. Finally, the flight experiment demonstrates the effectiveness of the proposed method.

A comparison of the modelling methodologies to capture the damage onset and delamination initiation in Abaqus and LS-Dyna is presented. A quasi-isotropic carbon fibre reinforced polymer laminate is modelled under a low-energy impact scenario. Hashin, Puck and Cuntze criteria are implemented for assessing intra-laminar damage in Abaqus in the linear elastic regime without damage evolution, with Virtual Crack Closure Technique being used for inter-laminar failure. In LS-Dyna, the Chang-Chang criterion is used for the intra-lamina failure with damage evolution, whereas delamination is captured using cohesive zone model and the tiebreak contact algorithm. The implementations carried out by both finite element software result in a modelling work well set to analyse and predict the impact response at the initial stages of delamination and damage within the plies. The composite damage criteria used in both finite element codes overall predict stiffer results when compared with the experimental data, however, remain in close agreement with each other.

Tight budgets often limit the scope of test campaigns within the development programmes of small uncrewed air vehicles (UAVs). This paper explores a range of combinations of instrumentation suites and protocols for both wind tunnel and flight evaluation, focusing on the key aspect of drawing up the drag curve of the airframe. Through extensive testing of a 5kg maximum take-off mass, fixed wing, twin motor, richly instrumented test platform, we show that automated glides over a range of airspeeds and the slow down manoeuvre are effective ways of determining power-off drag, while estimating thrust from propeller speed, and voltage and current sensing based methods work well for the power-on case. We also seek the most time-efficient and robust mix of the above manoeuvres to yield a given drag curve accuracy level and we find wind condition impacts the manoeuvre makeup of the optimal strategy.

To enhance the performance of anti-ship missiles cooperative attack, this paper proposes a finite-time trajectory shaping-based cooperative guidance law (TSCGL). Firstly, the cooperative guidance model is established on segmented linearisation of the missile’s heading angle. Then, a trajectory shaping guidance law for a single missile is derived by a weighted optimal energy cost function and Schwarz inequality. On this basis, a finite-time TSCGL is proposed combined with trajectory shaping technology and finite-time theory. The desirable finite-time convergence performance can ensure a simultaneous attack. Through an improved method of time-to-go estimation, it is independent of small-angle assumption and relaxes the launching conditions of the missiles. Additionally, the proposed finite-time TSCGL can achieve better damage performance through energy management. Finally, simulation results demonstrate the effectiveness and superiority of the proposed finite-time TSCGL.

With the increase of air transportation, some crossing waypoints (CWPs) are becoming bottlenecks in the operation of air traffic networks. This paper presents a CWP operation optimisation framework based on a two-stage optimisation method. First, we considered the interests of airlines and air traffic controllers and established a flight-level dynamic allocation model for the CWP to minimise the flight-level deviation and the number of flight conflicts. A multi-objective, self-adaptive differential evolution-local search hybrid algorithm was used to solve the model in a parallel computing manner. Subsequently, a flight conflict resolution algorithm based on the Monte-Carlo tree search was designed for flight conflicts that existed after the optimisation. Finally, based on real operation data, four experimental scenarios were constructed, and the air traffic operation simulation system was used for experimental validation. For daily traffic and 1.2 times peak traffic scenarios, the average flight-level deviation reduction rates after optimisation were 53% and 39%, and the successful flight conflict resolution rates reached 89% and 75%, respectively. The experimental results showed that this optimisation framework can effectively balance the number of flight conflicts with the efficiency of flight-level usage and directly improve the capacity of the CWP, which can be used as a reference for air traffic control auxiliary decision support systems.

The flow characteristics of the plume ejected from a micro-jet engine’s rectangular exhaust nozzle have been studied by conducting experimental and numerical analyses. The radiated infrared signature of a plume ejected from a rectangular exhaust nozzle with a large aspect ratio in a jet propulsion engine is known to be significantly lower than that of a plume ejected from a circular exhaust nozzle. The velocity and temperature distributions, which are the flow characteristics of the jet, were measured to investigate this phenomenon. For this purpose, we installed a circular nozzle and a rectangular exhaust nozzle with an aspect ratio of five to a micro-jet engine. The results showed that the plume spreads wider as it moves away from the nozzle exit and that the velocity rapidly decreases in the case of the rectangular nozzle, contrary to the case of the circular nozzle. Similar tendencies were observed for the temperature distribution and magnitude of the ejected plume. Thus, we concluded that the flow distribution caused by the nozzle shape induces a greater drop in the radiated infrared signature of the plume ejected from the rectangular nozzle than the circular nozzle. Flow analysis was conducted to evaluate the flow in and outside the exhaust nozzle; results similar to those of the experiment were obtained. These results show that the ejecting jet has a greater mixing effect on the air outside when using the rectangular nozzle than the circular nozzle.

The Arcanum mission is a proposed L-class mother-daughter spacecraft configuration for the Neptunian system, the mass and volume of which have been maximised to highlight the wide-ranging science the next generation of launch vehicles will enable. The spacecraft is designed to address a long-neglected but high-value region of the outer Solar System, showing that current advances make such a mission more feasible than ever before. This paper adds to a series on Arcanum and specifically provides progress on the study of areas identified as critical weaknesses by the 2013–2022 decadal survey and areas relevant to the recently published Voyage 2050 recommendations to the European Space Agency (ESA).

In this paper, we investigate the constrained attitude control problem of hypersonic vehicles (HVs). An improved prescribed performance dynamic surface control method is proposed based on an adaptive scaling strategy. Because of the uncertain time-varying disturbances, the controlled state may violate the constraint in the prescribed performance control (PPC) framework. An adaptive scaling strategy is introduced in the PPC method to avoid state violation. The performance function is scaled with respect to the state adaptively. Moreover, a nonlinear disturbance observer is used to compensate the sum of external and other internal disturbances of the system. The proposed method improves the system dynamic performance while ensuring the system robustness. Furthermore, the stability of the closed-loop system is proved by Lyapunov analysis. Finally, numerical simulations are implemented to verify the effectiveness of the PPC method and superiority over other methods.

A compressible large eddy simulation (LES) is performed to study a pulsed jet actuator that is used to control a turbulent axisymmetric bluff body wake. The actuator is driven at low-frequency ($f = 200$Hz, $S{t_\theta } = 0.029$) and high amplitude (${C_\mu } = 0.034$). The numerical scheme and a suitable boundary condition for the pulsed jet are validated, showing good agreement with experimental results. A comparison of the velocity boundary condition and the moving boundary condition shows that, in the vicinity of the orifice/slot and in the downstream region, the results from these two methods are identical, while the fluid behaviour inside the cavity shows difference. An analysis of the pulsed jet actuator shows that the phase lag of the cavity pressure is determined by the integration of the diaphragm motion and the pulsed jet. The mean total pressure distribution shows that the total pressure loss is concentrated in the vicinity of the slot. Dynamic mode decomposition (DMD) on the pressure field is used to extract coherent structures which oscillate with the same frequency as that of the diaphragm motion. Some small-scale high-frequency structures are also apparent.

Machine vision has been extensively researched in the field of unmanned aerial vehicles (UAV) recently. However, the ability of Sense and Avoid (SAA) largely limited by environmental visibility, which brings hazards to flight safety in low illumination or nighttime conditions. In order to solve this critical problem, an approach of image enhancement is proposed in this paper to improve image qualities in low illumination conditions. Considering the complementarity of visible and infrared images, a visible and infrared image fusion method based on convolutional sparse representation (CSR) is a promising solution to improve the SAA ability of UAVs. Firstly, the source image is decomposed into a texture layer and structure layer since infrared images are good at characterising structural information, and visible images have richer texture information. Both the structure and the texture layers are transformed into the sparse convolutional domain through the CSR mechanism, and then CSR coefficient mapping are fused via activity level assessment. Finally, the image is synthesised through the reconstruction results of the fusion texture and structure layers. In the experimental simulation section, a series of visible and infrared registered images including aerial targets are adopted to evaluate the proposed algorithm. Experimental results demonstrates that the proposed method increases image qualities in low illumination conditions effectively and can enhance the object details, which has better performance than traditional methods.

The ground delay program (GDP) is a commonly used tool in air traffic management. Developing a departure flight delay prediction model based on GDP can aid airlines and control authorities in better flight planning and adjusting air traffic control strategies. A model that combines the improved sparrow search algorithm (ISSA) and Multilayer Perceptron (MLP) has been proposed to minimise prediction errors. The ISSA uses tent chaotic mapping, dynamic adaptive weights, and Levy flight strategy to enhance the algorithm’s accuracy for the sparrow search algorithm (SSA). The MLP model’s hyperparameters are optimised using the ISSA to improve the model’s prediction accuracy and generalisation performance. Experiments were performed using actual GDP-generated departure flight delay data and compared with other machine learning techniques and optimisation algorithms. The results of the experiments show that the mean absolute error (MAE) and root mean square error (RMSE) of the ISSA-MLP model are 16.8 and 24.2, respectively. These values are 5.61%, 6.3% and 1.8% higher in MAE and 4.4%, 5.1% and 2.5% higher in RMSE compared to SSA, particle swarm optimisation (PSO) and grey wolf optimisation (GWO). The ISSA-MLP model has been verified to have good predictive and practical value.

This paper proposes a methodology to define and quantify the precision uncertainties in aerothermodynamic cycle model comparisons. The total uncertainty depends on biases and random errors commonly found in such comparisons. These biases and random errors are classified and discussed based on observations found in the literature. The biases account for effects such as differences in model inputs, the configurations being simulated, and thermodynamic packages. Random errors consider the effects on the physics modeling and numerical methods used in cycle models. The methodology is applied to a comparison of two cycle models, designated as the model subject to comparison and reference model, respectively. The former is the so-called Aerothermodynamic Generic Cycle Model developed in-house at the Laboratory of Applied Research in Active Control, Avionics and AeroServoElasticity (LARCASE); the latter is an equivalent model programmed in the Numerical Propulsion System Simulation (NPSS). The proposed methodology is intended to quantify the bias and random errors effects on different cycle parameters of interest, such as thrust, specific fuel consumption, among others. Each bias and random errors are determined by deliberately preventing the effects from other biases and random errors. The methodology presented in this paper can be extended to other cycle model comparisons. Moreover, the uncertainty figures derived in this work are recommended to be used in other model comparisons when no better reference is available.

Every manufacturing procedure is subject to tolerance variations. Over the years, a set of key characteristic features (KCF) that can explain the effect of manufacturing variations on the aero-mechanical performance of a fan blade has been devised and monitored to ensure conformality and good performance. The KCFs are derived from a cloud of coordinate measurement machine (CMM) points and are defined on approved engineering drawings for the manufactured part. In this paper, it is demonstrated that some of the traditional, common wisdom KCFs are not adequate to explain the engine performance deviation behaviour on a test bed at the sea-level condition. On the other hand, good correlation is found by analysing a set of engineering parameters drawn from a new inverse-mapping procedure of the CMM data. It is further demonstrated that a deviation measured via CMM or 3D structured light (GOM) data in cold conditions can be translated to a variation in the hot running shape of the blade. Having identified the key blade features, a cheap alternative to modifying the manufacturing procedure is devised to recover the fan performance by optimising its leading-edge shape.