The effect of tab orientation on the mixing characteristics of a Mach 1.6 circular jet issuing from a convergent-divergent (C-D) nozzle is studied experimentally. The tabs used in this study are triangular tabs with sharp and truncated vertices positioned upright and in inverse orientations, along diametrically opposite locations at the nozzle exit. Mixing characteristics of the jet operated at nozzle pressure ratios (NPRs) 3 to 6, in step 1, were studied. For inverse triangular and inverse truncated triangular tabs, a maximum core length reduction of about 87% is achieved at NPR 3. The corresponding core length reductions caused by the upright triangular and truncated triangular, and rectangular tabs are 71, 81 and 84%, respectively. It is found that the jet mixing is strongly influenced by the combined effect of tab geometry, tip effectand the pressure gradient at the nozzle exit. The pressure distribution in the directions along and perpendicular to the tab, at different axial locations, was used to discern the evolution and spread of the jet. The pressure profiles for all tab geometries show that the jet spread perpendicular to the tab is more than that along the tab at all the NPRs studied. The shadowgraph images of the jets show that the waves present in the controlled jet are weaker than those in the uncontrolled jet.

This paper presents a novel artificial intelligence-based autopilot control system designed for the Cessna Citation X (CCX) aircraft longitudinal motion during cruise. In this control methodology, the unknown aircraft dynamics in the state-space representations of each vertical speed (VS) mode and altitude hold (AH) mode were approximated by two multiplayer fuzzy recurrent neural networks (MFRNNs) trained online using a novel approach based on particle swarm optimisation and backpropagation algorithms. These MFRNNs were used with two sliding mode controllers to guarantee the robustness of both VS and AH modes. In addition, a novel fuzzy logic-based transition algorithm was proposed to efficiently switch the controller between these autopilot modes. The performance of the controllers was evaluated with a nonlinear simulation platform developed for the CCX based on data from a Level D research aircraft flight simulator certified by the FAA. The system stability and robustness were proved by the Lyapunov theorem. The simulation, tested under 925 flight conditions, demonstrated the controllers exceptional tracking capability in a variety of uncertainties, including turbulent and non-turbulent flight scenarios. In addition, the design ensured that the smoothness of the control input signals was maintained in order to preserve the mechanical integrity of the elevator actuation system.

Renewed interest in supersonic air travel has prompted researchers to reconsider the design and operation of supersonic transport aircraft. Previously, such aircraft were restricted to overwater routes due to the disturbances caused by their sonic booms. Now, however, low-boom designs and overland flight at marginally supersonic Mach numbers are seen as potential enablers for widespread supersonic air travel. As a result, the trajectories that next-generation supersonic transports may fly are likely to be less constrained than for previous types, and in the last decade there has been a noticeable increase in research focusing on trajectory planning for such aircraft. This paper reviews the different methods that have been used to generate and optimise the flight paths of past and future supersonic transports. The challenges associated with optimising trajectories for aircraft that do not yet exist are discussed, and suggestions for future research activity are presented. Climate-optimal trajectory planning and development of detailed, non-proprietary supersonic aircraft performance models are identified as two key areas for future work.

The success of cooperative unmanned aerial vehicle (UAV) missions relies on effective multi-UAV path planning. To address the issues of limited individual diversity and susceptibility to local optima during the population initialisation phase of the traditional grey wolf optimiser (GWO), this paper proposes an improved chaotic grey wolf optimiser (CGWO). The algorithm enhances population diversity by introducing chaotic initialisation to generate more uniformly distributed initial solutions. Combined with a chaotic local search strategy, it employs a dynamic balancing mechanism that allows individuals in the population to strike a balance between global exploration and local refinement, thereby breaking free from local optima constraints and accelerating optimal solution convergence. The algorithm was validated by using the CEC2017 benchmark functions and simulations of multi-UAV mission scenarios. The results clearly demonstrate that the improved algorithm significantly outperforms the original GWO and other common optimisation algorithms in terms of convergence accuracy and speed during benchmark testing. In multi-UAV mission scenarios, the enhanced algorithm excels in trajectory planning, flexibly avoiding obstacles while maintaining smooth flight paths for UAVs. Overall, this research provides a practical solution for coordinated multi-UAV operational path planning.

Birds and bats are extremely adept flyers: whether in hunting prey, or evading predators, post-stall manoeuvrability is a characteristic of vital importance. Their performance, in this regard, greatly exceeds that of uncrewed aerial vehicles (UAVs) of similar scale. Attempts to attain post-stall manoeuvrability, or supermanoeuvrability, in UAVs have typically focused on thrust-vectoring technology. Here we show that biomimetic wing morphing offers an additional pathway to classical supermanoeuvrability, as well as novel forms of bioinspired post-stall manoeuvrability. Using a state-of-the-art flight simulator, equipped with a multibody model of lifting surface motion and a delay differential equation (Goman-Khrabrov) dynamic stall model for all lifting surfaces, we demonstrate the capability of a biomimetic morphing-wing UAV for two post-stall manoeuvres: a classical rapid nose-pointing-and-shooting (RaNPAS) manoeuvre; and a wall landing manoeuvre inspired by biological ballistic transitions. We show that parametric variation of nonlinear longitudinal stability profiles is an effective open-loop strategy to explore the space of post-stall manoeuvres in these types of UAVs; and it yields insight into effective morphing kinematics to enable these manoeuvres. Our results demonstrate the capability of morphing-based control of nonlinear longitudinal stability to enable complex forms of transient supermanoeuvrability in UAVs.

Gas turbine maintenance strategy relies heavily on accurate estimation of critical component life consumption of gas turbine engines during their operations. The equivalent operating hours (EOH) is a useful concept to measure the engine life consumption and support condition-based maintenance planning for gas turbine engines and their critical components. However, the current EOH calculation methods are mostly empirical and engine-specific, relying on vast operating data and experience. This paper introduces a novel physics-based method to estimate the EOH of the high-pressure turbine rotor blades of a gas turbine engine based on the damages caused by creep and low-cycle fatigue (creep-LCF) interactions. The method has been applied to a typical turbofan engine taking both 440-minute long-haul flight at one flight per day and 60-minute short-haul flight at two flights per day. A comparison of the predicted damages and life consumptions indicates that the creep EOH and also the creep damage of the engine of the short-haul aircraft is about 1.38 times that of the engine of the long-haul aircraft, the LCF equivalent operating cycles (EOC) and also the LCF damage of the engine of the short-haul aircraft is about 2.0 times that of the engine of the long-haul aircraft, and the total damages are more affected by the creep damage than the LCF damage with the creep damage being 6.78 times the LCF damage for the engine of the short-haul aircraft and 9.81 times for the engine of the long-haul aircraft. In addition, the total EOH or the total damage of the engine of the short-haul aircraft is about 1.44 times that of the engine of the long-haul aircraft. The proposed method shows a great potential to provide a quick estimate of the life consumption of gas turbine engines for condition monitoring, and it can be applied to other types of gas turbine engines.

In the process of utilising machine vision-assisted large aircraft component docking assembly, due to the occlusion induced by process equipment such as assembly tooling, the features on the calibration board cannot be extracted by each camera at the same time, resulting in calibration difficulties or calibration failure. This paper aims to propose a stereo calibration method for multi-cameras in large aircraft component assembly to improve calibration accuracy. Firstly, the sub-pixel edge extraction method based on Canny-Zernike is proposed to accurately extract the circular edges and circle centres of the calibration board, and the Zernike moment model is improved. The circle centre sorting method based on the triangular markers is introduced to realise the sorting of circle centres on the calibration board. Secondly, the intrinsic and extrinsic parameter models of multi-cameras and the visual parameter models between cameras are constructed, and Zhang’s calibration method and indirect calibration method are integrated to solve the parameters. Subsequently, the distortion correction model is optimised by Levenberg-Marquardt. Finally, experiments are performed to test the proposed method. The results show that the proposed method, compared with uncalibration and Zhang’s calibration method, the proposed method achieves stereo calibration of the multi-cameras under complex working conditions, enhances the calibration accuracy and improves the quality of the large aircraft component docking assembly.

The electrohydrodynamic force of a surface dielectric barrier discharge (SDBD) has been well-developed for flow control applications during recent decades. In the present paper, a geometrical modification of the SDBD plasma actuator has been applied to induce a vectorised normal flow at the trailing edge of a NACA0015 aerofoil. The pitot-tube velocity measurements of the normal jet along its propagation direction revealed formation of vortices at the centre of the electrode distance played a role in flow control authority of the jet. The aerodynamic operation of the double-SDBD structure as a virtual flap was assessed versus a single counter-flow jet of a floating structure at pre- and post-stall angles of attack at low Reynolds numbers. It was found that at small angles of attack, the steady counter-flow gives the most effectiveness of lift enhancement in low velocity, whereas in the higher velocity the unsteady one results in more efficacy. The efficiency of both steady and unsteady normal jets increased considerably at high angles such that a lift coefficient improvement of 38% was achieved at $\alpha = 14^\circ $. In the higher velocity, the plasma induced vertical flow acts like a Gurney flap, causing lift increase at high angles by affecting the vortical structures at the trailing edge. Evaluating the obtained results recommended employment of the induced normal flow as a virtual flap at high angles of attack in the unsteady actuation mode.

This article presents the implementation of a new monopulse auto-tracking architecture at the Oran ground station (GS). This architecture is based on a metaheuristic particle swarm optimisation (PSO) algorithm, which measures and adjusts the Q(R) summation associated with the satellite’s main beam direction to ensure optimal synchronisation between the GS and the satellite in terms of antenna pointing. This implementation was validated through practical tests during ALSAT-2B satellite flybys, comprising two distinct scenarios. In the first scenario, the satellite captures new images while simultaneously transmitting data from previously recorded images, thus leading to a misalignment between its antenna and the GS. The second scenario focused solely on data transmission; the satellite being directly aligned with the GS. The results indicate that the pointing error accuracy remains below 0.6 degrees, in accordance with the nominal specifications, thereby enhancing communication performance with a higher received signal level of −55 dBm, which resulted in no loss of images.

The noise levels produced by high-performance supersonic military aircraft engines significantly exceed those of civilian aircraft, highlighting the critical importance of predicting military aircraft noise levels. This paper shows the modeling and assessment of the correlation between sound frequency and sound pressure level (SPL) using particle awarm optimisation (PSO) and the cuckoo search algorithm (CSA) for the high-performance fighter aircraft F-22 Raptor. The developed model aims to predict noise with high precision at various microphone angles from 60° to 150°. As a result of the analysis, the MAPE value for CSA was found to be below 1% for 10 different inlet angles, while the maximum mean absolute percentage error (MAPE) for PSO was 1.7863%. The large dataset ranging from 238 to 762 data points are used and the minimal error values confirm the high accuracy of the model. Additionally, the PSO and CSA algorithms were compared indirectly. The lower error values for CSA, along with its correlation coefficient (R) values closer to 1 indicate that the CSA method gives better results than PSO.

In this paper, a single passage unsteady numerical simulation is carried out. Three different self-recirculating casing treatment structures with circumferential coverage ratios of 20%, 40% and 60% were designed. The calculation results show that as the circumferential coverage ratio increases, the stability enhancement ability of the self-recirculating casing also increases. Especially when the circumferential coverage ratio increases to 60%, the self-recirculating casing achieves the largest increase in stall margin, with an increase of 49.05%, but the decrease in the peak efficiency is 1.33%. An increase in the circumferential coverage ratio enhances the suction capacity of the self-recirculating casing. This enables it to better suppress the expansion of the leakage flow and reduce the degree of blockage within the passage. The self-recirculating casing can inhibit the occurrence of vortex breakdown in the tip passage. However, at the low flow rate point, it cannot effectively eliminate the interaction between the leakage streamlines. When the circumferential coverage ratio is relatively large, it can suppress the airflow separation phenomenon. The flow separation near the blade trailing edge and the mixing of the leakage flow within the tip passage are important reasons for the internal flow instability of the self-recirculating casing compressor.

Unstable approaches are one of the main safety concerns that contribute to approach and landing accidents. The International Air Transport Association reports that, between 2012 and 2016, 61% of accidents occurred during the approach and landing phase, of which 16% involved unstable approaches. This study addresses this issue by applying the Functional Resonance Analysis Method to examine the dynamics of stable approaches. A total of 195 aviation safety reports, which referred to near-miss data from a single airline, were used in the analysis to identify both actual and aggregated variability. The findings revealed that variability mainly occurred in the following functions: control speed, configure aircraft for landing, communicate with air traffic control and manage flight paths. Effective communication, coordination and collaboration, as well as monitoring, briefings and checklists, were key factors in managing the variability of a stable approach. The study reveals how adopting a perspective of ‘how things go right’ provides insightful findings regarding approach stability, complementing traditional approaches focused on ‘what went wrong’. This study also highlights the value of utilising the Functional Resonance Analysis Method to analyse near-miss data and uncover systemic patterns in everyday flight operations.

To investigate the stall mechanisms of a multi-stage axial compressor under different rotational speeds and identify the initial stall stages, this study focuses on a high-load nine-stage axial compressor, validated through experimental data. The results reveal that at 100% corrected rotational speed, flow instability is primarily triggered by corner separation in the front four stators (S1–S4). At 80% corrected rotational speed, the instability stems from the interaction between the first rotor (R1) tip leakage vortex and the main flow, coupled with the front four stators’ corner separation. Precise identification of initial stall locations in multi-stage axial compressors is imperative. The study first employs qualitative flow-field analysis to identify initial stall locations by comparing meridional mass flux variation contour maps and axial velocity iso-surfaces. The results show that the stall inception occurs at the S2 root under 100% corrected rotational speed, while at 80% corrected rotational speed, stall initiates simultaneously at both the S2 root and the R1 tip. Furthermore, an innovative three-dimensional flow blockage quantification method was established to systematically evaluate blockage severity within multi-stage blade passages. This approach utilises relative blockage variation metrics to quantitatively identify regions of rapid flow deterioration, achieving remarkable consistency with qualitative flow-field analysis. The qualitative and quantitative analysis results have been mutually corroborated. The proposed blockage quantification approach enables precise evaluation across stages without complex flow fields comparisons, allowing rapid identification of stall-initiating locations and supporting subsequent stability enhancement optimization.

In this study, self-piercing riveting (SPR) connection, which is one of the joining techniques of aluminum alloys, is investigated. SPR is a cold mechanical joining process used to join two or more sheets of material by pushing the rivet that pierces the upper sheet under the guidance of a suitable mold and then locking it to the lower sheet. The SPR process was carried out with the split Hopkinson pressure par test system. The bar inside the cylinder, accelerated by pressure, performs the riveting process by hitting the surface of the mold developed for SPR. In this study, different numbers of slots were opened on the rivet tail, and the process was carried out using SPRs at different deformation rates. A powerful tomography scanner device designed for 3D metrology was used to visualise the SPR joining mechanisms without cutting. Tensile-shear tests were applied to the samples made with rivets with different numbers of slots and different pressures, and cross-tension tests were also applied to the samples prepared with rivets with different numbers of slots. The opened slots caused a decrease in the maximum strength of the samples. It was understood that the appropriate riveting pressure could change the connection strength by approximately 50%. In general, the force values decreased as the number of slots increased.

Reinforcement learning (RL) has demonstrated computational efficiency and autonomy in solving unmanned aerial vehicle (UAV) obstacle avoidance problems. However, practical applications still remain challenges, such as three-dimensional manoeuvres, dynamic obstacles and kinematic constraints. This paper proposes a real-time obstacle avoidance method based on RL and a kinematic model, where the RL framework outputs 3D-axis velocity to enable continuous UAV manoeuver control. To perceive large-scale, highly dynamic obstacles, we establish a 3D safety separation model and construct a modular observation matrix to enhance perception capability. The Soft Actor-Critic (SAC) algorithm is adopted to enhance stochastic exploration in high-dimensional state space while incorporating flight uncertainty. Under simulation, the proposed method effectively avoids dynamic obstacles. The optimised state space boosts learning speed and performance. This provides an effective solution for UAV autonomous obstacle avoidance in complex environments.