This paper proposes a cooperative midcourse guidance law with target changing and topology switching for multiple interceptors intercepting targets in the case of target loss and communication topology switching. Firstly, a three-dimensional guidance model is established and a cooperative trajectory shaping guidance law is given. Secondly, the average position consistency protocol of virtual interception points is designed for communication topology switching, and the convergence of the average position of virtual interception points under communication topology switching is proved by Lyapunov stability theory. Then, in the case of the target changing, the target handover law and the handover phase guidance law are designed to ensure the acceleration smoothing, at last, the whole cooperative midcourse guidance law is given based on the combination of the above guidance laws. Finally, numerical simulation results show the effectiveness and the superiority of the proposed cooperative midcourse guidance law.

As avionics systems become increasingly complex, traditional fault prediction methods are no longer sufficient to meet modern demands. This paper introduces four advanced fault prediction methods for avionics components, utilising a multi-step prediction strategy combined with a stacking regressor. By selecting various standard regression models as base regressors, these base regressors are first trained on the original data, and their predictions are subsequently used as input features for training a meta-regressor. Additionally, the Tree-structured Parzen Estimator (TPE) algorithm is employed for hyperparameter optimisation. The experimental results demonstrate that the proposed stacking regression methods exhibit superior accuracy in fault prediction compared to traditional single-model approaches.

The challenging tracking control issue for a space manipulator subject to parametric uncertainty and unknown disturbance is addressed in this paper. An observer-based fixed-time terminal sliding mode control methodology is put forward. Firstly, a nonlinear disturbance observer is introduced for exactly reconstructing the lumped uncertainty without requiring any prior knowledge of the lumped uncertainty. Meanwhile, the estimation time’s upper bound is not only irrelevant to the initial estimation error but can be directly predicted in advance via a specific parameter in the observer. Invoking the estimated information, a fast fixed-time tracking controller with strong robustness is designed, where a novel sliding mode surface incorporated enables faster convergence. The globally fixed-time stability of the closed-loop tracking system is rigorously demonstrated through Lyapunov stability analysis. Finally, numerical simulations and comparisons verify the validity and superiority of the suggested controller.

So much has been written about Frederick W. Lanchester over the years, it is hard to imagine finding something new to discuss about his efforts in aerodynamics. Many of the previous Lanchester Memorial Lectures discussed topics such as wing aerodynamics, aircraft concepts and design, unsteady rotor aerodynamics, aerodynamics research and a wide variety of other related aerodynamic topics. However, there has never been a lecture about Lanchester’s book Aerodynamics as a tool for aerodynamics education in the early 20th century. The lecture will discuss his book relative to other aerodynamics books before and after 1907, and uncover how Lanchester’s book had a very distinct, and important, contribution to make for aerodynamic education.

In this article, a genetic algorithm (GA) is proposed as a solution for the path planning of unmanned aerial vehicles (UAVs) in 3D, both static and dynamic environments. In most cases, genetic algorithms are utilised for optimisation in offline applications; however, this work proposes an approach that performs real-time path planning with the capability to avoid dynamic obstacles. The proposed method is based on applying a genetic algorithm to find optimised trajectories in changing static and dynamic environments. The genetic algorithm considers genetic operators that are employed for path planning, along with high mutation criteria, the population of convergence, repopulation criteria and the incorporation of the destination point within the population. The effectiveness of this approach is validated through results obtained from both simulations and experiments, demonstrating that the genetic algorithm ensures efficient path planning and the ability to effectively avoid static and dynamic obstacles. A genetic algorithm for path planning of UAVs is proposed, achieving optimised paths in both static and dynamic environments for real-time tasks. In addition, this path planning algorithm has the properties to avoid static and moving obstacles in real-time environments.

The variable stator vanes (VSV) are a set of typical spatial linkage mechanisms widely used in the variable cycle engine compressor. Various factors influence the angle adjustment precision of the VSV, leading to the failure of the mechanism. The reliability analysis of VSV is a complex task due to the involvement of multiple components, high dimensionality input and computational inefficiency. Considering the hierarchical characteristics of VSV structure, we propose a novel multi-layer Kriging surrogate (MLKG) for the reliability analysis of VSV. The MLKG combines multiple Kriging surrogate models arranged in a hierarchical structure. By breaking the problem down into more minor problems, MLKG works by presenting each small problem as a Kriging model and reducing the input dimension of the sub-layer Kriging model. In this way, the MLKG can capture the complex interactions between the inputs and outputs of the problem while maintaining a high degree of accuracy and efficiency. This study proves the error propagation process of MLKG. To evaluate MLKG’s accuracy, we test it on two typical high-dimensional non-linearity functions (Rosenbrock and Michalewicz function). We compared MLKG with some contemporary KG surrogate modeling techniques using mean squared error (MSE) and R square (${R^2}$). Results show that MLKG achieves an excellent level of accuracy for reliability analysis in high-dimensional problems with a small number of sample points.

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.

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%.

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.

This paper presents the results of reverse-engineering (RE) strategies, surface roughness and computational fluid dynamics (CFD) modelling for a Wren100 micro gas turbine (MGT). Utilising silicone moulds and resin tooling, precise blade geometry capture was achieved for 3D reconstruction allowing for discrete and parametric geometric models to be created. Using these geometries, CFD simulations employing both Reynolds-averaged Navier–Stokes (RANS) and large eddy simulation (LES) models, alongside experimental wind tunnel cascade tests, were used to evaluate these reverse engineering strategies. The results show that while the parametric model captures overall MGT performance with fewer parameters, the discrete model provides enhanced accuracy, highlighting its suitability for detailed aerodynamic analyses. Contrary to initial expectations, surface roughness exhibited a noticeable impact on performance despite the lower Reynolds numbers (40,000), as demonstrated by the CFD model and wind tunnel experiments. The results indicate that surface roughness can reduce laminar separation bubbles on the blade leading edge, delay the onset of transition, and mitigate secondary flow losses. Overall, this study contributes to knowledge advancement in turbine blade reverse engineering and aerodynamics by detailing the impact of surface roughness on performance.

To meet the development needs of aeroengines for high thrust-to-weight ratios and fuel-air ratios, a high temperature rise triple-swirler main combustor was designed with a total fuel-air ratio of 0.037, utilising advanced technologies including staged combustion, multi-point injection and multi-inclined hole cooling. Fluent software was used to conduct numerical simulations under both takeoff and idle conditions, thereby obtaining the distribution characteristics of the velocity and temperature fields within the combustor, as well as the generation of pollutants. The simulation results indicate that under takeoff conditions, the high temperature rise triple-swirler combustor achieves a total pressure loss coefficient of less than 6% and a combustion efficiency exceeding 99%. Under takeoff conditions, the OTDF and RTDF values are 0.144 and 0.0738, respectively. The mole fraction of NOx emissions is 3,700ppm, while the mole fraction of soot emissions is 2.55×10−5ppm. Under idle conditions, the triple-swirler combustor maintains a total pressure loss coefficient of less than 6% and a combustion efficiency greater than 99.9%. The OTDF and RTDF values are 0.131 and 0.0624, respectively. The mole fractions of CO and UHC emissions are both 0×10−32ppm at the calculation limit of Fluent software.

A distributed cooperative guidance law without numerical singularities is proposed for the simultaneous attack a stationary target by multiple vehicles with field-of-view constraints. Firstly, the vehicle engagement motion model is transformed into a multi-agent model. Then, based on the state-constrained consensus protocol, a coordination control law with field-of-view (FOV) constraints is proposed. Finally, the cooperative guidance law has been improved to make it more suitable for practical application. Numerical simulations verified the effectiveness and robustness of the proposed guidance law in the presence of acceleration saturation, communication delays and measurement noise.

Contrails are a major contributor to the climate effect of aviation. Mitigation efforts and technological improvements aim to reduce the contrail climate effect. Many currently discussed innovations (like using sustainable aviation fuels (SAFs) or hydrogen) affect the physical processes and phenomena during contrail formation. Hence, understanding and analysing contrail formation is of great importance in the context of climate research. Ice crystal formation in a nascent contrail is completed within the first seconds after the engine exhaust is emitted. In the past, numerical models treating this early stage typically involved either a 3D or 0D approach. Whereas 3D models are computationally expensive, restricting the number of simulations that could be performed, less expensive 0D models allow to explore a larger parameter space but neglect plume heterogeneity and use a prescribed plume dilution. We present the new dynamical framework RadMod for contrail formation simulations that describes the evolution of a turbulent round jet emitted from an aircraft engine. Relative to large-eddy simulation (LES) or Reynolds-averaged Navier-Stokes (RANS) 3D models of contrail formation, our model is computationally less expensive, enabling extensive parameter studies. The model accounts for the mixing of the hot and moist exhaust air with the cold ambient air through the solution of the two-dimensional advection-diffusion equation of momentum, temperature, and water vapour. The validation of our model is conducted through comparisons with empirical relationships and CFD results. In the near future, this model will be combined with an existing microphysical model, resulting in a contrail formation model of intermediate complexity.

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.

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.

During the automatic docking assembly of aircraft wing-fuselage, using monocular camera or dual-camera to monitor the docking stage of the fork-ear will result in an incomplete identification of the fork-ear pose-position and an inaccurate description of the deviation in the intersection holes’ position coordinates. To address this, a quality inspection and error correction method is proposed for the fork-ear docking assembly based on multi-camera stereo vision. Initially, a multi-camera stereo vision detection system is established to inspect the quality of fork-ear docking assembly. Subsequently, a spatial position solution mathematical model of the fork-ear feature points is developed, and a spatial pose determination mathematical model of fork-ear is established by utilised the elliptical cone. Finally, an enhanced artificial fish swarm particle filter algorithm is proposed to track and estimate the coordinate of the fork-ear feature points. An adaptive weighted fusion algorithm is employed to fuse the detection data from the multi-camera and the laser tracker, and a wing pose-position fine-tuning error correction model is constructed. Experimental results demonstrate that the method enhances the effect of the assembly quality inspection and effectively improves the wing-fuselage docking assembly accuracy of the fork-ear type aircraft.

To investigate the flame acceleration to detonation in 2.0 and 0.5 mm planar glass combustion chambers, the experiments have been conducted utilising ethylene/oxygen mixtures at atmospheric pressure and temperature. The high-speed camera has been used to record the revolution of flame front and pressure inside the combustion chamber. Different equivalence ratios and ignition locations have been considered in the experiments. The results show that the detonation pressure in the 2 mm thick chamber is nearly three times of Chapman-Jouguet pressure, while detonation pressure in the 0.5 mm thick chamber is only 45.7% of the Chapman-Jouguet value at the stoichiometric mixture. This phenomenon is attributed to the larger pressure loss in the thinner chamber during the detonation propagation. As the value of equivalence ratio is 2.2, the detonation cannot be produced in the 2 mm thick chamber, while the detonation can be generated successfully in the 0.5 mm thick chamber. This phenomenon indicates that the deflagration is easily to be accelerated and transformed into the detonation, due to a larger wall friction and reflection. Besides, the micro-obstacle has been added into the combustor can shorten the detonation transition time and reduces the distance of the detonation transition.

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.