To investigate the downstream rim seal gas ingestion characteristics of a 1.5-stage turbine, the URANS equations were solved numerically using the SST turbulence model. The effects of different purge flow rates and the second vane on the ingestion characteristics of the aft cavity and the nonuniform fluctuations of the main gas path pressure are analysed. The results showed that the aft cavity is affected by the combined effects of the blade and the second vane, and the potential field at the leading edge of the second vane greatly influence the airflow variation in the aft cavity, which enhances the ingress of the mainstream into the wheel-space. The front purge flow weakens the egress between the suction side of the blade and the suction side of the second vane. The potential field at the leading edge of the second vane suppresses the nonuniform distribution of airflow in the aft cavity caused by the rotational effect of the blade.

This study presents a methodology to estimate the battery consumption of an electric powerplant, based on brushless motors, typically used in light unmanned aerial systems. The methodology models brushless motors through an equivalent circuit obtained from their dynamic behaviour. Propellers’ data are taken from an experimental database. Furthermore, a variable speed controller efficiency is considered in the methodology. All the parameters involved in the model are adjusted by minimising the mean quadratic error of measurements taken in both direct and alternating currents. This model allows designers to predict energy consumption, also if any element of the powerplant changes, such as battery or propeller. Thus, it is useful for selecting the best powerplant for an actual RPAS operation. The results obtained to predict the current consumption of several electric powerplants show a coefficient of determination higher than 0.96. Finally, the methodology is validated by means of a case study of an actual RPAS, where the best powerplant is selected in terms of endurance.

Single pilot passenger aircraft concepts are being developed by several manufacturers. Various technological approaches are being explored: One concept is to use a Harbour Pilot dedicated to providing support for departures and arrivals. The Harbour Pilot has comprehensive knowledge of the terminal area airspace, procedures and operations. If a single pilot aircraft is to be viable, however, the number of supporting personnel needs to be significantly smaller than the number of First Officers normally employed for a two-crew aeroplane, but the number such staff has yet to be determined. This study models operations by a UK low-cost operator at a regional airport to determine the optimum number of Harbour Pilots required to support operations throughout the day. The model uses a simplified timeline analysis with task data incorporated into a dynamic discrete event modelling system allowing for multiple replications using various configurations. Results suggest that for this operation six Harbour Pilots per shift used flexibly to support both departures and arrivals would be required.

In recent years, Performance Based Logistics (PBL) has been increasingly used to reduce the product lifecycle cost. As a result, the existing logistics analysis methods need to be reassessed due to the difference in PBL from the classical approach. This study considers the Spare Parts Allocation (SPA) and Level of Repair Analysis (LORA), which are the most commonly used problems within PBL, and are the subject of analysis. A comprehensive, multi-objective simulation-optimisation model is developed for a military aircraft operations case study, with the objectives of minimising total cost and maximising total flight hours. The Design of Experiment (DOE) method is used for determining simulation-optimisation parameters. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used for the first time in order to select the best design points. Simulated Annealing (SA) was used for multi-objective optimisation with the SPA model being solved first. Then the LORA problem was added to this model as a decision variable and the effects of the integrated solution (SPA+LORA) were examined. The results show that the integrated solution yields remarkably better results in terms of flight hours and cost when compared to the SPA optimisation approach alone. Moreover, the proposed model provides a profit-centric approach and can be efficiently used as a decision support tool for both customers and suppliers for difficult and complex logistics support activities.

In tandem with the fast-growing demand for Unmanned Aerial Vehicles (UAVs) for surveillance and reconnaissance, advanced controllers for these critical systems are needed. This paper proposes a flight dynamics controller design that considers various uncertainties for the Hydra Technologies UAS-S4 Ehécatl. In order to be realistic, in addition to flight dynamics nonlinearities, three main sources of uncertainties are considered, as those caused by unknown controller’s parameters, modeling errors, and external disturbances. A Robust adaptive fuzzy logic controller is designed, in charge of nonlinear flight dynamics in presence of a variety of uncertainties. The nonlinear flight dynamics is modeled based on the Takagi-Sugeno method relying on the soft association of local linear models. Since this controller is model-based, an optimal reference model is defined, which is stabilised by the Linear Quadratic Regulator procedure. A fuzzy logic controller is then designed for the nonlinear model. Lastly, with the aim to handle the uncertainties, the gains of the fuzzy controller are reconfigured, and are continuously adjusted by Lyapunov-based robust adaptive laws. The performance of the UAS-S4 Robust adaptive fuzzy logic controller is evaluated in terms of lateral and longitudinal flight dynamics stabilisation, and the reference model state variables tracking under various uncertainties.

The tip leakage flow generates a large amount of aerodynamic losses in a zero inlet swirl turbine rotor (ZISTR), which directly uses the axial exit flow downstream of a combustion chamber without any nozzles. To reduce the tip leakage flow loss and improve the efficiency for the ZISTR, a front suction side winglet is employed on the blade tip, and the effect of winglet width is numerically investigated to explore its design space. It is found that, a suction side leading edge horseshoe vortex (SHV) on the blade tip plays a crucial role in mitigating the tip leakage flow loss. This SHV rotates in the reverse direction to the leakage vortex, so it tends to break the formation of the leakage vortex near the front part of suction side. With a larger winglet width, the SHV stays longer time on the blade tip and leaves it at a further downstream location. This increases the time and the contact area of the interaction between the SHV and the leakage vortex, so the leakage vortex is further weakened. Thus, the tip leakage flow loss is reduced, and the efficiency is improved. However, a larger winglet width also increases the heat load of the blade due to a larger blade surface area. The ZISTR designed with the winglet width equal to 2.1% blade pitch achieves a great trade-off between efficiency and heat load that the efficiency is improved by 0.85% at an expense of 1.2% increment of the heat load. Besides, for the blade using this winglet, the mechanical stress due to the centrifugal, aerodynamic and thermal load is acceptable for the engine application. This investigation indicates a great potential in the improvement of efficiency for the ZISTR using a blade tip winglet designed on the front suction side.

In this paper, the prediction of the unsteady flow field over typical high aspect ratio (AR) wings in the transonic flow regime but below the sonic Mach number is of interest. The methodology adopted is a computational approach based on the transonic small disturbance unsteady potential equation. It is shown that the higher AR wings generally have a higher lift coefficient as well as a higher lift-to-drag ratio. With NASA’s common research model (CRM) wing, there is an increase in maximum lift with increasing AR while the induced drag is almost the same. There is also an optimum sweep angle, which is different for each angle-of-attack so that variable sweep lifting surfaces may be designed to provide optimum solutions. The computed flutter speeds indicate an expected reduction with increasing AR.

The main purpose of this study was to combine the currently separate objectives of aerodynamic performance and manufacturing efficiency, then find an optimal point of operation for both objectives. An additional goal of the study was to explore the effects of changes in design features, the position of the spars, and analyse how the changes influenced the optimal operating conditions. A machine-learning approach was taken to combine and model the gathered aero-manufacturing data, and a multi-objective optimisation approach utilising genetic algorithms was implemented to find the trade-off relationship between optimal target objectives (mission performance and manufacturability). The main achievements and findings of the study were: The study was a success in building a machine-learning model for the combined aero-manufacturing data utilising software library XGBoost; multi-objective optimisation, which did not include spar positions as a variable found the trade-off region between high manufacturability and high mission performance, with choices that offered reasonably high values of both; there was no clearly identified correlation between a small change in spar position and the target objectives; multi-objective optimisation with spar positions resulted in a trade-off relationship between target objectives, which was different from the trade-off relationship found in optimisation without spar positions; multi-objective optimisation with spar positions also offered more flexibility in the choice of manufacturing processes available for a given design; and the range of bump amplitudes for solutions found by multi-objective-optimisation with spar positions was lower and more focused than those found by optimisation without spar positions.

Intense acoustic loads from jet noise cause noise pollution and induce failures, such as the malfunctioning of electronic devices and fatigue failure of internal/external structures. Consequently, the prediction of jet noise characteristics is crucial in the development of high-speed vehicles. This study presents acoustic experiments and predictions for an under-expanded, unheated jet using a small-scale prototype. Outdoor measurements are carried out using a vertical ejection setup. Acoustic characteristics are measured using both linear and circular microphone arrays. Additionally, numerical prediction of the same jet noise is performed using a detached eddy simulation and the permeable Ffowcs-Williams and Hawkings acoustic analogy. The vertical experimental setup exhibits the typical acoustic characteristics of a supersonic jet in terms of directivity and broadband shock-associated noise. Moreover, the numerical prediction exhibits satisfactory accuracy for the jet downstream, where the large-scale turbulence structures of the directivity predominate. However, discrepancy increases in the domain of lower directivity. The presented experiment and prediction will be extended to future studies regarding the noise of various deflector duct configurations impinging on supersonic jets.

Weapon target allocation (WTA) is an effective method to solve the battlefield fire optimisation problem, which plays an important role in intelligent automated decision-making. We researched the multitarget allocation problem to maximise the attack effectiveness when multiple interceptors cooperatively attack multiple ground targets. Firstly, an effective and reasonable fitness function is established, based on the situation between the interceptors and targets, by comprehensively considering the relative range, relative angle, speed, capture probability and radiation source matching performance and thoroughly evaluating them based on the advantage of the attack effectiveness. Secondly, the optimisation performance of the particle swarm optimisation (PSO) algorithm is adaptively improved. We propose an adaptive simulated annealing-particle swarm optimisation (SA-PSO) algorithm by introducing the simulated annealing algorithm into the adaptive PSO algorithm. The proposed algorithm can enhance the convergence speed and overcome the disadvantage of the PSO algorithm easily falling into a local extreme point. Finally, a simulation example is performed in a scenario where ten interceptors cooperate to attack eight ground targets; comparative experiments are conducted between the adaptive SA-PSO algorithm and PSO algorithm. The simulation results indicate that the proposed adaptive SA-PSO algorithm demonstrates great performance in convergence speed and global optimisation capabilities, and a maximised attack effectiveness can be guaranteed.

The rotorcraft is a complex dynamical system that demands specialist modelling skills, and a high level of understanding of the aeromechanics arising from the main rotor wake and aerodynamic couplings. One such example is the difficulty predicting off-axis responses, particularly in hover and low-speed flight, associated with induced velocity variation through the rotor disk resulting from the rotor wake distortions. Various approaches have been developed to deal with this phenomenon but usually demand prerequisites of high levels of expertise and profound aerodynamic knowledge. This paper presents a new and practical approach to capturing this wake distortion through an augmented rotor inflow model. The proposed model is coupled with a nonlinear simulation using the FLIGHTLAB environment, and comparisons are made between the simulation results and flight test data from the National Research Council of Canada’s Advanced System Research Aircraft in hover and low speed. Results show good predictability of the proposed nonlinear model structure, demonstrated by its capability to closely match the time responses to multi-step control inputs from flight test. The results reported are part of ongoing research at Liverpool and Cranfield University into rotorcraft simulation fidelity.

The aim of this paper is to provide preliminary results on a traffic coordination framework based on stochastic task allocation. General trends and the predicted advent of personal aerial vehicles increase traffic rapidly, but current air traffic management methods admittedly cannot scale appropriately. A hierarchical system is proposed to overcome the problem, the middle layer of which is elaborated in this paper. This layer aims to enable stochastic control of traffic behaviour using a single parameter, which is achieved by applying distributed stochastic task allocation. The task allocation algorithm is used to allocate speeds to vehicles in a scalable way. By regulating the speed distribution of vehicles the conflict rates remain manageable. Multi-agent simulation results show that it is possible to control ensemble dynamics and together with that traffic safety and throughput via a single parameter. Using transient simulations the dynamic performance of the system is analysed. It is shown that the traffic conflict reduction problem can be transformed into a control design problem. The performance of a simple controller is also evaluated. It was shown that by applying the controller, quicker transients can be achieved for the mean speed of the system.

This paper presents the extension and validation of omni-failure envelopes for first-ply failure (FPF) and last-ply failure (LPF) analysis of advanced composite materials under general three-dimensional (3D) stress states. Phenomenological failure criteria based on invariant structural tensors are implemented to address failure events in multidirectional laminates using the “omni strain failure envelope” concept. This concept enables the generation of safe predictions of FPF and LPF of composite laminates, providing reliable and fast laminate failure indications that can be particularly useful as a design tool for conceptual and preliminary design of composite structures. The proposed extended omni strain failure envelopes allow not only identification of the controlling plies for FPF and LPF, but also of the controlling failure modes. FPF/LPF surfaces for general 3D stress states can be obtained using only the material properties extracted from the unidirectional (UD) material, and can predict membrane FPF or LPF of any laminate independently of lay-up, while considering the effect of out-of-plane stresses. The predictions of the LPF envelopes and surfaces are compared with experimental data on multidirectional laminates from the first and second World-Wide Failure Exercise (WWFE), showing a satisfactory agreement and validating the conservative character of omni-failure envelopes also in the presence of high levels of triaxiality.

The cooperative guidance problem of multiple inferior missiles intercepting a hypersonic target with the specific impact angle constraint in the two-dimensional plane is addressed in this paper, taking into consideration variations in a missile’s speed. The guidance law is designed with two subsystems: the direction of line-of-sight (LOS) and the direction of normal to LOS. In the direction of LOS, by applying the algebraic graph theory and the consensus theory, the guidance command is designed to make the system convergent in a finite time to satisfy the goal of cooperative interception. In the direction of normal to LOS, the impact angle is constrained to transform into the LOS angle at the time of interception. In view of the difficulty of measuring unknown target acceleration information in real scenarios, the guidance command is designed by utilising a super-twisting algorithm based on a nonsingular fast-terminal sliding mode (NFTSM) surface. Numerical simulation results manifest that the proposed guidance law performs efficiently and the guidance commands are free of chattering. In addition, the overall performance of this guidance law is assessed with Monte Carlo runs in the presence of measurement errors. The simulation results demonstrate that the robustness can be guaranteed, and that overall efficiency and accuracy in intercepting the hypersonic target are achieved.

In this paper, we expolore Multi-Agent Reinforcement Learning (MARL) methods for unmanned aerial vehicle (UAV) cluster. Considering that the current UAV cluster is still in the program control stage, the fully autonomous and intelligent cooperative combat has not been realised. In order to realise the autonomous planning of the UAV cluster according to the changing environment and cooperate with each other to complete the combat goal, we propose a new MARL framework. It adopts the policy of centralised training with decentralised execution, and uses Actor-Critic network to select the execution action and then to make the corresponding evaluation. The new algorithm makes three key improvements on the basis of Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm. The first is to improve learning framework; it makes the calculated Q value more accurate. The second is to add collision avoidance setting, which can increase the operational safety factor. And the third is to adjust reward mechanism; it can effectively improve the cluster’s cooperative ability. Then the improved MADDPG algorithm is tested by performing two conventional combat missions. The simulation results show that the learning efficiency is obviously improved, and the operational safety factor is further increased compared with the previous algorithm.

A smart morphing winglet driven by piezoelectric Macro Fiber Composite (MFC) is designed to adjust cant angle autonomously for various flight conditions. The smart morphing winglet is composed of the MFC actuator, DC-DC converter, power supply, winglet part and wing part. A hinge is designed to transfer the bending deformation of intelligent MFC bending actuator to rotation of the winglet structure so as to achieve the adaptive cant angle. Experimental and numerical work are conducted to evaluate the performance of smart morphing winglet. It is demonstrated that the proposed intelligent MFC bending actuator has an excellent bending performance and load resistance. This smart morphing winglet exhibits the excellent characteristic of flexibility on large deformation and lightweight. Moreover, a series of wind tunnel tests are performed, which demonstrate that the winglet driven by intelligent MFC bending actuator produces sufficient deformation in various wind speed. At high wind speed, the cant angle of the winglet can reach 16 degrees, which is still considered to be very useful for improving the aerodynamic performance of the aircraft. The aerodynamic characteristics are investigated by wind tunnel tests with various attack angles. As a result, when the morphing winglet is actuated, the lift-to-drag ratio could vary up to 11.9% and 6.4%, respectively, under wind speeds of 5.4 and 8.5m/s. Meanwhile, different flight phases such as take-off, cruise and landing are considered to improve aerodynamic performance by adjusting the cant angle of winglet. The smart morphing winglet varies the aerofoil autonomously by controlling the low winglet device input voltage to remain optimal aerodynamic performance during the flight process. It demonstrates the feasibility of piezoelectric composites driving intelligent aircraft.

In order to intercept a highly manoeuvering target with an ideal impact angle in the three-dimensional space, this paper promises to probe into the problem of three-dimensional terminal guidance. With the goal of the highly target acceleration and short terminal guidance time, a guidance law, based on the advanced fast non-singular terminal sliding mode theory, is designed to quickly converge the line-of-sight (LOS) angle and the LOS angular rate within a finite time. In the design process, the target acceleration is regarded as an unknown boundary external disturbance of the guidance system, and the RBF neural network is used to estimate it. In order to improve the estimation accuracy of RBF neural network and accelerate its convergence, the parameters of RBF neural network are adjusted online in real time. At the same time, an adaptive law is designed to compensate the estimation error of the RBF neural network, which improves the convergence speed of the guidance system. Theoretical analysis demonstrates that the state and the sliding manifold of the guidance system converge in finite time. According to Lyapunov theory, the stability of the system can be guaranteed by online adjusting the parameters of RBF neural network and adaptive parameters. The numerical simulation results verify the effectiveness and superiority of the proposed guidance law.

This article focuses on the aerodynamic design of a morphing aerofoil at cruise conditions using computational fluid dynamics (CFD). The morphing aerofoil has been analysed at a Mach number of 0.8 and Reynolds number of $3 \times 10^{6}$, which represents the transonic cruise speed of a commercial aircraft. In this research, the NACA0012 aerofoil has been identified as the baseline aerofoil where the analysis has been performed under steady conditions at a range of angles of attack between $0^{^{\kern1pt\circ}}$ and $3.86^{^{\kern1pt\circ}}$. The performance of the baseline case has been compared to the morphing aerofoil for different morphing deflections ($w_{te}/c = [0.005 - 0.1]$) and start of the morphing locations ($x_{s}/c = [0.65 - 0.80]$). Further, the location of the shock wave on the upper surface has also been investigated due to concerns about the structural integrity of the morphing part of the aerofoil. Based upon this investigation, a most favourable morphed geometry has been presented that offers both, a significant increase in the lift-to-drag ratio against its un-morphed counterpart and has a shock location upstream of the start of the morphing part.