The number of unmanned aerial vehicles (UAVs, also known as drones) has increased dramatically in the airspace worldwide for tasks such as surveillance, reconnaissance, shipping and delivery. However, a small number of them, acting maliciously, can raise many security risks. Recent Artificial Intelligence (AI) capabilities for object detection can be very useful for the identification and classification of drones flying in the airspace and, in particular, are a good solution against malicious drones. A number of counter-drone solutions are being developed, but the cost of drone detection ground systems can also be very high, depending on the number of sensors deployed and powerful fusion algorithms. We propose a low-cost counter-drone solution composed uniquely by a guard-drone that should be able to detect, locate and eliminate any malicious drone. In this paper, a state-of-the-art object detection algorithm is used to train the system to detect drones. Three existing object detection models are improved by transfer learning and tested for real-time drone detection. Training is done with a new dataset of drone images, constructed automatically from a very realistic flight simulator. While flying, the guard-drone captures random images of the area, while at the same time, a malicious drone is flying too. The drone images are auto-labelled using the location and attitude information available in the simulator for both drones. The world coordinates for the malicious drone position must then be projected into image pixel coordinates. The training and test results show a minimum accuracy improvement of 22% with respect to state-of-the-art object detection models, representing promising results that enable a step towards the construction of a fully autonomous counter-drone system.

This paper presents the design, manufacturing and experimental assessment of a morphing element consisting of a composite corrugated panel that hosts a diffused actuation system based on Shape Memory Alloy (SMA) actuators. The characterisation of the SMA actuators is reported and the system performance is predicted through an analytical model and finite element analyses. Two versions of the actuated system are proposed, with different methods for the physical integration of the SMA wires into the composite part. Manufacturing and testing of specimens with different wire densities are reported. Correlation with experiments validates the analytical and numerical approaches adopted for the design and analyses. The results confirm the potential of the concept proposed for developing corrugated panels that can be contracted in a predefined direction by a load-bearing actuation system, but still retain high stiffness and strength properties in other directions.

This paper presents a performance analysis on a novel engine concept, currently under development, in order to achieve hybrid air-breathing rocket technology. A component-level approach has been developed to simulate the performance of the engine at Mach 5, and the thermodynamic interaction of the different working fluids has been analysed. The bypass ramjet duct has also been included in the model. This facilitates the improved evaluation of performance parameters. The impact of ram drag induced by the intake of the engine has also been demonstrated. The whole model is introduced into a multi-platform application for aeroengine simulation to make it accessible to the interested reader. Results show that the bypass duct modelling increases the overall efficiency by approximately 7%. The model calculates the specific impulse at approximately 1800 seconds, which is 4 times higher than any chemical rocket.

This study investigates and proposes a fire detection and suppression system for a smart air cargo container. A series of smoke spread and fire evolution numerical models are executed to assess the performance of container-based fire detection in various fire scenarios. This is to identify the worst case and optimise the location and threshold setting of fire detection sensors, achieving the shortest detection time. It is found that the fire detection threshold (reduction in light transmission = 12%/ft) for a container-based system can be set at three times the standard activation threshold for a cargo-based fire detection system, which can reduce the number of false alarms by three orders of magnitude. Moreover, effectiveness analysis of passive fire protection for the glass fibre-reinforced polymer-made smart container indicates an allowable leakage size of 0.01m2. The risk of internal overpressure has been found to be negligible for the leakage size required by aircraft pressure equalisation.

An unusual philosophical approach is proposed here to decarbonise larger civil aircraft that fly long ranges and consume a large fraction of civil aviation fuel. These inject an important amount of carbon emissions into the atmosphere, and holistic decarbonising solutions must consider this sector. A philosophical–analytical investigation is reported here on the feasibility of an airliner family to fly over long ranges and assist in the elimination of carbon dioxide emissions from civil aviation.

Backed by state-of-the-art correlations and engine performance integration analytical tools, a family of large airliners is proposed based on the development and integration of the body of a very large two-deck four-engine airliner with the engines, wings and flight control surfaces of a very long-range twin widebody jet. The proposal is for a derivative design and not a retrofit. This derivative design may enable a swifter entry to service.

The main contribution of this study is a philosophical one: a carefully evaluated aircraft family that appears to have very good potential for first-generation hydrogen-fuelled airliners using gas turbine engines for propulsion. This family offers three variants: a 380-passenger aircraft with a range of 3,300nm, a 330-passenger aircraft with a range of 4,800nm and a 230-passenger aircraft with a range of 5,500nm. The latter range is crucially important because it permits travel from anywhere in the globe to anywhere else with only one stop. The jet engine of choice is a 450kN high-bypass turbofan.

Multi-dimensional aerodynamic database technology is widely used, but its model often has the curse of dimensionality. In order to solve this problem, we need projection to reduce the dimension. In addition, due to the lack of traditional method, we have improved the traditional flow field reconstruction method based on artificial neural networks, and we proposed an array neural network method.

In this paper, a set of flow field data for the target problem of the fixed Mach number is obtained by the existing CFD method. Then we arrange all the sampled flow field data into a matrix and use proper orthogonal decomposition (POD) to reduce the dimension, whose size is determined by the first few modals of energy. Therefore, significantly reduced data are obtained. Then we use an arrayed neural network to map the flow field data of simplified target problem and the flow field characteristics. Finally, the unknown flow field data can be effectively predicted through the flow field characteristic and the trained array neural network.

At the end of this paper, the effectiveness of the method is verified by airfoil flow fields. The calculation results show that the array neural network can reconstruct the flow field of the target problem more accurately than the traditional method, and its convergence speed is significantly faster. In addition, for the case of high angle flow field, the array neural network also performs well. There are no obvious jumps, and huge errors are found in results. In general, the proposed method is better than the traditional method.

The potential to recover waste heat from the exhaust gases of a turboprop engine and produce useful work through an Organic Rankine Cycle (ORC) is investigated. A thermodynamic analysis of the engine’s Brayton cycle is derived to determine the heat source available for exploitation. The aim is to use the aircraft engine fuel as the working fluid of the organic Rankine cycle in order to reduce the extra weight of the waste heat recovery system and keep the thrust-to-weight ratio as high as possible. A surrogate fuel with thermophysical properties similar to aviation gas turbine fuel is used for the ORC simulation. The evaporator design as well as the weight minimisation and safety of the suggested application are the most crucial aspects determining the feasibility of the proposed concept. The results show that there is potential in the exhaust gases to produce up to 50kW of power, corresponding to a 10.1% improvement of the overall thermal efficiency of the engine.

This paper provides a solution to the active vibration control of a microsatellite with two solar panels. At first, the microsatellite is processed as a finite element model containing a rigid body and two flexible bodies, according to the principles of mechanics, and that the dynamic characteristics are solved by modal analysis. Secondly, the equation involving vibration control is established according to the finite element calculation results. There are several actuators composed of macro fibre composite on the two solar panels for outputting control force. Furthermore, the control voltage for driving actuator is calculated by using fuzzy algorithm. It is clear that the smart structure consists of the flexible bodies and actuators. Finally, the closed-loop control simulation for suppressing harmful vibration is established. The simulation results illustrate that the responses to the external excitation are decreased significantly after adopting fuzzy control.