To phased microphone array for sound source localization, algorithm with both high computational efficiency and high precision is a persistent pursuit until now. In this paper, convolutional neural network (CNN) a kind of deep learning is preliminarily applied as a new algorithm. The input of CNN is only cross-spectral matrix, while the output of CNN is source distribution. With regard to computing speed in applications, CNN once trained is as fast as conventional beamforming, and is significantly faster than the most famous deconvolution algorithm DAMAS. With regard to measurement accuracy in applications, at high frequency, CNN can reconstruct the sound localizations with up to 100% test accuracy, although sidelobes may appear in some situations. In addition, CNN has a spatial resolution nearly as that of DAMAS and better than that of the conventional beamforming. CNN test accuracy decreases with frequency decreasing; however, in most incorrect samples, CNN results are not far away from the correct results. This exciting result means that CNN perfectly finds source distribution directly from cross-spectral matrix without given propagation function and microphone positions in advance, and thus, CNN deserves to be further explored as a new algorithm.

The landing of a civil transport aircraft is one of the most critical phases due to parametric uncertainties and strong crosswind conditions. In this paper, separate controllers are designed for longitudinal and lateral-directional channels for the landing phase, which is divided into the final approach, flare, and decrab. A multivariable model reference adaptive control scheme is implemented with state feedback for output tracking. The safety and flight performance of the autolanding control system are demonstrated through Monte Carlo simulations of a nonlinear civil transport aircraft model.

Supercooled large droplet (SLD), which can cause run-back ridged ice, will affect the aerodynamic performance of aircraft and poses a serious threat to aircraft safety. However, there is little knowledge about the abnormal run-back icing mechanism, which is vital for the development of aircraft anti-icing technologies. The flow and freezing of supercooled droplet impinging on inclined surface can help us better understand the run-back icing of SLD, especially the coupling of water flow and phase change in the freezing process. This paper experimentally investigates the freezing behavior of supercooled water droplet impinging on inclined surface. By observing the processes of water flow, ice formation and growth with a high-speed camera, the overflow distance and the freezing time are recorded with different temperatures. Different from previous discoveries that droplet freezes as the form of two smaller droplets on an inclined surface, we found two new frozen morphologies under the condition of short nucleation time: ellipse and slender strip, when the supercooling is high and low, respectively. The overflow distance and freezing time will increase with the decrease of ice growth rate, when supercooling decreases. And the freezing time will increase dramatically when the supercooling is low enough. Finally, the mechanism of run-back freezing of droplet based on the nucleation and icing evolution is discussed. Droplet impact on the inclined surface will result in large overflow distance when it nucleates after its retraction stage.

In turbomachinery, the effect of cooling injection on the over-tip leakage (OTL) flow has been the focus. In the present work, the flow and heat transfer on the blade tip surfaces of two typical different tip structures including a flat tip and a squealer tip are investigated. The grid independence verification and turbulence model validation (including Shear Stress Transport k–ω model and Spalart–Allmaras model) are conducted. Numerical results are compared with the existing experimental results. It is found that there exists the shock wave near the corner of the pressure side, and a striped high-pressure coefficient region appears on the tip surface near the pressure side. The cooling injection could alter the range of high striped pressure coefficient region. The tip leakage vortex (TLV) was formed by the blending between the OTL flow and mainstream, causing a large aerodynamic penalty. In comparison, the flat tip shows a greater loss near the casing and the tip surface than the squealer tip. An interesting observation is that the coolant ejecting from the cooling jet hole bifurcates and then forms a counter-rotating vortex pair (CRVP) for both the flat tip and the squealer tip, which greatly changes the flow structures and heat transfer characteristics within the tip region. The branches of the CRVP cause the thermal stripes on the surfaces of blade tip and the suction side rim. The present results reveal the cooling injection has a strong effect on OTL flow and enlighten the design and optimization of blade tips.

When helicopter is climbing from the ground or flying close to a solid surface, the flow around the lifting rotor can be strongly affected such that it will become time varying. To control the helicopter when the ground effect presents, a fast and accurate simulation technique is required. Traditional finite state inflow model with ground effect still need numerical integration since it cannot directly give prediction below the disk, and the computation of wake is necessary due to its interaction with ground. To improve the efficiency of the model, the adjoint theorem is adopted such that the wake can be solved with closed form equations. The result in hover condition is validated with Hayden model which is correlated well with the experimental data.

Avionics system integration is a prominent trend in research and development of civil airplane. It can improve task effectiveness, function efficiency, and resource utilization of system. Information fusion, which includes function information fusion, processing information fusion, and sensor input fusion, is a core process of avionics system integration. Some researches about the impact of information fusion on system safety are done in avionics system which is shown as follows: (1) the concept of Mishap Dilution, Mishap Implication and Mishap Confusion (MD–MI–MC) is first defined in function information fusion of avionics system. (2) The model of multi-source MD–MI–MC is established based on hazard theory. (3) The function fusion of Automatic-Dependent Surveillance–Broadcast (ADS–B) and Traffic Collision Avoidance System (TCAS) is used as a typical example to analyze fusion system during the aircraft climbing or landing state. In this paper, the concept and model of multi-source MD–MI–MC are proposed for safety analysis of integrated avionics system. A fusion model with a variable sampling Variational Bayesian–Interacting Multiple Model (VSVB–IMM) algorithm is used to analyze. At last, a set of theory system and evaluation standards including the positive and negative earning analyses are built based on the presented MD–MI–MC theory and mechanism of integrated avionics.

For low-cost unmanned aerial vehicles, it is practically important to estimate flight height using the measurements from low-cost accelerometer and barometer sensors. In this paper, we propose a simple two-step strategy to fuse the measurements from the two sensors. In the first step, two different filters, moving average filter and Kalman filter, are adopted to pre-process the measurements from accelerometer and barometer, respectively. In the second step, a properly designed complementary filter is employed for high-precision height estimation. Several experimental comparison results on a small-size quadrotor demonstrate the effectiveness of the strategy. The strategy is further combined with a simple height controller to yield a height feedback-control scheme. The closed-loop experimental results show that 8-cm and 20-cm control accuracies are achieved for 5-m- and 10-m-height tracking tasks, respectively.

Increasing the environmental sustainability of aviation is a key design goal for commercial aircraft for the foreseeable future. From the perspective of structural engineering, this is accomplished through reducing the mass of aircraft components and structures. Advanced manufacturing techniques offer new avenues for design, enabling more complex structures which can have highly tailored properties. One advanced manufacturing concept is the use of 3D printed polymer preforms that are coated with nanocrystalline metal through electrodeposition. This enables the use of high-performance materials in virtually any geometry. To exploit this manufacturing approach, it is incumbent to have well-established mechanical models of the behavior of such hybrid structures. In particular, hybrid polymer–nanometal structures tend to fail due to compressive instabilities. This paper describes a model of local shell buckling, a typical compressive instability, as it applies to hybrid polymer–nanometal structures. The analysis depends upon the Southwell stress function model for radially loaded solids of rotation, and couples this with the Timoshenko analysis of local shell buckling. This combination is applicable to a range of practical configurations for truss-like hybrid structures.

The control problem for linearised three-dimensional perturbations about a nominal laminar boundary layer over a flat plate (the Blasius profile) is considered. With a view to preventing the laminar to turbulent transition, appropriate inputs, outputs, and feedback controllers are synthesised that can be used to stabilise the system. The linearised Navier–Stokes equations are reduced to the Orr–Sommerfeld and Squire equations with wall-normal velocity actuation entering through the boundary conditions on the wall. An analysis of the work-energy balance is used to identify an appropriate sensor output that leads to a passive system for certain values of the streamwise and spanwise wavenumbers. Even when the system is unstable, it is demonstrated that strictly positive real feedback can stabilise this system using the special output.

This paper investigates the flocking and obstacle avoidance problem of multi-quadrotor system with a lattice-type structure. To tackle nonlinear dynamics and cooperative consensus of a swarm of quadrotors, we proposed two algorithms (one for free flocking and one for constrained flocking) based on artificial potential field with two cooperative strategies using position tracking and attitude tracking, respectively. Firstly, the inner-loop control model of single quadrotor is provided. Then, we build an artificial potential function to act on the coordinate variable. Third, obstacle avoidance term is added to the flocking algorithm proposed previously. Finally, the position and attitude are taken as the coordinate variables, respectively, to both two algorithms, one for optimizing the distance of each quadrotor until the lattice-type structure is formed and keeping continuously and another for optimizing the distance between quadrotor and obstacles to avoid collision. Simulation results demonstrate the validity of both algorithms.