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.

The turbine vane bears higher and higher temperature of upstream flow with the higher requirements for the engine thrust. The heat resistance of turbine vanes is a severe problem for the lifetime of turbine vanes. Therefore, it is essential to study the flow field and heat transfer of the vane to find better ways to improve the heat resistance of the turbine and increase the thrust of the engine. To improve the efficiency of the turbine vanes, the present paper conducted researches on the heat transfer and the pressure loss of turbine vanes under different radius ratio of swirl and hot streak. The numerical applies CFD 3D RANs solver with the SST turbulent model to get the influence of non-uniform inflow velocity and temperature distribution on turbine vanes. The present numerical model utilizes turbine vane C3X. Considering the viscosity of the fluid causes shear stress on the wall, the paper set the boundary layers mesh in the numerical model. The size of the first boundary layer mesh is 10–6 m. The results show that the hot fluid on the suction side migrates towards the hub, and the hot fluid on the pressure side migrates towards the shroud while there are coupling effect of the swirl and hot streak. The larger the radius ratio of the hot streak and the swirl (RHS) is, the higher the temperature of the local high-temperature regions exist on the suction side of leading edge and the pressure side of the trailing edge is, and the higher the pressure loss is.

This paper proposes an optimization-based computational approach to design multi-rate observers for linear models of aerospace systems with asynchronous measurements. A case study on the estimation of the state of an autonomous quadrotor UAV around its hovering operating point will be used as an example of the applicability of the proposed method. There are two theoretical contributions of the proposed method. The first is the derivation of a set of Linear Matrix Inequalities (LMIs) for the design of linear observers yielding convergence of the state estimation error given the maximum allowable sampling period (MASP) for each sensor. The second contribution is to propose an optimization problem subject to LMIs for finding the MASPs that guarantee exponential stability of the estimation error. The two contributions enable the analysis and design of multi-rate observers for systems with linear models, including quadrotor UAVs around a hovering operating point. The examples show a very intuitive result: as the sampling frequency of one sensor decreases, another sensor must sample faster to guarantee convergence of the estimated state to the real state. Simulations of a quadrotor with 12 states and 9 measurements show the effectiveness of the approach.

Aiming at the non-uniform strain in the welding of airship skin, this paper studies the traditional digital image correlation algorithm, optimizes the shape and size of the subset, and presents an adaptive subset algorithm. Under the premise of ensuring a substantially constant subset area, the modified algorithm uses the initial u and v values to optimize the shape of the subset, find the optimal aspect ratio. Besides, the modified digital image correlation dynamically adjusts the shape of the subset according to the threshold value, making the algorithm better applicable to non-uniform deformation and large deformation. As the results show, in the simulation experiment, under the different strains such as 1000 μɛ, 5000 μɛ, and 9000 μɛ, the standard error measured by the modified method is reduced to more than 50% compared with the traditional method. Meanwhile, during the real speckle experiment, the error in the modified digital image correlation algorithm was reduced from 9.3e−04 to 7.2e−04. Furthermore, the modified digital image correlation only costs 3% more time, has a little effect on computational efficiency. Therefore, the modified method can smooth the measured strain, and make the robustness and accuracy better during the airship skin measurement.

At the present situation composite material, particularly laminate type systems are becoming increasingly important in civil aviation due to their strength and weight characteristics. However, the effectiveness of these materials depends on the rational usage of its mechanical properties. There is an optimal fiber angle in the case of ply stacking and optimal ply thickness. Both manipulations reveal the variability of composite features. This work is carried out about the optimization of aircraft structure elements. Optimization issues will cover both constituents. The process will be dividing into stages, and the most factors affecting the final result will be considered with a sight to the two main criteria (strength and weight). Using the structure diagram scheme of a vertical stabilizer, an analysis was carried out and an algorithm was developed that allows finding optimum in the structure depending on the specific loads. The optimization issues have been laid by ply stacking and thickness. Complex analysis and algorithm simplicity of the program code makes it possible to use the advantages of composite materials which showed significant weight superiority in comparison with metal analogues.

In this paper, the formation control problem of a second-order unmanned aerial vehicle swarm system with switching topology and collision/obstacle avoidance has been studied. First, the linear consensus protocol for formation control with switching topology is designed using graph theory. The conditions for information consensus are given. Second, the problem of collision/obstacle avoidance is also considered. And the consensus protocol with switching topology and collision/obstacle avoidance is proposed. The improved artificial potential approach is applied to realize collision/obstacle avoidance, which can avoid potential fields falling into the local minimum. Third, system stability under the proposed protocol is proved using the Lyapunov theory. Finally, numerical simulations are presented to demonstrate the effectiveness of the proposed protocol.

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.