航天器微低重力模拟及试验技术

针对国内外不同类型的微低重力模拟机理、应用方法及特点进行了介绍。综述了基于气悬浮技术的多自由度模拟器的关键技术以及组合应用方法;对各种复杂航天器(包括大型空间机械臂)在微低重力模拟环境下进行的展开、编队、抓捕对接、分离以及在轨服务等典型试验应用进行了系统介绍,同时总结了针对宇航员模拟训练的微低重力环境的实现手段及其特点。最后,展望了微低重力模拟及试验技术的发展前景,并提出了多项亟待突破的关键技术。     

低温对涡轴发动机起动性能影响的试验与分析

为研究低温对涡轴发动机起动性能的影响,对国军标的适用与裁剪进行了讨论,开展了低温起动试验,试验以滑油箱内的滑油温度达到-34 ℃算起,冷浸4 h后进行起动,分析了低温起动过程的阻力矩、剩余扭矩、点火性能和温升效应对起动性能的影响。结果表明:-34 ℃条件下的初始阻力矩是25 ℃条件下的2.25倍,至点火转速附件阻力矩降低为1.53倍;温度越低,点火边界对应的索尔太平均直径(SMD)越小,燃烧室点火边界越窄;温升效应对低温起动性能的影响显著,考虑温升效应的起动时间延长约25%。热空气加温和起动滑油断油可以降低起动初始阻力矩,改善点火性能,从而提高了低温起动性能。研究结论对同类发动机开展低温起动试验、起动供油规律优化及相关研究提供了参考。      

Study on the resolution of multi-aircraft flight conflicts based on an IDQN

With the rapid growth of flight flow, the workload of controllers is increasing daily, and handling flight conflicts is the main workload. Therefore, it is necessary to provide more efficient conflict resolution decision-making support for controllers. Due to the limitations of existing methods, they have not been widely used. In this paper, a Deep Reinforcement Learning(DRL) algorithm is proposed to resolve multi-aircraft flight conflict with high solving efficiency. First, the characteristics ...     

微小型大气数据采集系统设计与实现

大气数据采集对飞行器自动控制具有重要的意义。根据系统实时性和小型化的要求,设计了一种微小型大气数据采集系统。该系统以TMS320F2812为控制器,采用高精度A/D转换器和均值滑动滤波的方法来提高测量精度;由于软件采用了μC/OS-II,大大简化了系统的管理、维护工作。该系统结构简单、体积小、成本低,试验结果表明该系统测量精度高,具有较高的实际应用价值。     

Review on ultra-lightweight flapping-wing nano air vehicles:Artificial muscles,flight control mechanism,and biomimetic wings

Flying insects are capable of flapping their wings to provide the required power and control forces for flight. A coordinated organizational system including muscles, wings, and control architecture plays a significant role, which provides the sources of inspiration for designing flapping-wing vehicles. In recent years, due to the development of micro-and meso-scale manufacturing technologies, advances in components technologies have directly led to a progress of smaller Flapping-Wing Nano Air V...     

Locally generalised multi-agent reinforcement learning for demand and capacity balancing with customised neural networks

Reinforcement Learning (RL) techniques are being studied to solve the Demand and Capacity Balancing (DCB) problems to fully exploit their computational performance. A locally generalised Multi-Agent Reinforcement Learning (MARL) for real-world DCB problems is proposed. The proposed method can deploy trained agents directly to unseen scenarios in a specific Air Traffic Flow Management (ATFM) region to quickly obtain a satisfactory solution. In this method, agents of all flights in a scenario form a multi-agent decision-making system based on partial observation. The trained agent with the customised neural network can be deployed directly on the corresponding flight, allowing it to solve the DCB problem jointly. A cooperation coefficient is introduced in the reward function, which is used to adjust the agent’s cooperation preference in a multi-agent system, thereby controlling the distribution of flight delay time allocation. A multi-iteration mechanism is designed for the DCB decision-making framework to deal with problems arising from non-stationarity in MARL and to ensure that all hotspots are eliminated. Experiments based on large-scale high-complexity real-world scenarios are conducted to verify the effectiveness and efficiency of the method. From a statistical point of view, it is proven that the proposed method is generalised within the scope of the flights and sectors of interest, and its optimisation performance outperforms the standard computer-assisted slot allocation and state-of-the-art RL-based DCB methods. The sensitivity analysis preliminarily reveals the effect of the cooperation coefficient on delay time allocation.     

Static magnetic field analysis of hollow-cup motor model and bow-shaped permanent magnet design

The hollow-cup Permanent Magnet (PM) motors have the characteristics of low power consumption, and are widely used in the aerospace field. At present, the tile-shaped PMs used by hollow-cup PM motors have poor sinusoidal characteristics of the air gap magnetic flux density waveform, which will cause torque ripple. The existing method for improving the air gap magnetic flux density waveform is not very effective when applied to hollow cup, a special motor with no stator core and large air gap. A bow-shaped PMs structure is designed for the hollow-cup motor in this paper. First, the equivalent surface current method is used to calculate the analytical formula of the static magnetic field of the model. Then, the Finite Element (FE) method is used to calculate the static air gap flux density waveform of conventional tile-shaped PMs and bow-shaped PMs with different bow heights, and the corresponding harmonics and sine distortion are obtained by Fourier decomposition. The simulation results show that the bow-shaped PMs can effectively improve the sinusoidal characteristics of the static air gap flux density waveform. And the suitable bow height is determined. Finally, a prototype is made based on the suitable bow height for experiments, and compared with the analytical result and the FE result, and the accuracy and effectiveness of the bow-shaped PMs with the suitable bow height are verified.     

Multi-scale simulation model of air system based on cross-dimensional data transmission method

The Secondary Air System (SAS) plays an important role in the safe operation and performance of aeroengines. The traditional 1D-3D coupling method loses information when used for secondary air systems, which affects the calculation accuracy. In this paper, a Cross-dimensional Data Transmission method (CDT) from 3D to 1D is proposed by introducing flow field uniformity into the data transmission. First, a uniformity index was established to quantify the flow field parameter distribution characteristics, and a uniformity index prediction model based on the locally weighted regression method (Lowess) was established to quickly obtain the flow field information. Then, an information selection criterion in 3D to 1D data transmission was established based on the Spearman rank correlation coefficient between the uniformity index and the accuracy of coupling calculation, and the calculation method was automatically determined according to the established criterion. Finally, a modified function was obtained by fitting the ratio of the 3D mass-average parameters to the analytical solution, which are then used to modify the selected parameters at the 1D-3D interface. Taking a typical disk cavity air system as an example, the results show that the calculation accuracy of the CDT method is greatly improved by a relative 53.88% compared with the traditional 1D-3D coupling method. Furthermore, the CDT method achieves a speedup of 2 to 3 orders of magnitude compared to the 3D calculation.     

复杂钛合金进气道热等静压近净成形技术研究

作为冲压发动机的进气装置，进气道是发动机的关键核心构件，也是一种复杂异形薄壁钛合金构件，成形难度非常大。以TA15钛合金粉末为原材料，利用热等静压近净成形技术在国际上首次研制成功进气道，实现了整体结构的一次成形，并成功通过飞行考核。从进气道本体取样，测试了不同位置的组织，结果表明：热等静压TA15钛合金不同位置组织均匀性好，主要以板条状或片层状α相为主，在粉末颗粒边界大应变带周围分布着等轴α相，相间分布少量的细小β相。测试了材料各项性能，其平均室温抗拉强度、屈服强度、伸长率、断面收缩率、500℃抗拉强度、断裂韧性和冲击韧性分别为995MPa、924MPa、18.2%、43%、673MPa、90.6MPa·m1/2和51.4J/cm2 ，各项性能数据均达到了GJB2744A-2007中规定的TA15钛合金锻件的水平，综合性能良好。