电帆推进在等离子体环境下推力影响因素分析和试验研究

为了分析电帆推力的影响因素，根据电帆推进原理设计了电帆地面模拟装置。首先分析了真空中带电导线和等离子作用机理，得出了电帆推力公式。利用朗缪尔探针测量了电帆模拟试验环境中等离子体参数，计算产生推力的大小，最后通过微推力测量系统测量电帆产生的推力，与计算结果进行了对比。根据推力公式和仿真结果表明，提高电压、增加带电粒子密度和速度、增加电帆长度均可增加推力。在试验中电帆上电压从300V增加到800V时，推力从9μN增加到26μN。仿真和试验结果表明，电压、带电粒子密度和速度、电帆导线长度都对推力有影响。根据试验结果，电帆推力公式的经验推力系数在1～2取值。     

Developing a novel radial ultrasonic vibration-assisted grinding device and evaluating its performance in machining PTMCs

Particle-reinforcing titanium matrix composites(PTMCs) exhibit the sharp raising applications in modern industries owing to its extraordinary physical and mechanical properties. However, the poor grindability and unstable grinding processes due to the existence of TiC particles and TiB short fibres inside PTMCs, leading to the sudden grinding burn and low material removal rate.In this work, a novel radial ultrasonic vibration-assisted grinding(RUVAG) device with a special cross structure was dev...     

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.     

Grain erosion wear properties and grinding performance of porous aggregated cubic boron nitride abrasive wheels

Cubic boron nitride (cBN) superabrasive grinding wheels exhibit unique advantages in the grinding of difficult-to-cut materials with high strength and toughness, such as titanium alloys and superalloys. However, grinding with multilayered metallic cBN superabrasive wheels faces problems in terms of grain wear resistance, the chip storage capability of the working layers and the stability and controllability of the dressing process. Therefore, in this work, novel metallic cBN superabrasive wheels with aggregated cBN (AcBN) grains and open pore structures were fabricated to improve machining efficiency and surface quality. Prior to the grinding trials, the air-borne abrasive blasting process was conducted and the abrasive blasting parameters were optimized in view of wear properties of cBN grains and metallic matrix materials. Subsequently, the comparative experiments were performed and then the variations in grinding force and force ratio, grinding temperature, tool wear morphology and ground surface quality of the multilayered AcBN grinding wheels were investigated during machining Ti–6Al–4V alloys. In consideration of the variations of grain erosion wear volume and material removal rate per unit of pure metallic matrix materials as the abrasive blasting parameters changes, the optimal abrasive blasting parameters were identified as the SiC abrasive mesh size of 60# and the abrasive blasting distance and time of 60 mm and 15 s, respectively. The as-developed AcBN grains exhibited better fracture toughness and impact resistance than monocrystalline cBN (McBN) grains because of the existence of metal-bonded materials amongst multiple cBN particles that decreased crack propagation inside whole grains. The metallic porous AcBN wheels had lower grinding forces and temperature and better ground surface quality than vitrified McBN wheels due to the constant layer-by-layer exposure of cBN particles in the working layer of AcBN wheels.     

FY-2C星地面应用分系统指令与数据获取站

介绍了风云二号(FY-2)C星地面应用分系统数据与指令接收站(CDAS)的主要技术指标、工作流程,以及与C星的星地接口与地面应用分系统其他部分的接口.说明了CDAS的天伺馈、信道、图像获取(IAS)、三点测距(TRRR)、数据收集(DCP)、遥测遥控(TT&C)、卫星模拟器、标校、时间统-、低速信息传输(LRIT)信息编码与发送等子系统的组成与功能.阐述了C星CDAS的设计原则,以及用群调技术实现DCP的数据解调、用扩频伪码进行TRRR定位、图像处理、TT&C增加图形化界面控制、正交相移键控(QPSK)解调器抗长连"1"功能等关键技术.在轨测试和试运行期间,C星的CDAS不仅解决暴露的问题,而且进行适应性调整.验收前测试结果表明,其功能及技术指标满足业务运行要求,设备工作正常、性能稳定.