期望状态序列导向的深空探测器规划修复方法

Aiming at the challenges caused by the persistence, concurrency and energy consumption of probe actions, a plan repair method of deep space probe based on the expected state sequence is proposed. In this method, the expected state sequence is formed of the expected effect of the unfinished action and the expected precondition of the unexecuted action in the pre designed plan, according to the execution status of the action. The expected state sequence is an ordered set of states with mixed logic and energy, providing subgoals for plan repair and also transforming the plan repair problem into the state transition path searching problem. During the search, the plan repair strategy with energy supply priority is proposed, which separates the logic repair from energy repair to reduce the difficulty of solving the problem. And this method enables the probe to recover from plan failure autonomously. Finally, the effectiveness and rationality of the proposed method are verified through simulation by taking the Mars Orbiter as an example.     

Injection of 40-kHz-modulated electron beam from the satellite: II. Excitation of electrostatic and whistler waves

Beam-plasma interaction effects are studied during the active space experiment with electron and Xe-ion beam injections in an ionospheric plasma. Permanent 40-kHz-modulated electron beam injection occurs simultaneously with a xenon-ion beam injected by the Hall-type plasma thruster operating in a square-pulse mode (100/50 s for a job/pause duration). The unusual behavior of the background charged particle fluxes and wave activity stimulated during the beam-plasma interaction have been registered by the scientific instruments onboard Intercosmos-25 station (IK-25) and Magion-3 subsatellite. The longitudinal and electromagnetic wave instabilities and their mutual relationship are considered in order to explain the observed effects. The excitation of electrostatic waves by the electron injection has been considered for different resonance conditions near the linear stability boundary. Beam-driven electromagnetic instability is responsible for the backward-propagating whistler waves excited via cyclotron resonance. Competition of these two beam instabilities is one of the subjects of the present study.     

Energy requirements of a thermally processed ISRU radiation shield for a lunar habitat

The purpose of this study was to establish, on a first principles basis, the order of magnitude of energy requirements for a thermally processed, lunar regolith radiation shield constructed using an in-situ resource utilisation (ISRU) approach. This was done by developing a reference scenario habitat and using thermodynamic relationships and specific heat capacity expressions to determine the energy required to bring such a regolith volume up to sintering temperatures (c. 1,375 K). Once the energy requirements were developed some power system architectures were outlined conceptually and a nuclear power plant of c. 400 kW was suggested as a means to supply the necessary energy. This is well beyond current space nuclear applications. The study concludes that it is likely that the most efficient near-term solution is chemical processing of regolith, from an energy requirements perspective. The technology is also more mature and likely to be delivered on near term projects as it does not require such scaled-up power system architectures. Alternatively, bringing storm shelters up with the habitat to provide a means of weathering major solar events, and adding additional radiation protection to habitat quarters, possibly through a water blanket or similar mechanism, could provide a non-ISRU solution with current technology. However, in the longer term, the development of MW-scale power system architectures (fission, solar etc.), may permit a very large volume of material to be processed thermally for construction material, making a large, permanent human presence on the Moon more easily realisable.     

月球表层采样样品智能确认方法

表层采样是月球采样探测的重要方式，样品智能确认有助于提升工作效率与复杂问题处理能力。结合月球表层采样铲挖工作过程，分析了铲挖过程中臂载相机图像的特点，模仿有人参与识别过程，提出了层次解耦的月球样品智能识别流程，利用深度学习方法构建了一类深度卷积识别网络，完整地描述了图像、特征、标记在网络中的正反传递关系，并在月球表层采样地面试验中进行了验证，结果表明该方法对不同光照、不同背景、不同过程、不同形态的样品，具有较好的泛化识别能力，误识别率优于8.1%，平均单幅识别时间约0.7 s。     

Application of a PCA-DBN-based surrogate model to robust aerodynamic design optimization

An efficient method employing a Principal Component Analysis (PCA)-Deep Belief Network (DBN)-based surrogate model is developed for robust aerodynamic design optimization in this study. In order to reduce the number of design variables for aerodynamic optimizations, the PCA technique is implemented to the geometric parameters obtained by parameterization method. For the purpose of predicting aerodynamic parameters, the DBN model is established with the reduced design variables as input and the aerodynamic parameters as output, and it is trained using the k-step contrastive divergence algorithm. The established PCA-DBN-based surrogate model is validated through predicting lift-to-drag ratios of a set of airfoils, and the results indicate that the PCA-DBN-based surrogate model is reliable and obtains more accurate predictions than three other surrogate models. Then the efficient optimization method is established by embedding the PCA-DBN-based surrogate model into an improved Particle Swarm Optimization (PSO) framework, and applied to the robust aerodynamic design optimizations of Natural Laminar Flow (NLF) airfoil and transonic wing. The optimization results indicate that the PCA-DBN-based surrogate model works very well as a prediction model in the robust optimization processes of both NLF airfoil and transonic wing. By employing the PCA-DBN-based surrogate model, the developed efficient method improves the optimization efficiency obviously.     

Stall flutter prediction based on multi-layer GRU neural network

The modeling of dynamic stall aerodynamics is essential to stall flutter, due to the flow separation in a large-amplitude pitching oscillation process. A newly neural network based Reduced Order Model (ROM) framework for predicting the aerodynamic forces of an airfoil undergoing large-amplitude pitching oscillation at various velocities is presented in this work. First, the dynamic stall aerodynamics is calculated by solving RANS equations and the transitional SST-γ model. Afterwards, the stall flutter bifurcation behavior is calculated by the above CFD solver coupled with structural dynamic equation. The critical flutter speed and limit-cycle oscillation amplitudes are consistent with those obtained by experiments. A newly multi-layer Gated Recurrent Unit (GRU) neural network based ROM is constructed to accelerate the calculation of aerodynamic forces. The training and validation process are carried out upon the unsteady aerodynamic data obtained by the proposed CFD method. The well-trained ROM is then coupled with the structure equation at a specific velocity, the Limit-Cycle Oscillation (LCO) of stall flutter under this flow condition is predicted precisely and more quickly. In order to predict both the critical flutter velocity and LCO amplitudes after bifurcation at different velocities, a new ROM with GRU neural network considering the variation of flow velocities is developed. The stall flutter results predicted by ROM agree well with the CFD ones at different velocities. Finally, a brief sensitivity analysis of two structural parameters of ROM is carried out. It infers the potential of the presented modeling method to depict the nonlinearity of dynamic stall and stall flutter phenomenon.     

Collaborative image compression and classification with multi-task learning for visual Internet of Things

Widespread deployment of the Internet of Things(Io T) has changed the way that network services are developed, deployed, and operated. Most onboard advanced Io T devices are equipped with visual sensors that form the so-called visual Io T. Typically, the sender would compress images, and then through the communication network, the receiver would decode images, and then analyze the images for applications. However, image compression and semantic inference are generally conducted separately, and t...     

载人空间站概念

空间站与其它航天器相比,有很多优越性。文内详细地阐述了空间站的四大特征:①先入轨后上人,既提高了安全保障,又简化了研制过程;②具有自主补给消耗品、检修和更换设备的能力;③具有长期航天的素质;④具有可变更和可扩大其功能的性质。这些特征及其优越性,充分体现了空间站在未来载人航天活动中的地位和作用。     

载人航天中高温应急的医学对策

载人航天中高温应急事件发生概率较高,应予以充分重视。首先应该克服某些消极认识和不适做法,并指出高温负荷对工效的影响,可转而续发其它事故或未能完成预定飞行计划等问题。文中根据航天实际,提出了若干与高温耐力有关的选训措施和设想,侧重论述了最大氧摄取量（ＶＯ２ｍａｘ）与耐热能力的关系。认为可以采用心功能适应指数与ＶＯ２ｍａｘ的测定作为指标,选拔潜在耐热能力较高的航天员,并在此基础上安排某些体能训练,进一步提高耐热能力,达到在万一发生情况时避免发生事故,圆满完成任务的目的。     

深远空连续推进动力与施图林格解的解析

针对太阳系远深距离的探测将是人类下一阶段深空探测活动的主要目标。这一目标的实现依赖于探测器连续推进动力技术的突破。从描述连续常值推力下太空飞行的施图林格解出发,对其中反映的深远空飞行任务有效载荷比、任务时间、飞行距离等关键参数与发动机性能之间的关系进行了深入分析。给出了在特定任务时长、特定飞行距离要求下发动机比冲、功率需要满足的条件及其对有效载荷比、最终飞行速度等指标的影响。此外,基于二体轨道动力学对太阳系行星探测的大椭圆转移轨道和转移能量进行了推导,并对连续推力的太阳帆任务方案涉及的关键技术指标做了理论性的计算。这些结论是对深空探测连续推力方案基础理论的归纳,可以为我国未来开展深远空探测活动提供重要的启发和指导。