面向林火持续侦察的多无人机分布式控制方法

为解决目前面向林火持续侦察多无人机（UAV）协同控制实用性与自主性不足的问题，基于蔓延速度诱导元胞自动机（SVICA）林火蔓延算法、无人机与传感器建模，构建了较为真实的三维多无人机火场侦察仿真环境与侦察效能指标，提出了一种面向林火持续侦察的多无人机双层分布式控制架构，在行动层基于强化学习训练的人工神经网络（ANN），实现了有风条件下无人机自主火场环绕与地形跟随功能，在策略层设计通过时域均匀分布算法进行各无人机空速的离散自主调节，最终达到多无人机林火持续侦察时域分布的均匀性与即时性目的。通过一系列数值仿真实验，验证了所提出的无人机分布控制策略在无人机损失和补充突发情况下的自适应性。基于无人机数量与侦察效能指标关系的实验与研究，定义了无人机出动阈值并验证了无人机长时间出动回收策略。最终实验结果表明，针对林火持续侦察任务，所提出的多无人机分布式控制方法具备一定的有效性与实用性。     

Adaptive optimization methodology based on Kriging modeling and a trust region method

Surrogate-Based Optimization (SBO) is becoming increasingly popular since it can remarkably reduce the computational cost for design optimizations based on high-fidelity and expensive numerical analyses. However, for complicated optimization problems with a large design space, many design variables, and strong nonlinearity, SBO converges slowly and shows imperfection in local exploitation. This paper proposes a trust region method within the framework of an SBO process based on the Kriging model. In each refinement cycle, new samples are selected by a certain design of experiment method within a variable design space, which is sequentially updated by the trust region method. A multi-dimensional trust-region radius is proposed to improve the adaptability of the developed methodology. Further, the scale factor and the limit factor of the trust region are studied to evaluate their effects on the optimization process. Thereafter, different SBO methods using error-based exploration, prediction-based exploitation, refinement based on the expected improvement function, a hybrid refinement strategy, and the developed trust-region-based refinement are utilized in four analytical tests. Further, the developed optimization methodology is employed in the drag minimization of an RAE2822 airfoil. Results indicate that it has better robustness and local exploitation capability in comparison with those of other SBO methods.     

Experimental comparison between aircraft fuel tank inerting processes using NEA and MIG

Fuel tank inerting technologies are able to reduce the fire risk by injection of inert gas into the ullage or fuel, the former called ullage washing and the latter fuel scrubbing. The Green On-Board Inert Gas Generation System (GOBIGGS) is a novel technology based on flameless catalytic combustion, and owning to its simple structure and high inerting efficiency, it has received a lot of attentions. The inert gas in the GOBIGGS is mainly comprised of CO₂, N₂, and O₂ (hereinafter, Mixed Inert Gas (MIG)), while that in the On-Board Inert Gas Generation System (OBIGGS), which is one of the most widely used fuel tank inerting technologies, is Nitrogen-Enriched Air (NEA). The solubility of CO₂ is nearly 20 times higher than that of N₂ in jet fuels, so the inerting capability and performance are definitely disparate if the inert gas is selected as NEA or MIG. An inerting test bench was constructed to compare the inerting capabilities between NEA and MIG. Experimental results reveal that, if ullage washing is adopted, the variations of oxygen concentrations on the ullage and in the fuel are nearly identical no matter the inert gas is NEA or MIG. However, the ullage and dissolved oxygen concentrations of MIG scrubbing are always higher than those of NEA scrubbing.     

空域拥挤风险管理时间决策模型与方法

针对目前日益严重的空域拥挤现象,缺乏有效的空域拥挤风险管理机制,造成拥挤难以应对等问题,建立了空域拥挤风险预测模型、空域拥挤风险解决模型和风险损失成本模型。采用风险预测模型和解决模型预测可能产生空域拥挤的时段、提出不同时段的实施流量管理策略,基于风险损失成本模型给出了不同时段调整拥挤的运行成本,通过比较运行成本和空域拥挤风险管理决策方法确定出解决空域拥挤的最佳时间点。采用实际运行数据进行验证,结果表明:所建立的空域拥挤预测模型、空域拥挤风险解决模型、风险损失成本模型和空域拥挤风险管理时间决策方法能有效地预测未来空域发生拥挤的时段,迅速找到运行成本最小的调整拥挤的时间点,为空中交通流量动态管理提供了新途径。     

A novel signal processing approach for LEO space debris based on a fence-type space surveillance radar system

The increase in space debris can seriously threaten regular activities in the Low Earth Orbit (LEO) environment. Therefore, it is necessary to develop robust, efficient and reliable techniques to understand the potential motions of the LEO debris. In this paper, we propose a novel signal processing approach to detect and estimate the motions of LEO space debris that is based on a fence-type space surveillance radar system. Because of the sparse distribution of the orbiting debris through the fence in our observations, we formulate the signal detection and the motion parameter estimation as a sparse signal reconstruction problem with respect to an over-complete dictionary. Moreover, we propose a new scheme to reduce the size of the original over-complete dictionary without the loss of the important information. This new scheme is based on a careful analysis of the relations between the acceleration and the directions of arrival for the corresponding LEO space debris. Our simulation results show that the proposed approach can achieve extremely good performance in terms of the accuracy for detection and estimation. Furthermore, our simulation results demonstrate the robustness of the approach in scenarios with a low Signal-to-Noise Ratio (SNR) and the super-resolution properties. We hope our signal processing approach can stimulate further work on monitoring LEO space debris.     

Co-registration of Chang’E-1 stereo images and laser altimeter data with crossover adjustment and image sensor model refinement

Topographic information is of fundamental importance for various scientific investigations in lunar and planetary exploration. To provide high-precision, seamless mapping capability, it is critical to co-register image and altimetry data, the two major data sources for topographic modeling. This paper presents a method for co-registration of Chang’E-1 (CE-1) stereo images and laser altimeter (LAM) data with crossover adjustment and refinement of the image sensor model. The crossover adjustment is tested in a larger area (0–60°N, 50–0°W); the image refinement and co-registration with LAM data are tested in an area (46.2–50.0°N, 31.8–28.8°W) within the larger area. Experimental results demonstrate that this co-registration reduces the mean differences of inconsistency from more than 200 m to just 3.21 m in the Z direction of object space. In image space, the mean errors of homologous points both in the column and row directions are reduced to below 0.1 pixel. This indicates that the proposed crossover adjustment of LAM data and refinement of the CE-1 stereo image model can effectively improve co-registration of the two data sets.     

CET4听力测试对英语教学的反拨效应

反拨效应是指测试对其相应教学产生的影响。在借鉴国内外相关研究的基础上,以高职高专学生参加CET4为例,通过问卷调查研究受试者对四级听力的态度,以及四级听力对受试者学习策略和学习内容的反拨效应。     

直升机金属结构缺陷容限验证技术研究

直升机结构的缺陷容限验证在FAR／CCAR27／29．571条适航条款中有明确的要求。文章提出了全尺寸结构缺陷容限验证思路，对验证的各个环节，包含缺陷的类型及参数、缺陷容限特性曲线基本参数及安全系数、真实缺陷下载荷或应力的修正、结构的缺陷容限性能、检查周期的确定等进行了探讨，为开展直升机结构缺陷容限验证工作提供了技术支持。     

Nostoc sphaeroides Kützing,an excellent candidate producer for CELSS

Some phytoplankton can be regarded as possible candidates in the establishment of Controlled Ecological Life Support System (CELSS) for some intrinsic characteristics, the first characteristic is that they should grow rapidly, secondly, they should be able to endure some stress factors and develop some corresponding adaptive strategies; also it is very important that they could provide food rich in nutritious protein and vitamins for the crew; the last but not the least is they can also fulfill the other main functions of CELSS, including supplying oxygen, removing carbon dioxide and recycling the metabolic waste. According to these characteristics, Nostoc sphaeroides, a potential healthy food in China, was selected as the potential producer in CELSS. It was found that the oxygen average evolution rate of this algae is about 150 μmol O₂ mg⁻¹ h⁻¹, and the size of them are ranged from 2 to 20 mm. Also it can be cultured with high population density, which indicated that the potential productivity of Nostoc sphaeroides is higher than other algae in limited volume. We measured the nutrient contents of the cyanobacterium and concluded it was a good food for the crew. Based on above advantages, Nostoc sphaeroides was assumed to a suitable phytoplankton for the establishment of Controlled Ecological Life Support System. We plan to develop suitable bioreactor with the cyanobacterium for supplying oxygen and food in future space missions.     

涡扇发动机空中减速过程转速预测

以某型涡扇发动机为研究对象,对其空中减速的试验数据进行深度挖掘,分析了减速过程中低压和高压转速的变化规律,得到该型发动机空中减速过程中转速的预测关系式,并对预测结果进行验证。结果表明,通过预测关系式计算所得结果与飞行试验数据吻合良好,可用作该型发动机空中减速过程的转速预测。