基于神经网络的预膜雾化模型

为了实现对预膜雾化质量的快速预估，基于神经网络建立了以结构参数和工况参数为输入,SMD值为输出的预膜雾化模型。使用试验数据训练和测试网络模型,结果显示,模型在较宽的工作范围内具有较高的精度和较好的泛化能力。SMD预测值随输入参数的变化规律符合试验结论,可作为给定工况参数下预膜式雾化装置的结构参数优化依据。神经网络能够较好地学习预膜雾化过程中的隐含规律。随着供油压差的增大,预膜器逐渐出现阻雾化效应,导致其雾化效果比单喷嘴和直混式雾化均差。     

Comparison Structure Forms Between Isogrid and Orthogrid of C/ E CompositeTrellis Wound Structure Based on Calculation of Load Carrying

This paper calculated load carrying of isogrid and orthogrid of carbon epoxy composite trellis wound
structure (C/ E CTWS) using non linear finite element method. Based on the analysis, test cases were designed and
tests of axial compression were carried. Analysis result and test result fit well. In order to be used in the project, this
kind of structure cut out repairing was calculated. The method presented in this paper has been proved and can be used
to solve complicated engineering problems. According to calculations and experimental results combined with applica
tion, a principle of choosing wound structure is obtained and principle could be applied to engineering.
     

An intelligent approach for flight risk prediction under icing conditions

Flight risk prediction is significant in improving the flight crew’s situational awareness because it allows them to adopt appropriate operation strategies to prevent risk expansion caused by abnormal conditions, especially aircraft icing conditions. The flight risk space representing the nonlinear mapping relations between risk degree and the three-dimensional commanded vector(commanded airspeed, commanded bank angle, and commanded vertical velocity) is developed to provide the crew with practi...     

一种舱段快速连接结构设计及承载能力分析

设计了一种新型的舱段间连接装置，分析了其在轴向力载荷作用下的受力情况，并以相对滑动作为失效判据给出了预紧力的计算方法，在此基础上分析了卡箍倾角、摩擦系数以及预紧力等对该结构承载能力的影响。研究结果表明：直径为1 200 mm的连接结构能够满足1 000 kN 轴拉载荷下的使用要求。卡箍与壳体配合面倾角、摩擦系数以及预紧力等均会对该连接结构的承载能力产生影响，其中预紧力的影响主要表现为预紧力增大，卡箍与上下壳体对接面的压力增大，产生的摩擦力增大，因此其轴向承载能力增大。此外，随着配合面倾角增大以及摩擦系数的减小，则会导致该连接装置承载能力产生显著下降。     

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.     

An air-rail inter-modal strategy for aircraft recovery

It is common that airlines encounter a disruption of a flight schedule, which is mainly caused by resource shortages. In case of a disruption, subject to scarce resources, most of airlines lose flexibility of performing aircraft recovery on the basis of business interest priorities and need to delay, swap, and cancel flights. This paper proposes an air-rail inter-modal strategy to incorporate a High-Speed Rail(HSR) transport mode into an aviation network for aircraft recovery. The air-rail inter...     

基于多层次特征的高分影像海岸带地物分类

针对高分辨率影像地物光谱丰富复杂的问题，文章提出了一种结合像元-对象-空间格局特征的水域、盐田等海岸带精细地物分类方法。首先基于像元和空间格局特征分别利用遗传算法优化随机森林参数进行分类；其次将两种分类结果采用D-S证据理论融合；然后基于不同地物斑块的空间上下文信息，采用粒子群算法优化支持向量机（Support Vector Machine，SVM）参数实现面向对象的二次分类。为验证方法的有效性，收集山东省莱州湾海岸带附近区域的“高分二号”卫星影像，开展了水域及水利设施用地、盐田、工矿用地、交通运输用地、住宅用地、沿海滩涂、海域与耕地8类地物的分类实验，总体精度达到97.21%，Kappa系数为0.964 2。实验结果表明，文章提出的高分影像海岸带地物分类方法兼顾像元、对象及空间格局特征优点，能够实现多层次细致分类，并同时兼具较短的训练时长与较高的分类精度。该研究成果可为中国海岸带生态环境监测与土地利用规划提供一定技术支撑。     

载人航天器太阳翼多姿态输出能力建模及分析

载人航天器太阳翼在轨运行期间除正常对日定向转动外，根据飞行任务要求可能需要工作在α轴水平归零或垂直归零等特殊状态。在特殊工作模式下，太阳入射角和太阳翼的输出能力变化曲线更加复杂。建立太阳入射角与轨道角、太阳高度角、β轴转角等变量的数学模型，分析太阳入射角的变化规律，并结合光照区时长，建立太阳翼在轨输出能力的预测模型。与实际飞行数据相比较，表明该模型可较为准确地评估特殊工作模式下太阳翼的输出能力，可用于在轨整舱能量平衡分析，为飞行任务计划安排提供参考。     

基于SAN构建高可用实时存储系统

介绍SAN网络存储技术及其拓扑结构,针对某飞控中心数据存储系统的实际需求,设计和实现一个SAN存储结构上的高可用实时可扩展集群存储方案,并详细描述通过软、硬件结合实现冗余数据路径、故障切换、实时存储和查询的方法。     

Performance improvement of licklider transmission protocol in complex deep space networks based on parameter optimization

A reasonable parameter configuration helps improve the data transmission performance of the Licklider Transmission Protocol (LTP). Previous research has focused mainly on parameter optimization for LTP in simplified scenarios with one to two hops or multihop scenarios with a custody mechanism of the Bundle Protocol (BP). However, the research results are not applicable to communications in Complex Deep Space Networks (CDSNs) without the custody mechanism of BP that are more suitable for deep space communications with LTP. In this paper, we propose a model of file delivery time for LTP in CDSNs. Based on the model, we propose a Parameter Optimization Design Algorithm for LTP (LTP-PODA) of configuring reasonable parameters for LTP. The results show that the accuracy of the proposed model is at least 6.47% higher than that of the previously established models based on simple scenarios, and the proposed model is more suitable for CDSNs. Moreover, the LTP parameters are optimized by the LTP-PODA algorithm to obtain an optimization plan. Configuring the optimization plan for LTP improves the protocol transmission performance by at least 18.77% compared with configuring the other parameter configuration plans.