智能赋能流体力学展望

人工智能（AI）是21世纪的前沿科技,流体力学如何在智能化时代焕发青春是值得本领域研究者思考的话题。从智能赋能流体力学角度,就其研究内涵、研究内容、近期研究及难点进行了总结,并对智能流体力学未来的发展进行了展望。研究指出,流体力学计算或试验中所产生的数据是天生的大数据,如何通过深度神经网络、随机森林、强化学习等机器学习方法来利用这些数据,缓解甚至替代理论和方法层面对人脑的依赖,挖掘新的知识,成为一种新的研究范式;相关研究将涵盖流动控制方程的机器学习、湍流模型的机器学习、物理量纲分析与标度的智能化以及数值模拟方法的智能化;借助人工智能技术,发展流动信息特征提取与多源数据融合的智能化是流体力学发展的迫切需求;研究内容应至少涵盖海量数据挖掘方法以及多源气动数据的智能融合;发展数据驱动的流体力学多学科、多物理场耦合建模与控制是工程应用的迫切需求,相关工作涉及多场耦合建模、气动外形智能优化设计以及流动智能自适应控制等方面。     

数据分发用户协议模型研究

通过分析某型号卫星用户地面链路的实际应用情况,结合互联网应用协议模型,面向系统未来发展需要,提出了数据分发用户协议模型,分析了协议模型的层次关系,介绍了协议模型的具体工作过程,并对其工程可行性进行了分析,解决了地面链路连接管理以及应用负载分配的应用问题,在一定程度上避免了系统安全隐患,为系统实际工程应用提供了切实可行的途径。     

The possibilities of polar meteorology,environmental remote sensing,communications and space weather applications from Artificial Lagrange Orbit

The ability to observe meteorological events in the polar regions of the Earth from satellite celebrated an anniversary, with the launch of TIROS-I in a pseudo-polar orbit on 1 April 1960. Yet, after 50 years, polar orbiting satellites are still the best view of the polar regions of the Earth. The luxuries of geostationary satellite orbit including rapid scan operations, feature tracking, and atmospheric motion vectors (or cloud drift winds), are enjoyed only by the middle and tropical latitudes or perhaps only cover the deep polar regions in the case of satellite derived winds from polar orbit. The prospect of a solar sailing satellite system in an Artificial Lagrange Orbit (ALO, also known as “pole sitters”) offers the opportunity for polar environmental remote sensing, communications, forecasting and space weather monitoring. While there are other orbital possibilities to achieve this goal, an ALO satellite system offers one of the best analogs to the geostationary satellite system for routine polar latitude observations.     

某自动测试系统神经网络故障诊断模块设计与实现

阐述了自动测试系统中故障诊断的重要性,详述了诊断的流程.以某型防空导弹自动驾驶仪为例,首先利用LabVIEW中的MATLAB脚本节点,分别以BP和RBF神经网络为算法编写故障诊断函数;然后用LabVIEW开发故障诊断模块界面,最后将TabVIEW和神经网络两者的优势结合实现自动驾驶仪的故障诊断.实验仿真结果表明:模块设...     

Nighttime cloud properties retrieval using MODIS and artificial neural networks

In this work a methodology for inferring water cloud macro and microphysical properties from nighttime MODIS imagery is developed. This method is based on the inversion of a theoretical radiative transfer model that simulates the radiances detected in each of the sensor infrared bands. To accomplish this inversion, an operational technique based on Artificial Neural Networks (ANNs) is proposed, whose main characteristic is the ability to retrieve cloud properties much faster than conventional methods. Furthermore, a detailed study of input data is performed to avoid different sources of errors that appear in several MODIS infrared channels. Finally, results of applying the proposed method are compared with in-situ measurements carried out during the DYCOMS-II field experiment.     

Autonomous navigation of formation flying spacecrafts in deep space exploration and communication by hybrid navigation utilizing neural network filter

Autonomous navigation of spacecrafts is a difficult task, however, which is a must in future deep space exploration. With multiple spacecrafts flying in space, this aim can be achieved by formation flying spacecraft (FFS) utilizing inverse time difference of arrival (ITDOA) and inverse difference Doppler (IDD) methods, which can locate the position of earth-station from one-way uplink signals in the FFS coordinate, and by way of conversion of coordinates, the position of FFS is achieved in earth-centered earth-fixed (ECEF) coordinate. The ability of neural network (NN) filter in navigation to extract position of spacecrafts from random measuring noise of signal arrival time and Doppler shift is studied with different radius of FFS and surveying parameters. The NN filter used by spacecraft group is new way of unidirectional autonomous navigation and is of high precision of hybrid navigation.     

网络营销和传统营销的差异分析与整合

网络营销是随着计算机和网络技术的发展,在传统营销的基础之上发展起来的一种营销模式,是企业营销战略中的一部分。通过网络营销和传统营销的差异的分析,阐述了网络营销对传统营销的冲击,并提出只有网络营销和传统营销进行整合,优势互补,才能更好的促销营销市场的发展和完善。     

基于时空结构的卫星智能诊断模型研究

针对卫星这类复杂系统的故障诊断,提出了基于时空结构的智能故障诊断系统模型(iFDS),从系统结构,结构模型,推理机制、流程模型等方面进行论述,通过对各种故障诊断方法进行融合,实现了卫星系统网络化、个性化、远程并行诊断的智能故障诊断.在故障推理机制研究中,将故障分为系统故障、多发故障和单元故障3类,分别对每一类故障提出相应的智能故障推理方法.     

运载火箭测发控网络设计

运载火箭测试发射控制系统对数据处理能力、数据通信能力的要求越来越高。本文采用最新的网络通信技术,结合CZ-3A运载火箭测发控网络的实际设计需求和设计原则,概要介绍了运载火箭测发控网络的特点,着重从测发控网络的拓扑结构、双网卡捆绑技术、静态路由技术等五方面详细阐述了测发控网络的设计,最后通过测发控网络的功能测试验证了该设计的可靠性和先进性。     

基于身份的空间网络安全研究

空间网络安全的研究是天地一体化网络研究的重要组成部分,日益受到研究人员的重视。本文根据空间网络面临的安全威胁,分析需要采用的安全机制,构建了空间网络的安全体系结构。深入分析基于身份的密码体制（IBC）,在空间网络中应用IBC提供安全服务框架,以此为基础,提出了一种密钥交换协议,并详细描述了安全通信的建立过程。分析表明,同传统的基于公钥基础设施（PKI）体制的安全解决方案相比,IBC具有较低的存储、通信和计算开销,是适合空间网络的有效安全方案。