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171.
Fabrication and Investigation on Double-Hollow Shell CoFe Oxide@TiO2 Nanocube with Superior Electromagnetic Properties 下载免费PDF全文
Electromagnetic wave absorbing materials are urgently required in the fields of medicine, communication, and military. However, the thickness, weight, narrow effective bandwidth, and weak absorbing ability of the materials restrict their further application. In this work, a double-layer hollow nanocube with a dielectric titanium dioxide (TiO2) shell and a magnetic CoFe oxide inner shell is prepared. Prussian blue (PB) is prepared by the hydrothermal method, and used as the template to prepare PB@CoFe PB analogue (PBA). After selective etching and further calcination, hollow CoFe oxide particles are obtained. The obtained particles are then coated with SiO2 and TiO2, respectively, and the intermediate layer is dislodged to obtain the final CoFe oxide@TiO2 with the hollow double shell structure. The obtained double-layer hollow structure can effectively capture the incident electromagnetic waves, and increase the propagation path. Moreover, the obvious enhancement of interface polarization and the improvement of impedance matching enhance the wave absorbing ability of the material. The analysis results show that, the structure is stable and the dispersion is good. The maximum reflection loss (RL) at 10 GHz is as high as -46.1 dB with the sample thickness of 1.6 mm. The light-weight and high-efficiency CoFe oxide@TiO2 absorber is promised to be used in commercial and military aerospace fields. 相似文献
172.
双组元离心式喷注器10 N发动机偏工况试验 总被引:1,自引:0,他引:1
根据国内外同类发动机研制经验,双组元10 N发动机在入口压力为0.8~2.2 MPa范围内,入口压力偏差会使发动机真空比冲、燃气温度等性能产生较大变化。为了获得双组元离心式喷注器10 N发动机在落压推进系统要求的入口压力范围内性能,通过采用小流量喷雾试验台和42 km高模试验台,对偏工况条件下的冷态性能及热试性能进行试验研究。试验结果表明:该发动机额定入口压力1.58 MPa时真空比冲为2881 N·s/kg;当入口压力在0.6~2.5 MPa变化时,对应真空推力从4.7 N增加到14 N,落压比为3;入口压力0.6 MPa时真空比冲为2600 N·s/kg,入口压力2.5 MPa时真空比冲为2956 N·s/kg;入口压力在0.6~2.5 MPa试验范围内,发动机燃烧室壁温均低于材料许用温度,表明发动机热设计优良,可满足双组元落压推进系统对姿控发动机的性能需求。 相似文献
173.
Safety is the foundation of sustainable development in civil aviation. Although catastrophic accidents are rare,indicators of potential incidents and unsafe events frequently materialize. Therefore,a history of unsafe data are considered in predicting safety risks. A deep learning method is adopted for extracting reactions in safety risks. The deep neural network(DNN)model for safety risk prediction is shown to extract complex data characteristics better than a shallow network model. Using extended unsafe data and monthly risk indices,hidden layers and iterations are determined. The effectiveness of DNN is also revealed in comparison with the traditional neural network. Through early risk detection using the method in the paper,airlines and the government can mitigate potential risk and take proactive measures to improve civil aviation safety. 相似文献
174.
为了掌握UHMWPE/LDPE复合材料的损伤机理,运用声发射技术结合聚类分析方法建立不同损伤形式的声发射信号训练样本,通过神经网络实现损伤信号的识别,并分别探讨了训练函数、传递函数、网络结构等因素对识别率的影响。研究表明,由系统聚类可提取幅度、峰值频率、持续时间为模式特征,结合Kmeans聚类可建立11个类别共583信号的训练样本。以混淆矩阵为识别率指标,当训练函数为traingdx、隐层/输出层传递函数为tansig/logsig、隐层神经元数量为70时,网络的识别率达97.2%,为基于声发射技术的热塑性基体复合材料损伤识别提供参考。 相似文献
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建立了具有普遍性的考虑直升机空间机动飞行的尾传动轴动力学模型.分析了机动飞行对尾传动轴临界转速的影响,发现只有俯仰角速度、偏航角速度、横滚角速度和角加速度4个转动运动分量会影响尾传动轴的临界转速.通过算例着重分析了俯仰、偏航和横滚角速度对尾传动轴前3阶临界转速的影响规律.结果表明:俯仰角速度使尾传动轴的临界转速降低,但只对反进动第1阶临界转速有较大影响;偏航角速度对尾传动轴临界转速的影响效果与俯仰角速度完全相同;正向横滚角速度使尾传动轴的正进动临界转速提高,而使反进动临界转速降低;但对于反向横滚,在以横滚角速度等于某值的分界线之前,横滚角速度对尾传动轴临界转速的影响规律与正向横滚相反,前3阶临界转速变化曲线的分界线对应的横滚角速度分别为1.86,27.41,124.5rad/s. 相似文献