面向空间应用的单向微膨胀型热开关特性分析

为了提高探测器等航天器的温度控制精度,降低热波动造成的影响,基于金属的热胀冷缩原理设计了一种单向膨胀型热开关,利用二维稳态导热原理进行建模分析,得到热开关热特性参数。搭建了试验平台模拟热开关工作环境,测定不同功率条件下热开关的工作状态以及相关性能参数。当加热功率为04W时开关断开热阻为23046K/W;功率为30W时开关的导通热阻为03022K/W,开关控制比为7626。结果表明,试验数据与理论计算数据吻合较好,进一步说明了热开关的结构合理性以及适用性。     

火星稀薄大气参数对进入器气动特性的影响

针对火星稀薄大气环境的不确定性对进入器气动特性的影响问题,先以海盗号火星进入器的飞行试验数据对发展的三维并行直接模拟蒙特卡罗(DSMC)仿真软件进行了算例校验,再以火星科学实验室外形为例,计算气体组分、密度、温度及速度等来流参数的不确定性对进入器气动特性的影响偏差,定性定量给出火星高空稀薄环境下大气不确定性所带来的气动力特性规律。研究结果表明,通过与海盗号飞行实验数据的对比校验了所建立方法的正确性与可靠性;CO2大气环境对进入器气动特性的影响较大,利用空气稀薄环境中的计算及实验结果亦需进行CO2效应修正,这一点与连续流区的结论一致;来流密度及速度的不确定性对气动力、力矩特性均有影响,而来流温度影响的最大偏差小于0.5%;纵向压心对来流密度、温度及速度的扰动均不敏感。     

高温热管技术研究进展与展望

高温热管的工作温度高,传热性能好,在高超声速飞行器热防护、空间核反应堆冷却、太阳能利用等方面具有广阔的应用前景。报告了高温热管技术的研究现状,包括高温热管的冷冻启动特性研究、传热性能研究、试验研究、数值分析研究;介绍了放置倾角、工质物性参数、工质充装量、不凝气体含量、材料、结构和尺寸等因素对高温热管启动和传热性能的影响规律,以及高温热管技术在高超声速飞行器热防护、空间核反应堆冷却、太阳能利用等方面的应用研究等;指出了高温热管数值分析模型和工程应用验证等一系列有待深化研究的方向;提出了进一步深入研究高温热管技术的详细建议。     

基于电推力器进行南北位置保持的一种地球同步轨道注入参数方法

摘要： 电推力器在静止轨道卫星上应用越来越广泛,特别是基于电推力器进行南北位置保持,可以有效节省推进剂.提出改进的GPS星历参数解析算法,在此基础上考虑包含电推力模型在内多摄动项模型进行地面精密轨道计算,采用微分修正法,提出一种地球同步轨道注入参数方法,该方法可应用于星上自主完成基于电推力器的南北位置保持.仿真算例表明使用该方法得到的轨道注入参数,卫星能够在保证姿态确定精度的同时,完成南北位置保持任务.     

圆弧型指尖密封磨损计算方法及其特性研究

指尖密封是一种新型的接触式密封技术,磨损的存在制约着其密封性能的提升。为揭示圆弧型指尖密封磨损规律,根据其结构特点分析了指尖封严的磨损过程,构建了指尖密封体积磨损量关于时间的一阶线性非齐次微分方程,求解得到指尖密封中磨损量和磨损率计算的数学计算模型,并研究了结构参数对指尖密封磨损的影响。研究结果表明：指尖密封的体积磨损量随磨损时间呈指数增加趋势,初始阶段体积磨损量增加速度快,并随着磨损进行逐渐变慢,最终趋于某一定值;指式封严的磨损率随磨损时间的增加而呈指数趋势减小,开始阶段磨损率很大,随着磨损时间逐渐减小,最后磨损率逐渐趋于零;对指尖密封磨损快慢影响程度由大到小依次是：指梁厚度、指梁根圆、指梁顶圆、指梁基圆、指梁型线圆、周向角、指梁间隙。获得的结构参数对圆弧型指尖密封磨损特性影响规律,为圆弧型指尖密封性能优化提供了理论依据。     

叶片结构参数对电机外冷却风扇性能的影响及改进设计

采用计算流体动力学的方法对YX3小型电机外冷却系统进行了数值计算。分析了冷却风扇的叶片数、叶片外径和叶片宽度对电机风扇通风性能的影响,并从降低风扇输入功率的角度对风扇进行改进设计和样机试验验证。结果表明,装有改进风扇的电机机械损耗下降了39.1%,温升基本不变,电机效率提高了0.6%。     

同步磁阻电机性能分析与研究

针对永磁同步电动机(PMSM)用材多、成本高等问题,开发了成本低、效率高的同步磁阻电机(SRM)产品,在部分工况下替代PMSM,实现高效率电动机的推广。对2.2 kW、4极SRM的结构、电磁参数、控制方式等关键技术展开研究,为产品的系列化设计提供了理论基础,对电机设计人员有一定的参考价值。     

An application of the weighted horizontal magnetic gradient to solar compact and eruptive events

We propose to apply the weighted horizontal magnetic gradient (${\mathit{WG}}_M$), introduced in Korsós et al., 2015, for analysing the pre-flare and pre-CME behaviour and evolution of Active Regions (ARs) using the SDO/HMI-Debrecen Data catalogue. To demonstrate the power of investigative capabilities of the ${\mathit{WG}}_M$ method, in terms of flare and CME eruptions, we studied two typical ARs, namely, AR 12158 and AR 12192. The choice of ARs represent canonical cases. AR 12158 produced an X1.6 flare with fast “halo” CME ($v_{\mathit{linear}}$ = 1267 $\text{km}{\text{s}}^{-1}$) while in AR 12192 there occurred a range of powerful X-class eruptions, i.e. X1.1, X1.6, X3.1, X1.0, X2.0 and X2.0-class energetic flares, interestingly, none with an accompanying CME. The value itself and temporal variation of ${\mathit{WG}}_M$ is found to possess potentially important diagnostic information about the intensity of the expected flare class. Furthermore, we have also estimated the flare onset time from the relationship of duration of converging and diverging motions of the area-weighted barycenters of two subgroups of opposite magnetic polarities. This test turns out not only to provide information about the intensity of the expected flare-class and the flare onset time but may also indicate whether a flare will occur with/without fast CME. We have also found that, in the case when the negative polarity barycenter has moved around and the positive one “remained” at the same coordinates preceding eruption, the flare occurred with fast “halo” CME. Otherwise, when both the negative and the positive polarity barycenters have moved around, the AR produced flares without CME. If these properties found for the movement of the barycenters are generic pre-cursors of CME eruption (or lack of it), identifying them may serve as an excellent pre-condition for refining the forecast of the lift-off of CMEs.     

Detailed analysis of dynamic evolution of three Active Regions at the photospheric level before flare and CME occurrence

We present a combined analysis of the applications of the weighted horizontal magnetic gradient (denoted as ${\mathit{WG}}_M$ in Korsós et al. (2015)) method and the magnetic helicity tool (Berger and Field, 1984) employed for three active regions (ARs), namely NOAA AR 11261, AR 11283 and AR 11429. We analysed the time series of photospheric data from the Solar Dynamics Observatory taken between August 2011 and March 2012. During this period the three ARs produced a series of flares (eight M- and six X-class) and coronal mass ejections (CMEs). AR 11261 had four M-class flares and one of them was accompanied by a fast CME. AR 11283 had similar activities with two M- and two X-class flares, but only with a slow CME. Finally, AR 11429 was the most powerful of the three ARs as it hosted five compact and large solar flare and CME eruptions. For applying the ${\mathit{WG}}_M$ method we employed the Debrecen sunspot data catalogue, and, for estimating the magnetic helicity at photospheric level we used the Space-weather HMI Active Region Patches (SHARP’s) vector magnetograms from SDO/HMI (Solar Dynamics Observatory/Helioseismic and Magnetic Imager). We followed the evolution of the components of the ${\mathit{WG}}_M$ and the magnetic helicity before the flare and CME occurrences. We found a unique and mutually shared behaviour, called the U-shaped pattern, of the weighted distance component of ${\mathit{WG}}_M$ and of the shearing component of the helicity flux before the flare and CME eruptions. This common pattern is associated with the decreasing-receding phases yet reported only known to be a necessary feature prior to solar flare eruption(s) but found now at the same time in the evolution of the shearing helicity flux. This result leads to the conclusions that (i) the shearing motion of photospheric magnetic field may be a key driver for solar eruption in addition to the flux emerging process, and that (ii) the found decreasing-approaching pattern in the evolution of shearing helicity flux may be another precursor indicator for improving the forecasting of solar eruptions.     

基于动态集成算法的航空发动机气路参数预测

针对单一学习机对航空发动机气路参数预测困难的问题,提出了基于动态加权核密度估计（DWKDE)组合方法的集成预测算法,该组合方法选择测试样本的近邻样本,通过评估学习机在近邻样本的局部性能动态确定各学习机的权值,并基于该权值利用加权核密度估计实现数据序列的集成预测。该组合方法不易受离群值和样本不对称分布的影响,将该组合方法用于AdaBoost.RT和AdaBoost.R2算法,获得了改进后的集成学习算法。实验证明:相比于神经网络和原始集成学习算法,改进后的集成学习算法较好地提高了航空发动机气路参数序列的预测精度,方均根误差（RMSE)指标至少可降低27%。