Measurement and stability of the pointing of the BepiColombo Laser Altimeter under thermal load

The BepiColombo Laser Altimeter (BELA) has been selected to fly on ESA?s BepiColombo mission to Mercury. The instrument will be the first European laser altimeter designed for interplanetary flight. This paper describes the setup used to characterize the angular movements of BELA under the simulated environmental conditions that the instrument will encounter when orbiting Mercury. The system comprises a laser transmitter and a receiving telescope, which can move with respect to each other under thermal load. Tests performed using the Engineering Qualification Model show that the setup is accurate enough to characterize angular movements of the instrument components to an accuracy of ≈10 μrad. The qualification instrument is thermally stable to operate during all mission phases around Mercury proving that the transmitter and receiver sections will remain within the alignment requirements during its mission.     

Surface latent heat flux anomalies quasi-synchronous with ionospheric disturbances before the 2007 Pu’er earthquake in China

One of various mechanisms of pre-earthquake lithosphere–atmosphere–ionosphere coupling as possible explanation of the seismo-ionospheric effects is connected with the release of latent heat. Abnormal variations of ionospheric electromagnetic parameters possibly related to the 2007 Ms 6.4 Pu’er earthquake in China were reported. This paper attempts to examine whether there were abnormal changes of surface latent heat flux (SLHF) linked with this pre-earthquake ionospheric disturbances. The spatio-temporal statistical analyzes of multi-years SLHF data from USA NCEP/NCAR Reanalysis Project reveal that local SLHF enhancements appeared 11, 10 and 7 days before the Pu’er earthquake, respectively. As contrasted to the formerly reported local ionospheric Ne enhancement 9 days before the shock observed by DEMETER satellite, it is discovered that the SLHF and Ne anomalies are quasi-synchronous and have good spatial correspondence with the epicentre and the local active faults. This is valuable for understanding the seismogenic coupling processes and for recognizing earthquake anomaly with multiple parameters from integrated Earth observation system.     

Thermal and TEC anomalies detection using an intelligent hybrid system around the time of the Saravan,Iran, (Mw = 7.7) earthquake of 16 April 2013

A powerful earthquake of M_w = 7.7 struck the Saravan region (28.107° N, 62.053° E) in Iran on 16 April 2013. Up to now nomination of an automated anomaly detection method in a non linear time series of earthquake precursor has been an attractive and challenging task. Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) have revealed strong potentials in accurate time series prediction. This paper presents the first study of an integration of ANN and PSO method in the research of earthquake precursors to detect the unusual variations of the thermal and total electron content (TEC) seismo-ionospheric anomalies induced by the strong earthquake of Saravan. In this study, to overcome the stagnation in local minimum during the ANN training, PSO as an optimization method is used instead of traditional algorithms for training the ANN method. The proposed hybrid method detected a considerable number of anomalies 4 and 8 days preceding the earthquake. Since, in this case study, ionospheric TEC anomalies induced by seismic activity is confused with background fluctuations due to solar activity, a multi-resolution time series processing technique based on wavelet transform has been applied on TEC signal variations. In view of the fact that the accordance in the final results deduced from some robust methods is a convincing indication for the efficiency of the method, therefore the detected thermal and TEC anomalies using the ANN + PSO method were compared to the results with regard to the observed anomalies by implementing the mean, median, Wavelet, Kalman filter, Auto-Regressive Integrated Moving Average (ARIMA), Support Vector Machine (SVM) and Genetic Algorithm (GA) methods. The results indicate that the ANN + PSO method is quite promising and deserves serious attention as a new tool for thermal and TEC seismo anomalies detection.     

A comparison of different regression models for downscaling Landsat and MODIS land surface temperature images over heterogeneous landscape

Remotely sensed high spatial resolution thermal images are required for various applications in natural resource management. At present, availability of high spatial resolution (<200 m) thermal images are limited. The temporal resolution of such images is also low. Whereas, coarser spatial resolution (∼1000 m) thermal images with high revisiting capability (∼1 day) are freely available. To bridge this gap, present study attempts to downscale coarser spatial resolution thermal image to finer spatial resolution using relationships between land surface temperature (LST) and vegetation indices over a heterogeneous landscape of India. Five regression based models namely (i) Disaggregation of Radiometric Temperature (DisTrad), (ii) Temperature Sharpening (TsHARP), (iii) TsHARP with local variant, (iv) Least median square regression downscaling (LMS_DS) and (v) Pace regression downscaling (PR_DS) are applied to downscale LST of Landsat Thematic Mapper (TM) and Terra MODIS (Moderate Resolution Imaging Spectroradiometer) images. All the five models are first evaluated on Landsat image aggregated to 960 m resolution and downscaled to 480 m and 240 m resolution. The downscale accuracy is achieved using LMS_DS and PR_DS models at 240 m resolution at 0.61 °C and 0.75 °C respectively. MODIS data downscaled from 1000 m to 250 m spatial resolution results root mean square error (RMSE) of 1.43 °C and 1.62 °C for LMS_DS and PR_DS models, respectively. The LMS_DS model is less sensitive to outliers in heterogeneous landscape and provides higher accuracy when compared to other models. Downscaling model is found to be suitable for agricultural and vegetated landscapes up to a spatial resolution of 250 m but not applicable to water bodies, dry river bed sand sandy open areas.     

星载铷钟组件的热设计与热仿真

为保证在相应运行环境下星载铷钟的可靠性,对其关键组件热支撑结构、大功率器件分布等方面进行了热设计,并利用ANSYS进行了仿真分析。通过热设计和热仿真分析,避免了热流密度迅速升高,确保了大功率器件可以在正常的工作范围内工作,实现了整机的热可靠性。     

碳化材料三维烧蚀热响应有限元计算研究

针对碳化烧蚀热防护材料三维温度场计算问题进行了研究。采用弹簧松弛法模拟防热层表面后退运动,应用化学反应动力学模型描述材料内部热解过程,内部温度场计算模型考虑了防热材料的热传导、热解吸热、热解气体在碳化层内的流动以及热解气体与碳化层之间的热交换。对控制方程采用有限元方法进行离散,时间方向采用Newton-GMRES隐式迭代推进求解。将计算结果与经典程序的计算结果及实验数据进行了比对,初步验证了计算方法的可靠性,并通过球头算例展示了程序对三维问题的良好处理能力。     

基于L-M算法的液体火箭推力室壁面热流密度测量方法

为获取液体火箭推力室热防护方案构建的基础数据,结合单点瞬态法,提出了基于L-M算法测量壁面热流密度的方法。通过模拟热流密度分析算法中关键参数对求解精度的影响,给出关键参数的选取建议。在此基础上,对过氧化氢煤油推力室典型试验工况进行热流密度测量。结果表明：圆筒段末端壁面热流密度为3.35MW/m²,喉部位置单组元工况下壁面热流密度为2.21MW/m²,双组元工况下壁面热流密度为10.59MW/m²,热流密度变化过程与室压变化过程完全对应。变工况过程中近壁处燃气温度存在恢复过程,燃气温度稳定后,壁面热流密度也达到稳定状态。本文提出的方法可迅速、准确地测量推力室壁面热流密度。     

壁面温度对斜爆震发动机进气道流动特性影响的数值研究

为研究壁面温度条件对层流、转捩、湍流状态下斜爆震发动机进气道流场结构、流场参数的影响,选取Ma10级、具有曲面压缩段的斜爆震发动机进气道为研究对象进行数值模拟,对进气道壁面附近激波诱导分离区、热边界层的变化进行了深入探讨。数值模拟结果表明,进气道肩部圆弧过渡段出现的再层流化现象,壁面冷却对其起抑制作用,绝热壁面条件下再层流化程度最为严重。壁面温度的增加有利于延缓流动转捩,同时也导致了分离区尺寸的增加以及转捩、湍流状态下分离区主体位置逐渐前移,进气道内通道的转捩为分离诱导转捩,转捩位置主要受到分离点位置的影响,整体表现为壁面温度增加转捩位置前移。进气道出口顶板侧热边界层厚度随着壁面温度的增加逐渐变厚,转捩状态下热边界层厚度变化可达5%,温度峰值也随着壁面温度的增加逐渐增加,且峰值位置逐渐靠近壁面。壁面温度条件相同时,层流状态下热流、热边界层厚度均较小。转捩、湍流状态下进气道出口顶板侧热边界层较厚,约为层流状态3倍,同时转捩、湍流状态下热边界层厚度相差可达2%。     

组合动力用过氧化氢煤油推力室热防护方案设计方法

本文面向组合动力对过氧化氢煤油推力室的应用需求,建立工程计算方法以进行热防护方案设计。通过修正燃气对流换热系数和引入液膜分解率完善工程算法,使工程计算结果与三维流固热耦合计算结果和实际试验结果符合较好。在此基础上,对组合动力用推力室进行热防护方案设计,结果表明：采用头部过氧化氢液膜和身部过氧化氢再生的方式可实现可靠热防护,其中,液膜流量在氧化剂中占比为30%。采用上述研究思路具备开展快速方案论证的能力,可在众多方案中选出热防护性能较优的方案。     

高超声速流动壁面催化复合气动加热特性

针对高超声速流动壁面催化特性,计算了不同壁面催化复合系数条件下的球锥驻点热环境。引入了经验证的数值求解Navier Stokes方程的方法,在不同壁温500K～2500K的条件下分别分析了O 2和N 2气体在壁面处的催化复合气动加热特性,得到如下结论：（1） 原子复合放热将提高近壁面温度梯度,改变近壁面组分分布;原子复合放热一部分加热飞行器形成组分扩散热流,一部分加热近壁气体提高近壁温度梯度。（2） 在壁面催化复合系数较小时,原子复合放热主要转化为组分扩散加热,对于不同壁面温度,壁面催化复合系数α<0.1时,单一气体反应组分扩散热流小于总热流的20%。