B65A-S钢动态力学性能及本构模型的研究

为了研究B65A-S钢的动态力学行为,采用Instron液压试验机和分离式霍普金森压杆试验装置,在不同应变率和不同温度条件下对圆柱形试样进行准静态和动态加载试验。试验结果表明,材料的屈服强度与流动应力随着温度升高而降低;在温度一定时,随着应变和应变率的增大,材料的流动应力增高,具有典型的温度软化、应变强化和应变率强化特性。最后基于Jonson-Cook本构模型对试验数据拟合,得到B65A-S钢的Johnson-Cook本构模型参数。     

泰雷兹:让中法的天空更加通畅

正中国民用航空局空中交通管理局局长车进军表示:"从简单设备的引进,大型设备的引进,人员的培训到技术的合作,中法航空50年空管发展的历程见证了合作的加深,合作的广泛,合作的成功。"2016年是中国与法国之间开通航线50周年,也是中法航空合作50周年。在民航技术合作板块,中法两国在民航空管领域的合作最具代表性。     

基于电力综合集成的多绕组双流发电机技术分析

为解决采用传统发电机的移动电站输出电源种类单一,而采用多台发电机又会造成底盘过载影响机动性的问题,文章基于电力综合集成技术,分析研究实现发电机的双流发电的关键技术,突破发电机多绕组发电及励磁解耦等难题,减小了电机体积、降低了电机重量,有利于移动电站的多功能化与小型化设计。     

Drag Reducing and Increasing Mechanism on Triangular Riblet Surface

Drag reducing and increasing mechanism on riblet surface has been studied through computational fluid dynamics(CFD).Drag reduction is achieved through the optimization of riblet geometry which would affect flow structure inside riblet grooves.Force and flow structure on riblet surface are analyzed and compared with those of smooth surface based on the k-εturbulence model.Drag reducing and increasing mechanism is proved to be related to microvortexes induced inside riblets which lead to Reynolds shear stress reduction significantly and is considered to be the dominant factor resulting in wall friction reduction.Simulation results also show that the pressure drag generating from the deviation of static pressure on the front and rear ends of riblets occurs and grows exponentially with Mach number,which can cause drag increasing.Furthermore,near-wall vortical structures,Reynolds shear stress and static pressure on riblet surfaces are also analyzed in detail.     

Early analysis of precise orbit and clock offset determination for the satellites of the global BeiDou-3 system

Eight new-generation BeiDou satellites (BeiDou-3) have been launched into Medium Earth Orbit (MEO), allowing for global coverage since March 2018, and they are equipped with new hydrogen atomic clocks and updated rubidium clocks. Firstly, we analyzed the signals for the carrier-to-noise-density ratio (C/N0) and pseudorange multipath (MP) by using international GNSS (Global Navigation Satellite System) Monitoring and Assessment System (iGMAS) station data, and found that B1C has a lower C/N0, and B2a has the same level of C/N0 as the B1I and B3I signals. For pseudorange multipath, compared with the BeiDou-2 satellites, the obvious systematic variation of MP scatters related to the elevation angle is greatly improved for the BeiDou-3 and BeiDou-3e satellites signals. For the signals of the BeiDou-3 satellites, the order of the Root Mean Square (RMS) values of multipath and noise is B3I?<?B1I?<?B2a?<?B1C. Then, the comparison of the precise orbit determination and clock offset determination for the BeiDou-2, BeiDou-3, and BeiDou-3 experimental (BeiDou-3e) satellites was done by using 10 stations from iGMAS. The 3D precision of the 24?h orbit overlap is 24.55, 25.61, and 23.35?cm for the BeiDou-3, BeiDou-3e, and BeiDou-2 satellites, respectively. BeiDou-3 satellite has a comparable precision to that of the BeiDou-2 satellite. For the precision of clock offset estimation, the Standard Deviation (STD) of the BeiDou-3 MEO satellite is 0.350?ns, which is an improvement of 0.042?ns over that of the BeiDou-2 MEO satellite. The stabilities of the BeiDou-3 and BeiDou-3e onboard clocks are better than those of BeiDou-2 by factors of 2.84 and 1.61 at an averaging time of 1000 and 10,000?s, respectively.     

Fault Estimation and Accommodation for a Class of Nonlinear System Based on Neural Network Observer

The problem of fault estimation and accommodation of nonlinear systems with disturbances is studied using adaptive observer and neural network techniques.A robust adaptive learning algorithm based on switchingβsmodification is developed to realize the accurate and fast estimation of unknown actuator faults or component faults.Then a fault tolerant controller is designed to restore system performance.Dynamic error convergence and system stability can be guaranteed by Lyapunov stability theory.Finally,simulation results of quadrotor helicopter attitude systems are presented to illustrate the efficiency of the proposed techniques.     

High temporal resolution global PWV dataset of 2005–2016 by using a neural network approach to determine the mean temperature of the atmosphere

Atmospheric water vapour plays an important role in phenomena related to the global hydrologic cycle and climate change. However, the rapid temporal–spatial variation in global tropospheric water vapour has not been well investigated due to a lack of long-term, high-temporal-resolution precipitable water vapour (PWV). Accordingly, this study generates an hourly PWV dataset for 272 ground-based International Global Navigation Satellite System (GNSS) Service (IGS) stations over the period of 2005–2016 using the zenith troposphere delay (ZTD) derived from global-scale GNSS observation. The root mean square (RMS) of the hourly ZTD obtained from the IGS tropospheric product is approximately 4 mm. A fifth-generation reanalysis dataset of the European Centre for Medium-range Weather Forecasting (ECMWF ERA5) is used to obtain hourly surface temperature (T) and pressure (P), which are first validated with GNSS synoptic station data and radiosonde data, respectively. Then, T and P are used to calculate the water vapour-weighted atmospheric mean temperature (Tm) and zenith hydrostatic delay (ZHD), respectively. T and P at the GNSS stations are obtained via an interpolation in the horizontal and vertical directions using the grid-based ERA5 reanalysis dataset. Here, Tm is calculated using a neural network model, whereas ZHD is obtained using an empirical Saastamoinen model. The RMS values of T and P at the collocated 693 radiosonde stations are 1.6 K and 3.1 hPa, respectively. Therefore, the theoretical error of PWV caused by the errors in ZTD, T and P is on the order of approximately 2.1 mm. A practical comparison experiment is performed using 97 collocated radiosonde stations and 23 GNSS stations equipped with meteorological sensors. The RMS and bias of the hourly PWV dataset are 2.87/?0.16 and 2.45/0.55 mm, respectively, when compared with radiosonde and GNSS stations equipped with meteorological sensors. Additionally, preliminary analysis of the hourly PWV dataset during the EI Niño event of 2014–2016 further indicates the capability of monitoring the daily changes in atmospheric water vapour. This finding is interesting and significant for further climate research.