A comprehensive study of the 2016 Mw 6.0 Italy earthquake based on high-rate (10 Hz) GPS data

The 2016 M_w 6.0 Italy earthquake is successfully recorded by the near-field 10?Hz GPS and 200?Hz Strong Motion (SM) stations, providing valuable data for this study. A comprehensive study of this earthquake is carried out based on GPS data, which contains coseismic deformations analysis, noise analysis, seismic wave picking, and magnitude determination. The noise of most GPS-derived displacement waveforms can be described as a combination of white noise, flicker noise, and random walk noise after the earthquake occurrence, and the spectral indices vary significantly for most stations, implying that the seismic signals have affected the noise characteristic of GPS-derived displacement waveforms. S-transform is employed to assess the GPS capability to detect the seismic arrival time. The SM station AMT and the GPS station AMAT are in good agreement in seismic wave picking, and the difference is only 1.2?s in the north component, suggesting that the outcome of seismic wave picking using GPS data is reliable. Then, a classic empirical formula is employed to determine the moment magnitude. A robust moment magnitude (Mw 5.90) can be estimated by the nine GPS stations with about 23.9?s. If four GPS stations near the epicenter is chosen to determine the magnitude, it only take 13.0?s to retrieve a reliable preliminary (Mw 5.82) magnitude, which is 5.4?s ahead of nine stations. In addition, Cross Wavelet Transform (XWT) is adopted to measuring the correlation and phase relationship between GPS and SM records. The result of XWT analysis indicates 10?Hz GPS is capable of capturing reliable and accurate coseismic dynamic deformations, as evidenced by the XWT-based semblance being close to 1 between GPS and SM records. The above results confirm the capability of 10?Hz GPS to capture coseismic dynamic deformations, detect seismic arrival time, and determine earthquake magnitude. Moreover, rapid magnitude determination based on 10?Hz GPS data can be regarded as an important supplement to Earthquake Early Warning (EEW).     

李宏新发动机设计专家

作为长期从事飞机发动机研发工作的中航工业首席技术专家,请您谈一谈我国飞机发动机的研发现状以及需要攻克的难关。李宏新:航空发动机的研制是一个复杂的系统工程,研制道路充满艰辛和坎坷,不容丝毫懈怠和疏忽。     

A general calculation method to specify center-of-buoyancy for the stratospheric airship with multiple gas cells

As the lighter-than-air (LTA) flight vehicle, the stratospheric airship is a desirable platform to provide communication and surveillance services. During the ascent from sea-level to the mission altitude, the volume of the lifting gas may change significantly, which will result in the change of the center-of-buoyancy (CB). A general calculation method is developed to specify CB for the stratospheric airship with a double-ellipsoid hull and an arbitrary number of the gas cells. The cross-section-integral (CSI) method is used as a basic calculation scenario to specify CB. Considering the complexity in determining the boundary between the helium and air in the gas cell, a searching algorithm is put forward and the specification of CB can be conducted by the iterative calculation. As an important application, the stable condition of the pitch angle is analyzed when the change of CB is involved. Under different initial configurations, the stable pitch angle of the stratospheric airship during the ascent is specified and compared, which shows the advantages of the multi-gas-cell configuration. The results of this paper may provide an important reference for the engineering application of the stratospheric airship.     

平面近场测试中误差的分析

首先介绍了暗室中主要的误差项,然后通过实际测试的方式,分析了其中四项误差对超低副瓣天线-50dB副瓣的不确定度.结果对超低副瓣天线副瓣的误差分析有一定的参考意义,有助于天线设计师了解超低副瓣天线测试中误差项对副瓣的影响量级.     

Global ionospheric scintillations revealed by GPS radio occultation data with FY3C satellite before midnight during the March 2015 storm

Global observations of S4 amplitude scintillation index by the GPS Occultation Sounder (GNOS) on FengYun-3 C (FY3C) satellite reveal global dynamic patterns of a strong pre-midnight scintillations in F-region of the ionosphere during the St. Patrick’s Day geomagnetic super storm of 17–19 March 2015. The observed strong scintillations mainly occurred in the low latitudes, caused by equatorial plasma bubbles. During the main storm phase (March 17), the scintillations were first triggered in the New Zealand sector near 160°E longitudes, extending beyond 40°S dip latitude. They were also enhanced in the Indian sector, but significantly suppressed in East Asia near 120°E longitude and in Africa around 30°E longitude. During the initial recovery phase (March 18–19), the global scintillations were seldom observed in GNOS data. During the later recovery phase (after March 19), the scintillations recovered to the pre-storm level in Indian, African, and American sectors, but not in East Asian and any of Pacific sectors. These results closely correlate with observations of the density depletion structures by the Communication/Navigation Outage Forecasting System (C/NOFS) satellite, and ground-based instruments. Such consistency indicates reliability of our scintillation sensing approach even in a case-by-case comparison study. The prompt penetration electric field and disturbance dynamo electric field are suggested as the main factors that control the enhancement and inhibition of the scintillations during the storm, respectively.     

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.     

An Improved Nonlinear Dynamic Inversion Method for Altitude and Attitude Control of Nano Quad-Rotors under Persistent Uncertainties

Nonlinear dynamic inversion(NDI)has been applied to the control law design of quad-rotors mainly thanks to its good robustness and simplicity of parameter tuning.However,the weakness of relying on accurate model greatly restrains its application on quad-rotors,especially nano quad-rotors(NQRs).NQRs are easy to be influenced by uncertainties such as model uncertainties(mainly from complicated aerodynamic interferences,strong coupling in roll-pitch-yaw channels and inaccurate aerodynamic prediction of rotors)and external uncertainties(mainly from winds or gusts),particularly persistent ones.Therefore,developing accurate model for altitude and attitude control of NQRs is difficult.To solve this problem,in this paper,an improved nonlinear dynamic inversion(INDI)method is developed,which can reject the above-mentioned uncertainties by estimating them and then counteracting in real time using linear extended state observer(LESO).Comparison with the traditional NDI(TNDI)method was carried out numerically,and the results show that,in coping with persistent uncertainties,the INDI-based method presents significant superiority.     

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.