级联三能级原子系统的量子特征

运用油松分布的性质和二元泰勒级数展开方法，研究了初始处于下能级的级联三能级ＪＣ模型中的原子与两个初始相于辐射场的相互作用，得到了原子能级算符、光子数和偶极矩算符的平均值的近似解析解，与前人数值结果相比，更加明确地反映了系统的量子效应。     

DSP的数学原理及在实时系统的应用

制造系统里所用的微处理器中，单片机只能做逻辑处理和简单数学计算，而数字信号处理器（DSP）可进行相当复杂的数学处理。本文概述DSP的数学原理及其技术特点，介绍了基于DSP智能控制器在制造业中实时测控系统的应用实例。     

中介时序逻辑系统MTL的模型论性质

时序逻辑作为一种把时间概念直接引入其形式系统的逻辑系统,它具有较强的表达能力,近年来在计算机科学领域获得了广泛的应用.基于中介逻辑对时序逻辑进行多值扩充,建立了一种中介时序逻辑系统MTL(Medium Temporal Logic).讨论了它的形式系统和语义解释,但未论及其完备性.本文对MTL系统作进一步的讨论.在一可传结构下,讨论了它的可传、连通和过滤等模型论性质,为进一步讨论MTL系统的完备性作了理论上的准备.     

基于中介逻辑的多模态逻辑系统

多模态逻辑作为模态逻辑的扩充，是模态逻辑进行时态和动态扩充的基础。中介逻辑是一个新的逻辑系统，自创立后得到了很大发展，并在数理逻辑及计算机科学领域中得到广泛应用。为将中介逻辑进行时态和动态扩充，本文构造了一种基于中介逻辑的多模态逻辑系统ＭＭＫ，讨论了它的推理规则和语义解释，并证明了ＭＭＫ的可靠性和完备性，在此基础上给出了一种基于中介逻辑的时态逻辑系统ＭＴ，对它的可靠性和完备性进行了讨论。最后，分析了相应的经典多模态逻辑系统与ＭＭＫ系统及经典时态逻辑系统和ＭＴ系统之间的关系。     

中介公理集合论系统与经典公理集合论系统的关系——形式证明部分

在中介公理集合论系统（ＭＳ）中重新定义了良集的概念，讨论了它的性质。证明良集完全满足经典公理集合论系统（ＺＦＣ－：ＺＦＣ系统中去掉正则公理）的全部公理，且其配套的逻辑系统恰为中介逻辑的二值子系统ＦＩ＊ＭＬ，说明整个经典数学也能奠基于ＭＳ之上，从而最终回答了中介数学与经典数学的包含关系问题。     

符合CCSDS标准的RS(255,223)码译码器的FPGA实现及其性能测试

RS（Reed-Solomon)码是差错控制领域中一种性能优异的非二进制分组循环码，由于它具有很强的随机错误和突发错误的纠错能力，被CCSDS，NASA，ESA等空间组织接受，广泛应用于深空探测中．本文采用改进的Berlekamp算法，用FPGA实现了符合CCSDS标准的RS(255，223)码译码器；介绍了该译码器的实现流程、性能测试方法和基于PCI总线接口的测试平台；给出了测试结果，并且对理论上RS(255，223)译码器的误码性能与实际测试的误码率结果进行了比较和分析．验证结果证明该译码器能工作在400Mbps以上的码率，使用FPGA资源180000门，译码效果与理论上译码效果一致．     

A coupling VWM/CFD/CSD method for rotor airload prediction

A coupling fluid-structure method with a combination of viscous wake model(VWM),computational fluid dynamics(CFD) and comprehensive structural dynamics(CSD) modules is developed in this paper for rotor unsteady airload prediction. The hybrid VWM/CFD solver is employed to model the nonlinear aerodynamic phenomena and complicated rotor wake dynamics;the moderate deflection beam theory is implemented to predict the blade structural deformation; the loose coupling strategy based on the ‘delt method' is used to couple the fluid and structure solvers.Several cases of Helishape 7A rotor are performed first to investigate the effect of elastic deformation on airloads. Then, two challenging forward flight conditions of UH-60 A helicopter rotor are investigated, and the simulated results of wake geometry, chordwise pressure distribution and sectional normal force show excellent agreement with available test data; a comparison with traditional CFD/CSD method is also presented to illustrate the efficiency of the developed method.     

火箭橇体进水现象研究

在考核过载承受能力的火箭橇试验后,橇体内发现有水,从空气动力学的角度,对火箭橇体进水现象进行了初步分析,并利用FLUENT软件对进水原因进行了初步研究,通过分析,发现结构在穿越跨音速阶段时,由于内外压差的变化将导致内部或外部产生水汽。该发现为结构设计提供有益的建议。     

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.     

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.