A new spatial coherence model and analytical coefficients for multi-support response spectrum combination

In this paper, a new spatial coherence model of seismic ground motions is proposed by a fi tting procedure. The analytical expressions of modal combination (correlation) coeffi cients of structural response are developed for multi-support seismic excitations. The coeffi cients from both the numerical integration and analytical solutions are compared to verify the accuracy of the solutions. It is shown that the analytical expressions of numerical modal combination coeffi cients are of high accuracy. The results of random responses of an example bridge show that the analytical modal combination coeff icients developed in this paper are accurate enough to meet the requirements needed in practice. In addition, the computational effi ciency of the analytical solutions of the modal combination coeff icients is demonstrated by the response computation of the example bridge. It is found that the time required for the structural response analysis by using the analytical modal combination coeffi cients is less than 1/20 of that using numerical integral methods.     

Joint probability density function of the stochastic responses of nonlinear structures

The joint probability density fimction （PDF） of different structural responses is a very important topic in the stochastic response analysis of nonlinear structures. In this paper, the probability density evolution method, which is successfully developed to capture the instantaneous PDF of an arbitrary single response of interest, is extended to evaluate the joint PDF of any two responses. A two-dimensional partial differential equation in terms of the joint PDF is established. The strategy of selecting representative points via the number theoretical method and sieved by a hyper-ellipsoid is outlined. A two-dimensional difference scheme is developed. The free vibration of an SDOF system is examined to verify the proposed method, and a flame structure exhibiting hysteresis subjected to stochastic ground motion is investigated. It is pointed out that the correlation of different responses results from the fact that randomness of different responses comes from the same set of basic random parameters involved. In other words, the essence of the probabilistic correlation is a physical correlation.     

地面观测资料地形高度订正对我国东部暴雨数值模拟的影响

采用中尺度气象模式 WRFv3.8.1(Weather Research and Forecasting Model)和 GSI 同化系统(Gridpoint Statistical Interpolation System),建立了一套循环同化系统,开展了一个月的地面观测资料、探空资料、雷达资料和卫星资料的同化试验....     

阿尔金断裂花海段新生代变形特征及时间

在地表地质调查并结合钻井资料分析的基础上,主要通过地震剖面的精细地质解释,对阿尔金断裂东段的构造变形特征进行了系统分析。认为阿尔金断裂经阿克塞至肃北向北东东方向延伸,既没有止于玉门市西北的宽台山,也没有延伸至金塔盆地,而是止于其间的花海盆地花探7井东侧。阿尔金断裂花海段的变形时间主要为渐新世晚期、上新世末期和晚更新世末,以后者最为强烈。与红柳峡段的对比说明变形强度自西向东逐渐减弱,变形方式主要为走滑兼逆冲,主要构造样式为半花状构造,并派生有一系列向南西西方向收敛的弧形断裂。     

重庆市乡村义务教育资源可得性差异及影响因素

以国家统筹城乡教育发展试验区的重庆市乡村地区为例,采用Densi-Graph城乡识别法进行行政区划内部格网尺度的精准识别,在此基础上探究义务教育资源可得性水平的空间差异及影响因素。结果表明：1)基于Densi-Graph城乡识别法的重庆市城乡差异显著,乡村区域面积达79 752 km²,占区域总面积的96.82%。城市部分面积为2 616 km²,占区域总面积的3.18%。2)重庆市义务教育资源可得性水平具有显著的空间集聚与关联特征,并呈现由中心城区向外递减的格局。3)政府重视程度、社会经济发展水平、交通设施水平、自然地理环境均与义务教育资源可得性水平具有显著相关性。4)交通站点密度与教育投入是影响义务教育资源可得性水平的主导因子,二者与各项因子的交互叠加作用增强效果显著;影响机制上,地形起伏度与坡度是乡村义务教育资源可得性水平的限制条件,社会经济是基础,交通是关键,教育投入是核心。     

潜在地震灾害预测和评价神经网络系统及其若干问题

结合人工神经网络自身的特性和地震灾害预测研究的特点,本文应用神经网络模型,建立了潜在地震灾害预测和评价系统。针对网络模型参数设置、数据归一化、中间层神经元最优数目以及泛化分类评价指标等若干实际问题给出了实际可行的解决方案。通过大样本数据对网络的训练,形成了有识别和记忆功能的非线性预测和评价系统。对网络的测试和检验,论证了该系统在预测潜在地震灾害上的可行性和有效性。同时,从测试精度出发,探讨了这种预测网络存在的不足,并给出了相应的改进建议,为开展进一步的研究工作提供了参考。     

6级以上地震平静与7级以上地震发生的关系分析

利用χ2检验方法对我国大陆6级以上地震平静与7级以上地震发生之间的关系进行了统计检验,结果表明:6级以上地震平静与我国大陆地区发生7级以上地震的关系不显著。6级以上地震平静460天与其后1年2月内我国大陆及边境地区发生7级以上地震的关系显著。     

3D Step-by-step inversion strategy for audio magnetotellurics data based on unstructured mesh

A three-dimensional (3D) step-by-step inversion strategy for audio magnetotellurics(AMT) is investigated in this study.The objective function is minimized by it...     

1951—2018年衢州市椪柑采摘期连阴雨天气变化特征

基于1951—2018年衢州市椪柑采摘期降水量、雨日、日照时数、相对湿度等逐日气象资料,应用统计分析和小波分析方法,分析椪柑采摘期连阴雨天气变化特征及其大气环流背景.结果表明:1951—2018年衢州椪柑采摘期连阴雨日数、次数和强度呈略微增加趋势、滑动3d无雨次数呈减少趋势;滑动3d无雨次数存在明显的5a、7a和15a...     

Understanding the dynamical-microphysical-electrical processes associated with severe thunderstorms over the Beijing metropolitan region

The Dynamical-microphysical-electrical Processes in Severe Thunderstorms and Lightning Hazards(STORM973)project conducted coordinated comprehensive field observations of thunderstorms in the Beijing metropolitan region(BMR)during the warm season from 2014 to 2018.The aim of the project was to understand how dynamical,microphysical and electrical processes interact in severe thunderstorms in the BMR,and how to assimilate lightning data in numerical weather prediction models to improve severe thunderstorm forecasts.The platforms used in the field campaign included the Beijing Lightning Network(BLNET,consisting of 16 stations),2 X-band dual linear polarimetric Doppler radars,and 4 laser raindrop spectrometers.The collaboration also made use of the China Meteorological Administration’s mesoscale meteorological observation network in the Beijing-Tianjin-Hebei region.Although diverse thunderstorm types were documented,it was found that squall lines and multicell storms were the two major categories of severe thunderstorms with frequent lightning activity and extreme rainfall or unexpected local short-duration heavy rainfall resulting in inundations in the central urban area,influenced by the terrain and environmental conditions.The flash density maximums were found in eastern Changping District,central and eastern Shunyi District,and the central urban area of Beijing,suggesting that the urban heat island effect has a crucial role in the intensification of thunderstorms over Beijing.In addition,the flash rate associated with super thunderstorms can reach hundreds of flashes per minute in the central city regions.The super(5%of the total),strong(35%),and weak(60%)thunderstorms contributed about 37%,56%,and 7%to the total flashes in the BMR,respectively.Owing to the close connection between lightning activity and the thermodynamic and microphysical characteristics of the thunderstorms,the lightning flash rate can be used as an indicator of severe weather events,such as hail and short-duration heavy rainfall.Lightning data can also be assimilated into numerical weather prediction models to help improve the forecasting of severe convection and precipitation at the cloud-resolved scale,through adjusting or correcting the thermodynamic and microphysical parameters of the model.