湘西大脑坡铅锌矿床地质特征及成因分析

总结大脑坡铅锌矿床地质特征,对矿床微量元素、稀土元素地球化学特征进行了分析。从矿化产出形式、矿物共生组合和矿石组构、围岩蚀变、成矿方式及成矿物质来源等方面探讨矿床成因,综合分析认为矿床形成晚于围岩,属于层控型浅成低温热液型矿床,与MVT矿床相似。     

Numerical study on the dynamic behavior of rock avalanche: influence of cluster shape,size and gradation

Acta Geotechnica - In this paper, we present a numerical study of dynamic behavior of rock avalanche by using three-dimensional particle flow simulation. The emphasis is put on the influence of...     

Similarity criterion for the nonlinear thermal analysis of the soil freezing process: considering the dual effect of nonlinear thermal parameters and boundary conditions

Acta Geotechnica - Model tests are an important method to predict the design and long-term performance of structures and are widely used to analyze the seismic performance, wind resistance, etc.,...     

Controlling coal fires using the three-phase foam and water mist techniques in the Anjialing Open Pit Mine,China

Natural Hazards - Coal fires are a serious environment, health, and safety hazard throughout the world. They damage the environment, threaten the health of people living nearby, burn away...     

Analyzing the Waveform of the Shunchang Earthquakes in Fujian Province

On March 13, 2007, two earthquakes with M4.7 and M4.6 occurred in Zhengfang Village, Shunchang, Fujian. The M4.7 earthquake is the most intensive one in the Fujian region since the establishment of the Fujian digital seismic networks. These two earthquakes provide us with valuable first-hand observation data for seismological research. This paper analyzes their waveforms and concludes that （ 1 ） the crustal thickness in the seismic region is estimated to be about 40km according to the observed head-wave critical distance; （2） there is a salient difference between the ratios of S-wave＇s maximum amplitudes of these two earthquakes; （3） the focal depth of the M4.7 earthquake is estimated to be 8.4km according to the clear depth phrase sPn in waveforms, which is the same with the result of other determination methods.     

Improving monthly streamflow prediction in alpine regions: integrating HBV model with Bayesian neural network

Statistical methods have been widely used to build different streamflow prediction models; however, lacking of physical mechanism prevents precise streamflow prediction in alpine regions dominated by rainfall, snow and glacier. To improve precision, a new hybrid model (HBNN) integrating HBV hydrological model, Bayesian neural network (BNN) and uncertainty analysis is proposed. In this approach, the HBV is mainly used to generate initial snow-melt and glacier-melt runoffs that are regarded as new inputs of BNN for precision improvement. To examine model reliability, a hybrid deterministic model called HLSSVM incorporating the HBV model and least-square support vector machine is also developed and compared with HBNN in a typical region, the Yarkant River basin in Central Asia. The findings suggest that the HBNN model is a robust streamflow prediction model for alpine regions and capable of combining strengths of both the BNN statistical model and the HBV hydrological model, providing not only more precise streamflow prediction but also more reasonable uncertainty intervals than competitors particularly at high flows. It can be used in predicting streamflow for similar regions worldwide.     

Analysis of waves observed by synthetic aperture radar across ocean fronts

Ocean Dynamics - In this study, synthetic aperture radar (SAR) imaging of waves across ocean fronts was investigated using C-band Sentinel-1 VV-polarized SAR imagery collected over the Yangtze and...     

A low-latency pipeline for GRB light curve and spectrum using Fermi/GBM near real-time data

Rapid response and short time latency are very important for Time Domain Astronomy, such as the observations of Gamma-ray Bursts(GRBs) and electromagnetic(EM) counterparts of gravitational waves(GWs). Based on near real-time Fermi/GBM data, we developed a low-latency pipeline to automatically calculate the temporal and spectral properties of GRBs. With this pipeline, some important parameters can be obtained, such as T_(90) and fluence, within ～ 20 min after the GRB trigger.For ～ 90% of GRBs, T_(90) and fluence are consistent with the GBM catalog results within 2σ errors.This pipeline has been used by the Gamma-ray Bursts Polarimeter(POLAR) and the Insight Hard Xray Modulation Telescope(Insight-HXMT) to follow up the bursts of interest. For GRB 170817 A, the first EM counterpart of GW events detected by Fermi/GBM and INTEGRAL/SPI-ACS, the pipeline gave T_(90) and spectral information 21 min after the GBM trigger, providing important information for POLAR and Insight-HXMT observations.     

台风中降雨对中国高分3号合成孔径雷达观测信号的影响

Gaofen-3(GF-3), a Chinese civil synthetic aperture radar(SAR) at C-band, has operated since August 2016.Remarkably, several typhoons have been captured by GF-3 around the China Seas over its last two-year mission.In this study, six images acquired in Global Observation(GLO) and Wide ScanSAR(WSC) modes at verticalvertical(VV) polarization channel are discussed. This work focuses on investigating the observation of rainfall using GF-3 SAR. These images were collocated with winds from the European Centre for Medium-Range Weather Forecasts(ECMWF), significant wave height simulated from the WAVEWATCH-III(WW3) model, sea surface currents from climate forecast system version 2(CFSv2) of the National Centers for Environmental Prediction(NCEP) and rain rate data from the Tropical Rainfall Measuring Mission(TRMM) satellite. Sea surface roughness,was compared with the normalized radar cross section(NRCS) from SAR observations, and indicated a 0.8 correlation(COR). We analyzed the dependences of the difference between model-simulated NRCS and SARmeasured NRCS on the TRMM rain rate and WW3-simulated significant wave height. It was found that the effects of rain on SAR damps the radar signal at incidence angles ranging from 15° to 30°, while it enhances the radar signal at incidence angles ranging from 30° to 45° and incidence angles smaller than 10°. This behavior is consistent with previous studies and an algorithm for rain rate retrieval is anticipated for GF-3 SAR.     

MM4模式积云参数化方案的改进和检验Ⅰ:方案的改进

将 MM4模式应用于梅雨锋暴雨的中 -β尺度系统模拟时 ,模式的水平分辨率必须提高 ,这使得模式中原有的 Kuo- Anthes方案变得不适应。根据 Fritsch- Chappell方案的基本原理和特点 ,它可以合理取代 Kuo- Anthes方案来适应中 -β尺度系统的模拟 ;同时 ,结合近年来人们对积云属性研究的新成果 ,对 Fritsch- Chappell方案作了改进 ,最终得到一个适用于梅雨锋暴雨中 -β尺度系统模拟的改进 MM4模式