2008年1月一次强雨雪过程的诊断分析

采用NCEP1°×1°客观再分析资料和常规观测资料,对2008年1月25—29日发生在长江中下游地区的强雨雪过程进行诊断分析,结果表明,低空急流与强雨雪有着密切关系,强雨雪的发生需具备一定的温度条件以及水汽场与动力场的耦合机制。对强雨雪过程的湿Q矢量诊断分析表明,700hPa湿Q矢量辐合区以及850hPa锋生函数正值区与强雨雪区对应较好,对雨雪天气的发生有着很好的指示意义。湿位涡特征分析表明,此次强雨雪过程发生在层结稳定的大气中且垂直涡度发展较强。     

呼和浩特市降水化学特征分析

对2006年呼和浩特市降水离子监测资料进行分析,结果表明:降水呈碱性,季节分布明显,夏季降水集中且pH值为全年最低,冬季降水量少,pH值较高;SO42-离子为主要致酸离子,阳离子中Ca2+,Mg2+离子的浓度很高;降水中主要成分之间相关性显著,Ca2+的中和作用较强;降水气团的后向轨迹分析表明蒙古国的沙漠地区是呼和浩特冬春季碱性降水的主要来源,夏季较低的pH值降水则部分源于我国的华中、华北地区的酸性污染物中长距离输送。     

ENVIRONMENTAL CHANGES SINCE LATE PLEISTOCENE IN ESTUARINE PLAIN OF JIULONG RIVER, FUJIAN PROVINCE

TheestuarineplainoftheJiulongRiver,whichisthesecondlargestrivernexttotheMinjiangRiverinFujianPrc)vince,intervenesbetweenXi~enandZhangzhoucitiesinthesouthoftheprovince.'I'heplainconsistsofthreeparts:thenorthernplain,thesouthernPlainandZiniIsles.Withsoutllcrn--Subtr<)picoceanicm(>nasexinclimate,itdevelol>saregionalvegetationtypeofeveTgreen13r(Jad--lcav(3dfores[,ofwhicll,however,mosthasbeendestroyedbyhumanbeing.Nowaday-s.shruborgrasslandvegetationcanbeseenonthehillsintheviciTlily'ofthisarea…     

Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques

A reliable and accurate prediction of the tunnel boring machine(TBM) performance can assist in minimizing the relevant risks of high capital costs and in scheduling tunneling projects.This research aims to develop six hybrid models of extreme gradient boosting(XGB) which are optimized by gray wolf optimization(GWO), particle swarm optimization(PSO), social spider optimization(SSO), sine cosine algorithm(SCA), multi verse optimization(MVO) and moth flame optimization(MFO), for estimation of the TBM penetration rate(PR).To do this, a comprehensive database with 1286 data samples was established where seven parameters including the rock quality designation, the rock mass rating, Brazilian tensile strength(BTS), rock mass weathering, the uniaxial compressive strength(UCS), revolution per minute and trust force per cutter(TFC), were set as inputs and TBM PR was selected as model output.Together with the mentioned six hybrid models, four single models i.e., artificial neural network, random forest regression, XGB and support vector regression were also built to estimate TBM PR for comparison purposes.These models were designed conducting several parametric studies on their most important parameters and then, their performance capacities were assessed through the use of root mean square error, coefficient of determination, mean absolute percentage error, and a10-index.Results of this study confirmed that the best predictive model of PR goes to the PSO-XGB technique with system error of(0.1453, and 0.1325), R~2 of(0.951, and 0.951), mean absolute percentage error(4.0689, and 3.8115), and a10-index of(0.9348, and 0.9496) in training and testing phases, respectively.The developed hybrid PSO-XGB can be introduced as an accurate, powerful and applicable technique in the field of TBM performance prediction.By conducting sensitivity analysis, it was found that UCS, BTS and TFC have the deepest impacts on the TBM PR.     

内蒙古维拉斯托锡多金属矿石英脉形态分带定量分析

为探讨维拉斯托锡多金属矿床含锡石英脉形态分带的成矿动力学机制,通过利用分形和混合分布工具对断层脉带和上、下节理脉带进行定量分析。上、下节理脉带在脉厚、钨锡品位分形维数和混合筛分分布方面均具有相似性,暗示了两者可能具有相似的成矿机制。与上、下节理脉带相比,断层脉带的脉厚和钨锡品位分形维数均较小,断层脉带内的聚焦化流动、较低的脉体成核率、脉体叠加生长和矿化叠加富集可能是导致断层脉带的厚脉和富矿比例均高于上、下节理脉带的重要原因。     

Regional debris flow susceptibility analysis based on principal component analysis and self-organizing map: a case study in Southwest China

A method was developed to analyze the susceptibilities of 541 regional basins affected by debris flows at the Wudongde Dam site in southwest China. Determining susceptibility requires information on source material quantity and occurrence frequency. However, the large number of debris flows can hinder the individual field investigation in a each small basin. Factors that may trigger debris flows can be identified using remotely sensed interpretation information. Susceptibility analysis can then be conducted based on these factors. In this study, SPOT5 satellite imagery, digital elevation models (DEM), a lithology distribution map, and rainfall monitoring data were used to identify 12 debris flow trigger factors: basin relief ratio, slope gradient in the initiation zone, drainage density, downslope curvature of the main channel, vegetation coverage, main channel aspect, topographic wetness index, Melton’s ruggedness number, lithology, annual rainfall, form factor, and cross-slope curvature of the transportation zone. Principal component analysis was used to obtain the eight principal components of these factors that contribute to susceptibility results. Then, a self-organizing map method was adopted to analyze the principal components, which resulted in a debris flow susceptibility classification. Field validation of 26 debris flow basins was used to evaluate the errors of the susceptibility classification, as well as assess the causes of such errors. The study found that principle component analysis and self-organizing map methodologies are good predictors of basin susceptibility to debris flows.     

An approach to determination of phenolic compounds in seawater using SPME-GC-MS based on SWCNTs coating

Phenolic compounds have become one kind of the important pollutants of the marine environment. Single-walled Carbon nanotubes, as one-dimensional nano materials, have light weight and perfect hexagonal structure of connections, with many unusual mechanical, chemical and electrical properties. In recent years, with the research of carbon nanotubes and other nano materials, the application prospect is also constantly discussed. In this paper, homemade single-walled carbon nanotubes(SWCNTs) coating was used for establishing an analytical approach to the determination of five kinds of phenolic compounds in seawater using SPME-GC-MS. Optimal conditions: After saturation was conducted with Na Cl, and p H was adjusted to 2.0 with H_2SO_4, the extract was immersed in a water bath at 40 for GC℃-MS determination through 40-min agitating extraction at 500 rmin~(-1) and 3-min desorption at 280℃. The liniearities ranged between 0.01-100 μg L~(-1), and the determination limits ranged between 1.5-10 ngL~(-1). The relative standard deviation(RSD, n = 5) was less than 6.5%. For the phenolic compounds obtained from the spiked recovery test for actual seawater samples, the rates of recovery were 87.5%-101.7%, and the RSDs were less than 8.8%, which met the requirements of determination. Due to its simplicity, high efficiency and low consumption, this approach is suitable for the analysis of trace amounts of phenolic compounds in marine waters.