Relationship between polar motion and key hydrological elements at multiple scales

Science China Earth Sciences - Changes in the elements of the Earth system are closely related. Finding the key factors linked with hydrological changes is significant for in-depth analysis of...     

汉南杂岩体袁家沟辉长岩锆石U-Pb年龄及构造意义

袁家沟辉长岩体位于陕西省西乡县白勉峡镇,是汉南杂岩体白勉峡超单元的组成部分.本次研究对袁家沟辉长岩锆石U-Pb年龄,地球化学特征进行了研究.辉长岩的成岩年龄为905±11 Ma,源区继承性锆石年龄为984±4 Ma.岩石地球化学特征显示,袁家沟辉长岩w(SiO2)为49.70％～51.38％,w(K2O)为0.78％～1.27％,属于钙碱性系列.辉长岩中大离子亲石元素富集,稀土含量为143.12～240.72×10-6,稀土含量中等.LREE/HREE的比值为1.46～2.04,平均值为1.73,轻重稀土分馏程度较弱.辉长岩的源区为岩石圈地幔—混合软流圈地幔区域,表现出壳幔混合的特征,形成于火山岛弧环境.     

粉末压片-波长色散X射线荧光光谱法测定地球化学样品中氯的方法研究

在对比已有相关分析方法的基础上,建立了粉末压片-波长色散X射线荧光光谱法测定地球化学样品中氯元素的分析方法.采用岩石、沉积物和土壤等78种国家一级地球化学标准物质作为校准系列建立校准曲线;利用经验系数法进行基体效应校正,利用含量校正法进行谱线重叠干扰校正;总结了地球化学样品中氯元素测定值随测定次数的变化规律及原因.结果表明:氯的检出限为7.95μg/g;分析3种国家一级地球化学标准物质12次,得到测定值的相对标准偏差均小于10％;采用国家一级地球化学标准物质验证方法准确度,测定值与标准物质认定值相吻合,测定平均值与标准物质认定值的对数差值的绝对值(?lgω)均小于或等于0.02,满足多目标区域地球化学调查规范的要求.     

XRF半定量分析技术在矿石光片鉴定中的应用

偏光显微镜反光镜下鉴定金属矿物是最常用、最快捷有效的方法,然而鉴定结果容易受到鉴定者主观因素或磨片情况的影响。为了更快速、准确地在反光镜下鉴定矿物,利用XRF半定量分析技术快速、无损、前处理简单等特点,以及磨平抛光的矿石矿物在半定量分析过程中能较好地避免楔入效应和阴影效应的有利因素,采取了先用XRF半定量分析测得的结果去反推矿物,再在显微镜下鉴定矿物的方法。以多金属硫化物矿石、含铀多金属矿石及含微量铀的矿石样品为例进行鉴定,结果表明,在鉴定前知道光片上的元素及其质量分数,通过地球化学方法和经验法反推矿物,结合显微镜观察需要鉴定的矿物,可有效避免忽略掉透明/半透明矿物（锡石）、小粒径矿物（沥青铀矿）、易混淆矿物（铀黑）,提高光片鉴定工作的效率和准确性。     

“Source to Sink”: A Review of Tectonics-Erosion-Sedimentation Interactions in the Analogue Experiments of Accretionary WedgeEI北大核心CSCD

It is believed that the tectonics-erosion-sedimentation interaction in the analogue experiments was essentially improved by the theory of “from source to sink”. In particular, the widespread uplift and exhumation in the western China occurred in Cenozoic can be considered to be a typical natural laboratory in the world. Here we review our current understanding from tectonic sandbox models of tectonics-erosion-sedimentation and their interactions, as well as from natural laboratory. As we known, there are widespread erosion occurred predominantly at hinterland of the accretionary wedge, in contrast to the sedimentation occurred widely at foreland of the wedge. Therefore, fold-and-thrust belts with low syntectonic sedimentation and erosion would evolve in a self-similar fashion to produce a narrow accretionary wedge, while high syntectonic sedimentation and erosion would produce accretionary wedge with very active hinterland thrusts, and a large width. Furthermore, the critically tapered wedge model suggests that the crust-scale thrust-and-fold belts under a horizontal compressive force would come into a self-similar growth of a forward-tapering wedge when it reaches a critical taper angle of the combined angles of the base dip and the wedge slope. Such a process has important influence on the tectonics-erosion- sedimentation and their interactions both in accretionary wedges and their analogue experiments. Although there is a significant similarity between the analogue experiments and natural accretionary wedges in the surface processes of tectonics- erosion-sedimentation and their interactions, it is difficult to get more universal parameters between them. It should be noted that sandbox models of the accretionary wedges in the natural laboratory would improve significantly our understanding of the theory of the tectonics-erosion-sedimentation interactions and “from source to sink”. © 2018, Science Press. All right reserved.     

Research Progress of Relative Humidity and Its Changing Annual Cycle

Studies on the characteristics of relative humidity annual cycle change include the frequency, phase, and amplitude of the time series and their changes. The effective diagnosis of the relative humidity annual cycle can provide important help in the monitoring and regulation of seasonal haze, the spatial distribution of epidemic outbreaks and their prevention and control, and the real-time forecasting and decision-making of monsoon precipitation. Different from studies on the trend of the relative humidity, the diagnosis in the annual cycle is scarce. This paper summarized the research status of relative humidity and its annual cycle, introduced several current methods for extracting common signals, and evaluated the feasibility of these methods for extracting annual cycle signals. Due to the time-varying characteristics of the annual cycle of relative humidity and complex structures such as asymmetric triangular waves, square-like waves, and state transients, harmonic-based extraction methods are difficult to succeed. The nonlinear signal extraction method with high noise immunity will solve this problem. At present, the relative humidity annual cycle studies urgently need to be improved and improve the quality of relative humidity observation data, accurately extract and quantify the time-varying characteristics and complex structure of the annual cycle. Moreover, combining the dynamic process and statistical analysis, we also need to study the physical mechanism of the change of relative humidity annual cycle (frequency, phase, amplitude, etc.) in China.     

Prediction of landslide displacement with an ensemble-based extreme learning machine and copula models

Research on the dynamics of landslide displacement forms the basis for landslide hazard prevention. This paper proposes a novel data-driven approach to monitor and predict the landslide displacement. In the first part, autoregressive moving average time series models are constructed to analyze the autocorrelation of landslide triggering factors. A linear ensemble-based extreme learning machine using the least absolute shrinkage and selection operator is applied in predicting the displacement of landslides. Five benchmarking data-driven models, the support vector machine, neural network, random forest, k-nearest neighbor, and the classical extreme learning machine, are considered as baseline models for validating the ensemble-based extreme learning machines. Numerical experiments demonstrated that the proposed prediction model produces the smallest prediction errors among all the algorithms tested. In the second part, parametric copula models are fitted on the predicted displacement, to investigate the relationship between the triggering factors and landslide displacement values. The Gumbel-Hougaard copula model performs best, which indicates strong upper tail correlation between the triggering factors and displacement values. Thresholds for the triggering factors can be obtained by monitoring the landslide moving patterns with large displacement values. The effectiveness and utility of the proposed data-driven approach have been confirmed with the landslide case study in the region of the Three Gorges Reservoir.     

The investigation of ultra-long-distance concrete pipe stuck in quartz sandstone formation using numerical simulation

During mountainous area construction by long-distance pipe jacking, the pipe stuck encountered. To reveal the cause of the pipe stuck, this paper investigates the pipe surface frictional resistance corresponding to different burial depths and surrounding rock parameters by ADINA finite element analysis. Parameter sensitivity analysis results show that the cohesion effect on the frictional resistance was small, the frictional resistance tended to decrease markedly with the increasing other rock mechanical parameters and the decreasing burial depth and friction coefficient of the pipes. After continuing to consider the prerequisite of simultaneously changing the elastic modulus, internal friction angle and burial depth conditions, a solution of the maximum number of pipes driven by a single intermediate jacking station (IJS) was reduced from 59 to 40 was proposed based on an integration of simulations with the field monitoring results. Finally, the pipe jacking project was successfully completed after adopting the improvement proposals.     

An adaptive method for clustering spatio‐temporal events

The clustering of spatio‐temporal events has become one of the most important research branches of spatio‐temporal data mining. However, the discovery of clusters of spatio‐temporal events with different shapes and densities remains a challenging problem because of the subjectivity in the choice of two critical parameters: the spatio‐temporal window for estimating the density around each event, and the density threshold for evaluating the significance of clusters. To make the clustering of spatio‐temporal events objective, in this study these two parameters were adaptively generated from statistical information about the dataset. More precisely, the density threshold was statistically modeled as an adjusted significance level controlled by the cardinality and support domain of the dataset, and the appropriate sizes of spatio‐temporal windows for clustering were determined by the spatio‐temporal classification entropy and stability analysis. Experiments on both simulated and earthquake datasets were conducted, and the results show that the proposed method can identify clusters of different shapes and densities.