苏州阳西高岭土矿床氢氧稳定同位素特征

苏州阳西南岭土矿床按成因可分为脉岩型高岭土及溶洞充填型高岭土.高岭土的氢氧稳定同位素组成变化大,取决于样品的采集部位.在δD—δ~(18)O相关图上,以δ~(18)O=19‰为界,可分为A、B两区.脉岩型的残斑状高岭土氢氧同位素组成位于A区(δ~(18)O<19‰);而溶洞充填型的致密块状高岭土的氢氧同位素组成位于B区(δ~(18)O>19‰).据此可以认为脉岩型高岭土以热液成矿作用为主,溶洞充填型高岭土以风化淋滤作用为主.并分别在成矿后又受到了后期作用的叠加改造.     

Novel Extreme Learning Machine-Multi-Verse Optimization Model for Predicting Peak Particle Velocity Induced by Mine Blasting

Natural Resources Research - Peak particle velocity (PPV) is an important criterion for assessing the risk level of ground vibration induced by mine blasting. Based on this criterion, many efforts...     

A Thermodynamics-Based Model on the Internal Erosion of Earth Structures

The present paper describes a model of internal erosion of earth structures, based on rigorous thermodynamic principles and the theory of porous media. A particular focus of this paper is concerned with the initial stage of internal erosion, when the pore volume forms a continuous network, without the formation of macroscopic cavities or channels. The continuum approach is applicable in this case. The soil skeleton saturated by a pore fluid is treated as the superposition of three continua in interaction, with independent velocity fields. The pore fluid itself consists of a mixture of water and eroded particles. The erosion kinetics is based on the shear stress developed at the solid–fluid interface. The applicability of the model is illustrated by numerical simulations based on the finite element method. These simulations show how the phenomenon of piping can progressively arise, and preferentially in regions where hydraulic gradients are critical. Effects of mechanical degradations due to internal erosion are at the same time demonstrated.     

Spatial prediction of rainfall-induced shallow landslides using hybrid integration approach of Least-Squares Support Vector Machines and differential evolution optimization: a case study in Central Vietnam

This study represents a hybrid intelligence approach based on the differential evolution optimization and Least-Squares Support Vector Machines for shallow landslide prediction, named as DE–LSSVM_SLP. The LSSVM is used to establish a landslide prediction model whereas the DE is adopted to search the optimal tuning parameters of the LSSVM model. In this research, a GIS database with 129 historical landslide records in the Quy Hop area (Central Vietnam) has been collected to establish the hybrid model. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to assess the performance of the newly constructed model. Experimental results show that the proposed model has high performances with approximately 82% of AUCs on both training and validating datasets. The model’s results were compared with those obtained from other methods, Support Vector Machines, Multilayer Perceptron Neural Networks, and J48 Decision Trees. The result comparison demonstrates that the DE–LSSVM_SLP deems best suited for the dataset at hand; therefore, the proposed model can be a promising tool for spatial prediction of rainfall-induced shallow landslides for the study area.     

iGeoTrans – a novel iOS application for GPS positioning in geosciences

The iGeoTrans is an iOS application designed for navigation purposes for iPhone, iPad and iPod Touch. This application uses Global Positioning System (GPS), Assisted GPS system, GLONASS, Wi-Fi and Cellular Network for positioning. The iGeoTrans has included datum transformations and map projections that enable users to convert the collected data between different coordinate systems for almost all areas in the world. In addition, other features are also included such as distance, area measurements, and GPS results could be exported to the AutoCad dxf format for GIS softwares. The average horizontal and vertical root mean square errors (RMSEs) for the static test are around 4.11 and 3.51?m, respectively. The horizontal RMSE for the dynamic outdoor test is around 2.72?m. The iGeoTrans application can be used to support surveying, mapping and geosciences fieldworks for any area in the world.     

Regional‐scale investigation of the spatial distribution and origin of soluble salts in central north Queensland

A method for regional assessment of the distribution of saline outbreaks is demonstrated for a large area (68 000 km²) in north Queensland, Australia. Soil samples were used in conjunction with a digital elevation model and a map of potentially saline discharge zones to examine the landscape distribution of soluble salts in the region. The hypothesis of atmospheric accession of salt was tested for the topographically defined catchment regions feeding into each potentially saline discharge area. Most catchments showed a salt distribution consistent with this hypothesis, i.e. %TSS was large near the discharge areas and decreased rapidly with distance uphill from the discharge areas. In some catchments, however, local saline outbreaks were apparent at significant distances uphill from discharge areas. The possibility of geological sources of this salt was examined by comparing random point distributions with the location of saline points with distance downhill from geological units (excluding points near discharge zones). The distribution of some saline outbreaks was consistent with the occurrence of Cambro‐Ordovician metasediments, Devonian limestone, Upper Devonian–Lower Carboniferous volcanics, and Triassic sediments. Copyright © 2000 John Wiley & Sons, Ltd.     

Morphological Change in the Northern Red River Delta,Vietnam

Coastal erosion has become a worldwide concern, typically in the densely populated Asian mega-river deltas. Severe coastal erosion in the southern Red River Delta(RRD) has been intensively studied. Coastal morphological change in the northern RRD was examined in detail through DEM(Digital Elevation Model) analysis based on time series of bathymetrical maps(1965–2004) and Landsat images(1975–2015) in this study. The results show that the northern RRD is featured by rapid coastal accretion in the past few decades, although suspended sediment flux has dropped by roughly 60% after the completeness of Hoa Binh Dam(HBD) in 1988 and relative sea level rose at 1.9 mm yr~(-1). However, accretion at the outer part of subtidal shoals and platforms was observed to slow down quickly or even turned into erosion in the last two decades. The resuspended sediments from the erosion zone can be transported landward to replenish the inner coastal zone, keeping the latter accretion in the near future to compensate for the sediment discharge decrease from the river. However, this lag effect should be terminated soon if other adverse effects go worse, e.g., damming rivers, sea-level rising, strengthening storms, land reclamation and other poor-designed coastal engineering. Coastal planners and managers should pay full attention to these changes.     

Detection of clusters in traffic networks based on spatio‐temporal flow modeling

Spatio‐temporal clustering is a highly active research topic and a challenging issue in spatio‐temporal data mining. Many spatio‐temporal clustering methods have been designed for geo‐referenced time series. Under some special circumstances, such as monitoring traffic flow on roads, existing methods cannot handle the temporally dynamic and spatially heterogeneous correlations among road segments when detecting clusters. Therefore, this article develops a spatio‐temporal flow‐based approach to detect clusters in traffic networks. First, a spatio‐temporal flow process is modeled by combining network topology relations with real‐time traffic status. On this basis, spatio‐temporal neighborhoods are captured by considering traffic time‐series similarity in spatio‐temporal flows. Spatio‐temporal clusters are further formed by successive connection of spatio‐temporal neighbors. Experiments on traffic time series of central London's road network on both weekdays and weekends are performed to demonstrate the effectiveness and practicality of the proposed method.     

Prediction of Blast-Induced Ground Vibration Intensity in Open-Pit Mines Using Unmanned Aerial Vehicle and a Novel Intelligence System

Natural Resources Research - Predicting and reducing blast-induced ground vibrations is a common concern among engineers and mining enterprises. Dealing with these vibrations is a challenging issue...     

A Novel Artificial Intelligence Approach to Predict Blast-Induced Ground Vibration in Open-Pit Mines Based on the Firefly Algorithm and Artificial Neural Network

Natural Resources Research - The primary purpose of this study was to develop a novel hybrid artificial intelligence model, with a robust performance, to predict ground vibration induced by bench...