An implementation of rock engineering system for ranking the instability potential of natural slopes in Greek territory. An application in Karditsa County

This paper presents an application of rock engineering system (RES) in an attempt to reveal and assess the inherent instability potential of 388 sites where equivalent landslides have been manifested and recorded in the region of Karditsa County, Greece. The main objective has been defining the principal causative and triggering factors responsible for the manifestation of landslide phenomena, quantify their interactions, obtain their weighted coefficients, and calculate the instability index, which refers to the inherent potential instability of each natural slope of the examined region. From the statistical interpretation of the data reported in a well-documented database and concerning the examined failure sites, a clear correlation between the instability index and the area affected by a single landslide event has been revealed. Almost the entire failure sites, 98% of the examined slope sites, exhibit an instability index value over 55, a value which is thought to be a critical threshold for landslide manifestation concerning natural slopes in Karditsa County. It is argued that the presented RES methodology, engaging the selected set of parameters, could be considered as an effective expert's tool for ranking, in an objectively optimal and simple way, the instability potential of natural slopes in Karditsa County, and thus providing a tool for sound zoning landslide hazard.     

A New Algorithm for Wind-Vector Retrieval From Scatterometers

A new efficient algorithm for retrieving wind-vector solutions from scatterometers is developed based on a criterion of minimum normalized standard deviation (NSD) of wind speed derived from backscatter measurements using a geophysical model function (GMF). Its performance has been evaluated through simulations using QSCAT-1 GMF and the QuikSCAT observational geometry. The present algorithm, named the NSD algorithm, is found to be computationally more efficient (two to three times) besides being at par with the maximum-likelihood estimator (MLE) algorithm in terms of retrieval skill, retrieval errors, and distribution of solutions, on the basis of simulations as well as comparison of limited QuikSCAT-data-derived winds with National Centers for Environmental Prediction and European Centre for Medium-Range Weather Forecasts model winds. Simulation results and analysis of sample QuikSCAT data are presented.      

磷处理粉煤灰可作农业土壤磷源

粉煤灰(简称CCP或ash)具有改良土壤,增加植物产量的功能。此外,由于它特殊的多孔结构,也可用作吸纳并承载植物养分的载体。用NaH2PO4配制成含磷0.10mol/L浓度的溶液,对采自加拿大西安大略省Sarnia地区Lambton电厂的底灰(bottomash)进行振荡浸渍处理。结果表明,振荡浸渍66h后的粉煤灰中磷含量可达784×10-6。以磷处理粉煤灰、未进行磷处理的粉煤灰和石英砂按比例混合,作为基本生长介质进行玉米种植实验,其中实验配方设计为生长介质中含磷量分别为标准含磷浓度(50×10-6)的10%、25%、50%、75%和100%。生长26、34和46d后分别与不含磷的空白配方、施加含氮-磷-钾为0-20-0标准磷肥并控制磷含量为标准浓度(50×10-6)配方进行生物产量对比。生长实验结果表明,以磷处理粉煤灰供磷的生长介质,当含磷量为标准浓度的25%至100%时,其植物生长量就比添加标准浓度磷肥的配方好。种植46d后的生物生长量统计结果显示,含磷分别为标准浓度50%、75%和100%的实验介质中,玉米杆的鲜重较施标准磷肥介质中玉米分别增长39.46%、42.73%和46.13%;玉米杆干重依次增加29.71%、13.39%和28.87%;根鲜重平均增加16.62%;根干重平均增加14.03%。上述实验结果启示,粉煤灰可以很好地吸纳承载磷养分,并持续供给植物吸收生长,如果采用吸纳磷(或其他养分)的粉煤灰改良砂质土壤将有重要意义。     

A combined mathematical geophysical model for prediction of pyrite oxidation and pollutant leaching associated with a coal washing waste dump

The waste produced by coal washing process produces many environmental problems. In this study, the pollution problems associated with the waste produced by Alborz Sharghi Coal Washing Plant was investigated by mathematical modeling. The study area is located at 11 km. to Razmjah coal region and 45 km. to Tehran-Mashhad road in the north part od Iran. To achieve the goal, a few samples were taken from different depths at three points on the waste dump in order to investigate pyrite oxidation and pollution generation. The samples were then analysed, using an AA-670 Shimadzu atomic absorption to determine the fraction of pyrite remained within the waste particles. A numerical finite volume model using Phoenics package has been developed to simulate pyrite oxidation and pollution generation from the Alborz Sharghi coal washing waste dump. The pyrite oxidation reaction is described by the shrinking-core model. Gaseous diffusion is the main mechanism for the transport of oxygen through the waste. The results of numerical modelling were compared with the field observations and close agreement was achieved. A simple mathematical model incorporating advection and hydrodynamic dispersion processes was also presented in order to verify the results of geophysical time-laps method showing transportation of the pollutants through the downstream of the waste dump. Both mathematical model and geophysical time-laps method are agreed in the identification of pollutant transport emanated from the waste dump. The results of such investigations can be used for designing an effective environmental management program.     

First finds of Late Tithonian and middle-late Albian radiolarian assemblages in volcanogenic-siliceous rocks of the Amur River right lower reaches and their tectonic significance

The lithological-stratigraphic study of volcanogenic-siliceous rocks developed on the left side of the Machtovaya River, a right tributary of the Amur River, yielded the first radiolarian assemblages of the late Late Tithonian, the late Late Tithonian-early Valanginian, and the middle-late Albian age. It is established that the stratigraphic succession of volcanogenic-siliceous rocks in this area is composed of upper Tithonian-Valanginian dark red to red-brown cherts with basalts in the lower part of the section and Albian dark gray clayey cherts, olive-gray siliceous-tuffaceous argillites, and tufaceous siltstones in its upper part. The replacement of cherts by their clayey varieties likely occurred in the Aptian. The composition, structure, and age of these strata and the rocks constituting the Kiselevka-Manoma accretionary complex are different, which indicates their different tectonic origin.     

Geochemistry of magmatic rocks of the Koksharovka alkaline-ultrabasic massif,primorye, and results of trace-element modeling

New geochemical data are presented on the magmatic rocks of the Late Jurassic Koksharovka alkaline-ultrabasic massif, which is associated with deposits of vermiculite, apatite, V-bearing titanomagnetite, and placer isoferroplatinum. The REE geochemistry and strontium, oxygen, and carbon isotopic composition of carbonatites and related ijolites and pyroxenites, together with geological observations, point to the magmatic origin of the Koksharovka carbonatites. The origin of associated magmatic rocks is discussed. Trace element modeling of partial melting of mantle sources was conducted to decipher the genesis of the melts of the Koksharovka carbonatites and host titanite-kaersutite pyroxenites.     

A new concept of pedogenic nodule formation in landscapes of the Russian Far East

The typification of ferromanganese nodules (FMN) formed in subaqueous and subaerial settings and in residual materials, as well as FMN localization in various sediments and soils, is discussed. The genetic diversity of morphologically similar FMN and the transformation of FMN-bearing complexes with changes in landscapes have been established.     

Paleomagnetic studies of the Late Mesozoic deformation stage in the southern Primorye region

The analysis of paleomagnetic data available for the southern Primiorye region revealed that the studied objects were magnetized under regional remagnetization presumably during the Late Mesozoic folding and this magnetization can be interpreted as being synfolding. The interpretation is based on the parameter that characterizes the folding completion degree immediately before regional remagnetization. It is shown that the relaxation of Late Mesozoic horizontal stresses was irregular. The obtained estimates of the degree of folding completion are consistent with the available geological data and Talitskii’s model for tectonic deformations.     

Using Sequential Self-Calibration Method to Identify Conductivity Distribution: Conditioning on Tracer Test data

An iterative inverse method, the sequential self-calibration method, is developed for mapping spatial distribution of a hydraulic conductivity field by conditioning on nonreactive tracer breakthrough curves. A streamline-based, semi-analytical simulator is adopted to simulate solute transport in a heterogeneous aquifer. The simulation is used as the forward modeling step. In this study, the hydraulic conductivity is assumed to be a deterministic or random variable. Within the framework of the streamline-based simulator, the efficient semi-analytical method is used to calculate sensitivity coefficients of the solute concentration with respect to the hydraulic conductivity variation. The calculated sensitivities account for spatial correlations between the solute concentration and parameters. The performance of the inverse method is assessed by two synthetic tracer tests conducted in an aquifer with a distinct spatial pattern of heterogeneity. The study results indicate that the developed iterative inverse method is able to identify and reproduce the large-scale heterogeneity pattern of the aquifer given appropriate observation wells in these synthetic cases.     

Automated Kerogen Classification in Microscope Images of Dispersed Kerogen Preparation

We develop the classification part of a system that analyses transmitted light microscope images of dispersed kerogen preparation. The system automatically extracts kerogen pieces from the image and labels each piece as either inertinite or vitrinite. The image pre-processing analysis consists of background removal, identification of kerogen material, object segmentation, object extraction (individual images of pieces of kerogen) and feature calculation for each object. An expert palynologist was asked to label the objects into categories inertinite and vitrinite, which provided the ground truth for the classification experiment. Ten state-of-the-art classifiers and classifier ensembles were compared: Naïve Bayes, decision tree, nearest neighbour, the logistic classifier, multilayered perceptron (MLP), support vector machines (SVM), AdaBoost, Bagging, LogitBoost and Random Forest. The logistic classifier was singled out as the most accurate classifier, with an accuracy greater than 90. Using a 10 times 10-fold cross-validation provided within the Weka software, we found that the logistic classifier was significantly better than five classifiers (p<0.05) and indistinguishable from the other four classifiers. The initial set of 32 features was subsequently reduced to 6 features without compromising the classification accuracy. A further evaluation of the system alerted us to the possible sensitivity of the classification to the ground truth that might vary from one human expert to another. The analysis also revealed that the logistic classifier made most of the correct classifications with a high certainty.