Varieties of approaches and algorithms have been presented to identify the distribution of elements. Previous researches based on the type of problem, categorized their data in proper clusters or classes. This means t...Varieties of approaches and algorithms have been presented to identify the distribution of elements. Previous researches based on the type of problem, categorized their data in proper clusters or classes. This means that the process of solution could be supervised or unsupervised. In cases, where there is no idea about dependency of samples to specific groups, clustering methods (unsupervised) are applied. About geochemistry data, since various elements are involved, in addition to the complex nature of geochemical data, clustering algorithms would be useful for recognition of elements distribution. In this paper, Self-Organizing Map (SOM) algorithm, as an unsupervised method, is applied for clustering samples based on REEs contents. For this reason the Choghart Fe-REE deposit (Bafq district, central Iran), was selected as study area and dataset was a collection of 112 lithology samples that were assayed with laboratory tests such as ICP-MS and XRF analysis. In this study, input vectors include 19 features which are coordinates x, y, z and concentrations of REEs as well as the concentration of Phosphate (P<sub>2</sub>O<sub>5</sub>) since the apatite is the main source of REEs in this particular research. Four clusters were determined as an optimal number of clusters using silhouette criterion as well as k-means clustering method and SOM. Therefore, using self-organizing map, study area was subdivided in four zones. These four zones can be described as phosphate type, albitofyre type, metasomatic and phosphorus iron ore, and Iron Ore type. Phosphate type is the most prone to rare earth elements. Eventually, results were validated with laboratory analysis.展开更多
This paper is devoted to application of ordinary kriging method in Choghart north anomaly iron ore deposit in Yazd province, Iran. In order to estimate the deposit, 2329 input data gained from 26 boreholes were used. ...This paper is devoted to application of ordinary kriging method in Choghart north anomaly iron ore deposit in Yazd province, Iran. In order to estimate the deposit, 2329 input data gained from 26 boreholes were used. Fe grade was selected as the major regional variable on which the present research has focused. All of the available data were changed to 12.5 m composites so that statistical regularization could be reached. Studies indicated that iron grade input data had single-population characteristics. To carry out ordinary kriging, a spherical model was fitted over empirical variogram. Then the model was verified through cross validation method and proved to be valid with a coherence coefficient of 0.773 between the estimated and real data. Plotting the empirical variogram in different directions showed no geometric anisotropy for the deposit. To estimate the Iron grade, ordinary kriging method was used according to which, all of the exploitable blocks with dimensions 20 m x 20 m x 12.5 m were block esti- mated within the estimation space. Finally tonnage-grade curve has been drawn and reserve classified into measured, indicated and inferred.展开更多
The present article is a review study on the types of rare earth elements(REEs),environmental and biological effects as well as the sources of emission of these elements as pollution in nature.The purpose of this stud...The present article is a review study on the types of rare earth elements(REEs),environmental and biological effects as well as the sources of emission of these elements as pollution in nature.The purpose of this study is to provide a vision in environmental planning and control of pollution caused by REEs.The evaluation of rare earth elements was studied in human life and its environmental and biological effects,which have particular importance and are entering the life cycle through industrial and mining pollution sources.Since mining activities intensify the dispersion of these elements in the environment and the existence of industrial factories located around urban drainage system plays a unique role in creating and spreading pollution caused by rare earth elements;As a result,two case studies were conducted on two mining and industrial areas.The first case is the Choghart mine in Yazd province as an example of mining pollution,and the second case study is performed on the Kor river as an example of industrial pollution which is caused by industrial activities around it,Then the results are well explained to show both two environments of litho and hydro.Due to this fact that produced environmental pollution can cause exchange pollutant compounds with the surrounding environment besides its long-lasting destructive effects;It can cause irreversible biological effects on living organisms.By targeting this evaluation,several techniques can be proposed to prevent the entry and dispersal of rare earth elements from pollution sources besides methods to reduce the damage of these elements to the ecosystem.展开更多
文摘Varieties of approaches and algorithms have been presented to identify the distribution of elements. Previous researches based on the type of problem, categorized their data in proper clusters or classes. This means that the process of solution could be supervised or unsupervised. In cases, where there is no idea about dependency of samples to specific groups, clustering methods (unsupervised) are applied. About geochemistry data, since various elements are involved, in addition to the complex nature of geochemical data, clustering algorithms would be useful for recognition of elements distribution. In this paper, Self-Organizing Map (SOM) algorithm, as an unsupervised method, is applied for clustering samples based on REEs contents. For this reason the Choghart Fe-REE deposit (Bafq district, central Iran), was selected as study area and dataset was a collection of 112 lithology samples that were assayed with laboratory tests such as ICP-MS and XRF analysis. In this study, input vectors include 19 features which are coordinates x, y, z and concentrations of REEs as well as the concentration of Phosphate (P<sub>2</sub>O<sub>5</sub>) since the apatite is the main source of REEs in this particular research. Four clusters were determined as an optimal number of clusters using silhouette criterion as well as k-means clustering method and SOM. Therefore, using self-organizing map, study area was subdivided in four zones. These four zones can be described as phosphate type, albitofyre type, metasomatic and phosphorus iron ore, and Iron Ore type. Phosphate type is the most prone to rare earth elements. Eventually, results were validated with laboratory analysis.
基金the National Natural Science Foundation of China (Nos. 40772192 and 40372123)the Key Laboratory Project of Deep Rock Mechanics (No.PD1011)
文摘This paper is devoted to application of ordinary kriging method in Choghart north anomaly iron ore deposit in Yazd province, Iran. In order to estimate the deposit, 2329 input data gained from 26 boreholes were used. Fe grade was selected as the major regional variable on which the present research has focused. All of the available data were changed to 12.5 m composites so that statistical regularization could be reached. Studies indicated that iron grade input data had single-population characteristics. To carry out ordinary kriging, a spherical model was fitted over empirical variogram. Then the model was verified through cross validation method and proved to be valid with a coherence coefficient of 0.773 between the estimated and real data. Plotting the empirical variogram in different directions showed no geometric anisotropy for the deposit. To estimate the Iron grade, ordinary kriging method was used according to which, all of the exploitable blocks with dimensions 20 m x 20 m x 12.5 m were block esti- mated within the estimation space. Finally tonnage-grade curve has been drawn and reserve classified into measured, indicated and inferred.
文摘The present article is a review study on the types of rare earth elements(REEs),environmental and biological effects as well as the sources of emission of these elements as pollution in nature.The purpose of this study is to provide a vision in environmental planning and control of pollution caused by REEs.The evaluation of rare earth elements was studied in human life and its environmental and biological effects,which have particular importance and are entering the life cycle through industrial and mining pollution sources.Since mining activities intensify the dispersion of these elements in the environment and the existence of industrial factories located around urban drainage system plays a unique role in creating and spreading pollution caused by rare earth elements;As a result,two case studies were conducted on two mining and industrial areas.The first case is the Choghart mine in Yazd province as an example of mining pollution,and the second case study is performed on the Kor river as an example of industrial pollution which is caused by industrial activities around it,Then the results are well explained to show both two environments of litho and hydro.Due to this fact that produced environmental pollution can cause exchange pollutant compounds with the surrounding environment besides its long-lasting destructive effects;It can cause irreversible biological effects on living organisms.By targeting this evaluation,several techniques can be proposed to prevent the entry and dispersal of rare earth elements from pollution sources besides methods to reduce the damage of these elements to the ecosystem.
