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Pastukhov, A.M.; Rychkov, V.N.; Smirnov, A.L.; Skripchenko, S.Y.; Poponin, N.A. |
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Title |
Purification of in situ leaching solution for uranium mining by removing solids from suspension |
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Journal Article |
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Year |
2014 |
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Minerals Engineering |
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55 |
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1-4 |
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Bag filter, Firm particles, In situ leaching mining, Injection wells, Intake capacity, Purification |
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Abstract |
This study investigated the process of in situ leaching (ISL) method of uranium mining, and the removal of solid particles from the leaching solution. Investigations were carried out for 4months. The content of firm suspensions in the productive solutions arriving from the well field was up to standard of 3–5mg/l. After keeping in a settler of productive solutions within one hour concentration of suspensions decreases to 2–2.5mg/l. To increase the life of the wells requires more fine purification of the ISL solutions. The best results can be obtained but using filtration. Bag filters were used in experiments carried out at the extraction site. All samples of polypropylene bag filter was produced by the Tamfelt Corporation. The best results were obtained for fabrics S-51M03-L2K4 (pore size 3μm). After three month of trials following indicators of wells work were fixed: on the trial cell decrease in intake capacity did not occur; on the other cells of well field injectability of holes for the same period of time decreased for 15–40%. The results illustrated the high efficiency of this method, which allows injection wells to reach a constant intake capacity, making it possible for technological cells to achieve a constant productivity and balance. Purification of solutions allows to reduce acidulation term of new technological cells from 3–4 to 1.5–2months. |
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0892-6875 |
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THL @ christoph.kuells @ pastukhov_purification_2014 |
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204 |
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Ren, Y.; Yang, X.; Hu, X.; Wei, J.; Tang, C. |
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Title |
Mineralogical and geochemical evidence for biogenic uranium mineralization in northern Songliao Basin, NE China |
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Journal Article |
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2022 |
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Ore Geology Reviews |
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141 |
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104556 |
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Bacterial sulfate reduction, In-situ S isotope of pyrite, Northern Songliao basin, Sandstone-type uranium deposit, Sifangtai Formation |
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The sandstone-hosted uranium mineralization areas in the Sanzhao Sag of the northern Songliao Basin have been newly identified. The target stratum is the Upper Cretaceous Sifangtai Formation and the uranium mineralization mainly occurs in the bottom of Sifangtai Formation, corresponding to channel sand bodies in meandering river system, characterized by medium to fine-grained sandstone. This study proposes the uranium metallogenic model through petrographic observation, whole rock geochemistry, mineralogical study of uranium occurrence form (SEM), organic matter rock–eval pyrolysis analysis (REP) and in-situ sulfur isotope determination of different generations of pyrite by LA-MC-ICP-MS. Compared with the sandstones collected in barren reduction and oxidization zones, the mineralized sandstones show obvious increase in the contents of TOC, total sulfur, Y and U. Petrographic observations indicate that organic matters are mainly inherited from land plants. REP data display that the organic matter (OM) disseminated in the sandstone has very low hydrogen index (HI) from around 0 to 21 mg HC/g TOC and varied oxygen index (OI) from 44 to 115 mg CO2/g TOC, corresponding to Type Ⅳ kerogen (degraded kerogen). There are two types of coffinite with different grain size, micro-particles (μm-sized) and large aggregates (generally up to 100 μm) respectively. The coffinite micro spherules exhibit short rod-like or worm-like morphology occurring in clay matrix and cell cavities in degradofusinite or around subidiomorphic-idiomorphic pyrite. The coarse-grained coffinite contains other mineral facies (e.g. pyrite, quartz) and some of large coffinite aggregates display thrombolite-type microbial structures. The irregular pyrite relict particles in coarse-grained colloidal coffinite have light sulfur isotope compositions characterized by δ34S values from –39.96‰ to –49.89‰. The δ34S values of colloidal pyrite in replacement of OM or of the sub-idiomorphic FeS2 cement filling in the cavities of OM range from –52.77‰ to –13.88‰. Some of sub-idiomorphic pyrite cement and idiomorphic crystal have the heavier signature from – 27.06‰ to + 14.23‰. The light sulfur isotope signature suggests that the sulfur originates from bacterial sulfate reduction (BSR). The OM replacement by pyrite and the highest OI values recorded by REP in uranium mineralized samples are lines of evidence of biodegradation. Bacteria use the organic matter as food source and produce isotopically light reduced sulfur species. Oxygenated uranium-bearing waters infiltrated through the denudated windows at Daqing placanticline into the porous reduced sandstones deposited in the Sanzhao Sag. Uranium was indirectly reduced by BSR-derived iron disulfides or directly reduced by sulfate-reducing bacteria. |
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0169-1368 |
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THL @ christoph.kuells @ ren_mineralogical_2022 |
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144 |
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Jroundi, F.; Descostes, M.; Povedano-Priego, C.; Sánchez-Castro, I.; Suvannagan, V.; Grizard, P.; Merroun, M.L. |
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Profiling native aquifer bacteria in a uranium roll-front deposit and their role in biogeochemical cycle dynamics: Insights regarding in situ recovery mining |
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Journal Article |
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2020 |
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Science of The Total Environment |
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721 |
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137758 |
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Keywords |
Bacterial diversity, Bioremediation, In-situ recovery, Natural attenuation, Network analysis, Uranium |
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A uranium-mineralized sandy aquifer, planned for mining by means of uranium in situ recovery (U ISR), harbors a reservoir of bacterial life that may influence the biogeochemical cycles surrounding uranium roll-front deposits. Since microorganisms play an important role at all stages of U ISR, a better knowledge of the resident bacteria before any ISR actuations is essential to face environmental quality assessment. The focus here was on the characterization of bacteria residing in an aquifer surrounding a uranium roll-front deposit that forms part of an ISR facility project at Zoovch Ovoo (Mongolia). Water samples were collected following the natural redox zonation inherited in the native aquifer, including the mineralized orebody, as well as compartments located both upstream (oxidized waters) and downstream (reduced waters) of this area. An imposed chemical zonation for all sensitive redox elements through the roll-front system was observed. In addition, high-throughput sequencing data showed that the bacterial community structure was shaped by the redox gradient and oxygen availability. Several interesting bacteria were identified, including sulphate-reducing (e.g. Desulfovibrio, Nitrospira), iron-reducing (e.g. Gallionella, Sideroxydans), iron-oxidizing (e.g. Rhodobacter, Albidiferax, Ferribacterium), and nitrate-reducing bacteria (e.g. Pseudomonas, Aquabacterium), which may also be involved in metal reduction (e.g. Desulfovibrio, Ferribacterium, Pseudomonas, Albidiferax, Caulobacter, Zooglea). Canonical correspondence analysis (CCA) and co-occurrence patterns confirmed strong correlations among the bacterial genera, suggesting either shared/preferred environmental conditions or the performance of similar/complementary functions. As a whole, the bacterial community residing in each aquifer compartment would appear to define an ecologically functional ecosystem, containing suitable microorganisms (e.g. acidophilic bacteria) prone to promote the remediation of the acidified aquifer by natural attenuation. Assessing the composition and structure of the aquifer’s native bacteria is a prerequisite for understanding natural attenuation and predicting the role of bacterial input in improving ISR efficiency. |
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0048-9697 |
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THL @ christoph.kuells @ jroundi_profiling_2020 |
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177 |
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Pereira, A.J.S.C.; Neves, L.J.P.F. |
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Estimation of the radiological background and dose assessment in areas with naturally occurring uranium geochemical anomalies—a case study in the Iberian Massif (Central Portugal) |
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2012 |
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Journal of Environmental Radioactivity |
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112 |
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96-107 |
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Background, Dose assessment, Geochemical anomalies, Mine remediation, Natural radioactivity, Uranium |
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Naturally occurring uranium geochemical anomalies, representative of the several thousand recognized in the Portuguese section of the Iberian Massif and outcropping in three target areas with a total of a few thousand square metres, were subjected to a detailed study (1:1000 scale) to evaluate the radiological health-risk on the basis of a dose assessment. To reach this goal some radioactive isotopes from the uranium, thorium and potassium radioactive series were measured in 52 samples taken from different environmental compartments: soils, stream sediments, water, foodstuff (vegetables) and air; external radiation was also measured through a square grid of 10×10m, with a total of 336 measurements. The results show that some radioisotopes have high activities in all the environmental compartments as well as a large variability, namely for those of the uranium decay chain, which is a common situation in the regional geological setting. Isotopic disequilibrium is also common and led to an enrichment of several isotopes in the different pathways, as is the case of 226Ra; maximum values of 1.76BqL−1 (water), 986Bqkg−1 (soils) and 18.9Bqkg−1 (in a turnip sample) were measured. On the basis of a realistic scenario combined with the experimental data, the effective dose from exposure to ionizing radiation for two groups of the population (rural and urban) was calculated; the effective dose is variable between 8.0 and 9.5mSvyear−1, which is 3–4 times higher than the world average. Thus, the radiological health-risk for these populations could be significant and the studied uranium anomalies must be taken into account in the assessment of the geochemical background. The estimated effective dose can also be used as typical of the background of the Beiras uranium metalogenetic province and therefore as a “benchmark” in the remediation of the old uranium mining sites. |
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0265-931x |
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THL @ christoph.kuells @ pereira_estimation_2012 |
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129 |
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Singh, A.; Patel, S.; Bhadani, V.; Kumar, V.; Gaurav, K. |
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Title |
AutoML-GWL: Automated machine learning model for the prediction of groundwater level |
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2024 |
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Engineering Applications of Artificial Intelligence |
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127 |
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107405 |
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AutoML, Bayesian optimisation, Groundwater, Machine learning |
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Predicting groundwater levels is pivotal in curbing overexploitation and ensuring effective water resource governance. However, groundwater level prediction is intricate, driven by dynamic nonlinear factors. To comprehend the dynamic interaction among these drivers, leveraging machine learning models can provide valuable insights. The drastic increase in computational capabilities has catalysed a substantial surge in the utilisation of machine learning-based solutions for effective groundwater management. The performance of these models highly depends on the selection of hyperparameters. The optimisation of hyperparameters is a complex process that often requires application-specific expertise for a skillful prediction. To mitigate the challenge posed by hyperparameter tuning’s problem-specific nature, we present an innovative approach by introducing the automated machine learning (AutoML-GWL) framework. This framework is specifically designed for precise groundwater level mapping. It seamlessly integrates the selection of best machine learning model and adeptly fine-tunes its hyperparameters by using Bayesian optimisation. We used long time series (1997-2018) data of precipitation, temperature, evaporation, soil type, relative humidity, and lag of groundwater level as input features to train the AutoML-GWL model while considering the influence of Land Use Land Cover (LULC) as a contextual factor. Among these input features, the lag of groundwater level emerged as the most relevant input feature. Once the model is trained, it performs well over the unseen data with a strong correlation of coefficient (R = 0.90), low root mean square error (RMSE = 1.22), and minimal bias = 0.23. Further, we compared the performance of the proposed AutoML-GWL with sixteen benchmark algorithms comprising baseline and novel algorithms. The AutoML-GWL outperforms all the benchmark algorithms. Furthermore, the proposed algorithm ranked first in Friedman’s statistical test, confirming its reliability. Moreover, we conducted a spatial distribution and uncertainty analysis for the proposed algorithm. The outcomes of this analysis affirmed that the AutoML-GWL can effectively manage data with spatial variations and demonstrates remarkable stability when faced with small uncertainties in the input parameters. This study holds significant promise in revolutionising groundwater management practices by establishing an automated framework for simulating groundwater levels for sustainable water resource management. |
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THL @ christoph.kuells @ singh_automl-gwl_2024 |
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168 |
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