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Joseph, J.; Külls, C.; Arend, M.; Schaub, M.; Hagedorn, F.; Gessler, A.; Weiler, M. |
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Title |
Application of a laser-based spectrometer for continuous in situ measurements of stable isotopes of soil CO2 in calcareous and acidic soils |
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Journal Article |
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2019 |
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Soil |
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5 |
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1 |
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49-62 |
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Copernicus |
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THL @ christoph.kuells @ Joseph2019application |
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15 |
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Author |
Illgen, M.; Ackermann, H. |
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Book Chapter |
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Year |
2019 |
Publication |
Urban Flood Prevention: Technical and Institutional Aspects from Chinese and German Perspective |
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173-193 |
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Abstract |
Today’s cities face the challenge of climate change adaptation worldwide. In this context, prevention of damage caused by flash floods plays an important role. This requires a cooperative pluvial flood risk management approach, which includes planning, technical, and administrative measures and involves preliminary flood risk analyses. This article outlines the main components of this risk management approach, which has proven its effectiveness in Europe. The recommendations formulated for this purpose are applicable or adaptable to regions with other constraints, such as China, for example. |
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Springer International Publishing |
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Cham |
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Köster, S.; Reese, M.; Zuo, J.’e |
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978-3-030-01488-9 |
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THL @ christoph.kuells @ Illgen2019 |
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87 |
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Author |
Merembayev, T.; Yunussov, R.; Yedilkhan, A. |
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Title |
Machine Learning Algorithms for Stratigraphy Classification on Uranium Deposits |
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Journal Article |
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Year |
2019 |
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Procedia Computer Science |
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150 |
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46-52 |
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Keywords |
classification, geophysics logging data, machine learning, stratigraphy, uranium deposit |
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Abstract |
Machine learning today becomes more and more effective instrument to solve many particular problems, where there are difficulties to apply well known and described math model. In other words – it is a great tool to describe non-linear phenomena. We tried to use this technique to improve existing process of stratigraphy, and reduce costs on site by applying computer leaded predictions on the basis of existing on-field collected data. Article describes usage of machine learning algorithms for stratigraphy boundaries classification based on geophysics logging data for uranium deposit in Kazakhstan. Correct marking of stratigraphy from geophysics logging data is complex non-linear task. To solve this task we applied several algorithms of machine learning: random forest, logistic regression, gradient boosting, k nearest neighbour and XGBoost. |
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1877-0509 |
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THL @ christoph.kuells @ merembayev_machine_2019 |
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113 |
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Author |
Hall, S.M.; Gosen, B.S.V.; Paces, J.B.; Zielinski, R.A.; Breit, G.N. |
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Title |
Calcrete uranium deposits in the Southern High Plains, USA |
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Journal Article |
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Year |
2019 |
Publication |
Ore Geology Reviews |
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109 |
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50-78 |
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Keywords |
Calcrete, Carnotite, Finchite, Geochemistry, Uranium, Vanadium |
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Abstract |
The Southern High Plains (SHP) is a new and emerging U.S. uranium province. Here, uranyl vanadates form deposits in Pliocene to Pleistocene sandstone, dolomite, and limestone. Fifteen calcrete uranium occurrences are identified; two of these, the Buzzard Draw and Sulfur Springs Draw deposits, have combined in-place resources estimated at about 4 million pounds of U3O8. Ore minerals carnotite and finchite are hosted in dolomite at the Sulfur Springs Draw deposit, with accessory fluorite, celestine, smectite/illite, autunite, and strontium carbonate. Host carbonate at the Sulfur Springs Draw deposit is ∼190 ka and mineralization mobilized as recently as 3.8 ka. Ash collected near the deposit is 631 ka and erupted from the Yellowstone caldera complex. The Triassic Dockum Group that contains sandstone-hosted uranium deposits throughout the region and underlies the SHP is a potential source for uranium and vanadium. Regional uplift and dissection reintroduced oxygenated groundwater into the Dockum Group, mobilizing uranium. Additional uranium may have been contributed to groundwater by weathering of volcanic ash in Pliocene and Pleistocene host rocks. The locations of the uranium occurrences are mostly in modern drainage systems in the southeast portion of the SHP. Modelling of modern groundwater in the SHP carried out in a parallel study shows that a single fluid could form carnotite through evaporation, and that fluids of the requisite composition are more prevalent in the southern portion of the SHP. The southeastern portion of the SHP hosts more uranium occurrences due to a variety of factors including (1) upward transport of groundwater and connectivity between source and host rock, (2) higher uranium and vanadium content of groundwater, (3) higher rates of groundwater recharge in this region to drive the mineralizing system, and (4) shallower groundwater facilitating surface evaporation. Ongoing erosion of host rocks challenges preservation of deposits and may limit their size. |
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0169-1368 |
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THL @ christoph.kuells @ hall_calcrete_2019 |
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124 |
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Author |
Mühr-Ebert, E.L.; Wagner, F.; Walther, C. |
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Title |
Speciation of uranium: Compilation of a thermodynamic database and its experimental evaluation using different analytical techniques |
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Journal Article |
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Year |
2019 |
Publication |
Applied Geochemistry |
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100 |
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Pages |
213-222 |
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Environmental hazards are caused by uranium mining legacies and enhanced radioactivity in utilized groundwater and surface water resources. Knowledge of uranium speciation in these waters is essential for predicting radionuclide migration and for installing effective water purification technology. The validity of the thermodynamic data for the environmental media affected by uranium mining legacies is of utmost importance. Therefore, a comprehensive and consistent database was established according to current knowledge. The uranium data included in the database is based on the NEA TDB (Guillaumont et al., 2003) and is modified or supplemented as necessary e.g. for calcium and magnesium uranyl carbonates. The specific ion interaction theory (Brönsted, 1922) is used to estimate activity constants, which is sufficient for the considered low ionic strengths. The success of this approach was evaluated by comparative experimental investigations and model calculations (PHREEQC (Parkhurst and Appelo, 1999)) for several model systems. The waters differ in pH (2.7–9.8), uranium concentration (10−9-10−4 mol/L) and ionic strength (0.002–0.2 mol/L). We used chemical extraction experiments, ESI-Orbitrap-MS and time-resolved laser-induced fluorescence spectroscopy (TRLFS) to measure the uranium speciation. The latter method is nonintrusive and therefore does not change the chemical composition of the investigated waters. This is very important, because any change of the system under study may also change the speciation. |
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0883-2927 |
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THL @ christoph.kuells @ muhr-ebert_speciation_2019 |
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142 |
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