Publications by authors named "D M Rudakov"

In this study, we present an assessment of the uranium ore tailings impact on groundwater and surface water contamination. The radioactive materials were deposited in the tailings storage facility "Dniprovske" (the city of Kamianske, Ukraine) from 1954 to 1968; now it contains about 5.85·10 m of hazardous waste on the area of about 76 ha in the floodplain of the Dnipro river.

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Mine water injection into deep formations is one of the effective approaches for reducing the drainage from coal mines in the arid and semi-arid region of the Ordos basin, China. Many coal mines are attempting to execute the related projects. Under the influence of groundwater protection, the understanding of regional groundwater flow is becoming highly important to the mine water monitoring, whereas quite few academic research teams focus on the deep groundwater flow pattern by mine water injection.

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The Surface Eroding Thermocouple (SETC) is a robust diagnostic utilized in DIII-D to provide fast, edge-localized modes (ELMs) resolved heat flux measurements, in particular in geometric regions that are too shadowed for traditional infrared thermography. In order to further investigate the power dissipation in the divertor region, a combination of flush-mounted and recessed SETCs was developed to assess the effect on surface heating from non-charged particles at the divertor target. Utilizing the Divertor Materials Evaluation System sample exposure platform, the first demonstration of the feasibility of using this new method to distinguish between the heat flux from charged particles and that from neutrals and radiative heating was achieved.

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The mechanism of the noncatalytic bromination of carboranes was studied experimentally and theoretically. We found that the reactions of - and -carboranes and with elemental bromine are first order in the substrate but unusually high (approximately fifth) order in bromine. The calculated energy barriers of these reactions decrease sharply as more bromine molecules are added to the quantum-chemical system.

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A robust impurity detection and tracking code, able to generate large sets of dust tracks from tokamak camera footage, is presented. This machine learning-based code is tested with cameras from the Joint European Torus, Doublet-III-D, and Magnum-PSI and is able to generate dust tracks with a 65-100% classification accuracy. Moreover, the number dust particles detected from a single camera shot can be up to the order of 1000.

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