• Journal of Radiation Protection and Research
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• v.35 no.3
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• pp.105-110
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• 2010

Using N-type HPGe gamma spectrometer, uranium analysis technique of soil sample is developed where the chemical preprocessing is not a necessity. The results of uranium activities using the method presented in this paper were compared with those results with conventional alpha spectrometer and two results were similar from within uncertainty range. Therefore, this new method will be applied in uranium activity analysis of soil sample.

• Journal of Radiation Protection and Research
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• v.18 no.2
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• pp.61-69
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• 1993

We examined various enzyme activity changes by intraperitoneal injection uranium in the carp liver. These enzyme activity changes can be used as biochemical indicators of internal exposure to uranium. The results were followings ; 1) Total protein concentration decreased by intraperitoneal injection in the carp liver. 2) Lysosomal acid pretense and ${\beta}-glucuronidase$ activities increased in the liver until sixth intraperitoneal injection of uranium, but Lysosomal acid phosphatase activities decreased in the liver until the sixth injection of uranium. 3) Alkaline phosphatase activities sharply increased and Glutamate oxaloacetate Transaminase activities steadily decreased in the liver until the sixth injection of uranium. 4) Creatine %kinase activities steadily decreased and malate dehydrogenase activities sharply decreased in the liver after the primary injection of uranium. Any malate dehydrogenase activities was not detected after sixth injection of uranium.

• Nuclear Engineering and Technology
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• v.12 no.2
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• pp.106-110
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• 1980

The radio-equilibrium conditions of uranium and thorium in the Okcheon black shales and monazites have been studied. As the results. a radiometric method based on the measurements of gamma ray activity has been suggested for the simple analysis of many samples in the process of the prospecting and the grading of uranium and thorium minerals.

• Journal of Radiation Protection and Research
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• v.26 no.3
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• pp.275-279
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• 2001

In uranium enrichment plants and nuclear fuel fabrication facilities, exact measurement of fissile isotope enrichment of uranium is required for material accounting in international safeguards inspection as well as process quality control. The purpose of this study was to develop a simple measurement system which can portably be used at nuclear fuel fabrication plants especially dealing with low enriched uranium. For this purpose, a small size CZT (CdZnTe) detector was used, and the detector performance in low uranium gamma/X -rays energy range was investigated by use of various enriched uranium oxide samples. New enrichment measurement technique and analysis method for low enriched uranium oxide, so-called, 'semi-peak ratio technique' was developed. The newly developed method was considered as an alternative technique for the low enrichment and would be useful to account nuclear material in safeguarding activity at nuclear fuel fabrication facility.

• Journal of Korean Society on Water Environment
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• v.23 no.2
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• pp.201-205
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• 2007

This paper reports the amount of $^{222}Rn$ and $^{238}U$ in 18 sites of ground water and 30 sites of surface water. The instrument used to count $^{222}Rn$ activity was the liquid scintillation counter (LSC) which could resolute ${\alpha}$ and ${\beta}$ radiations. And $^{238}U$ was analyzed by the inductively coupled plasma (ICP). Radon and Uranium were not detected in raw and treated water which were sampled in a water treatment plant. However, radon ($^{222}Rn$) was high concentration in ground water from Jeon-la, Gang-won. So was uranium ($^{238}U$) in case of ground water from Gang-won, Choong-chung. Radon ($^{222}Rn$) activities were detected less than 15 pCi/L at 5 sampling points, 15~300 pCi/L at 7 sampling points, 300~4000 pCi/L at 6 sampling points. However, Radon ($^{222}Rn$) activities of all ground water samples were less than 4,000 pCi/L, which was bellow American Alternative Maximum Contamination Level (AMCL). Uranium ($^{238}U$) concentrations were less than $0.1{\mu}g/L$ at 5 sampling points, from $0.1{\mu}g/L$ to $20{\mu}g/L$ at 13 sampling points. Uranium was not detected in about 30% of the whole samples, but the concentration ranged from relatively low to high concentrations depending on the sampling point. The minimum detectable activity (MDA) of radon was 15 pCi/L. and the detection limit of uranium was $0.1{\mu}g/L$.

• Journal of the Mineralogical Society of Korea
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• v.24 no.2
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• pp.83-90
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• 2011

Removal of dissolved uranium by D. baculatum, a sulfate-reducing bacterium, and effects of trace metals such as manganese, copper, nickel, and cobalt were investigated. Total concentrations of dissolved uranium and trace metals were used by $50\;{\mu}M$ and $200\;{\mu}M$, respectively. Most dissolved uranium decreased up to a non-detectable level (< 10 ppb) MS during the experiments. Most of the heavy metals did nearly not affect the bioremoval rates and amounts of uranium, but copper restrained microbial activity. However, it is found that dissolved uranium rapidly decreased after 2 weeks, showing that the bacteria can overcome the copper toxicity and remove the uranium. It is observed that nickel and cobalt were readily coprecipitated with biogenic mackinawite.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4527-4542
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• 2023

The present microbial reinforcement of rock and soil exhibits limitations, such as uneven reinforcement effectiveness and low calcium carbonate generation rate, resulting in limited solidification strength. This study introduces electroosmosis as a standard microbial grouting reinforcement technique and investigates its solidification effects on microbial-reinforced uranium tailings. The most effective electroosmosis effect on uranium tailings occurs under a potential gradient of 1.25 V/cm. The findings indicate that a weak electric field can effectively promote microbial growth and biological activity and accelerate bacterial metabolism. The largest calcium carbonate production occurred under the gradient of 0.5 V/cm, featuring a good crystal combination and the best cementation effect. Staged electroosmosis and electrode conversion efficiently drive the migration of anions and cations. Under electroosmosis, the cohesion of uranium tailings reinforced by microorganisms increased by 37.3% and 64.8% compared to those reinforced by common microorganisms and undisturbed uranium tailings, respectively. The internal friction angle is also improved, significantly enhancing the uniformity of reinforcement and a denser and stronger microscopic structure. This research demonstrates that MICP technology enhances the solidification effects and uniformity of uranium tailings, providing a novel approach to maintaining the safety and stability of uranium tailings dams.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2004.06a
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• pp.407-417
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• 2004

This study is to verify radiation detection method by using $\alpha$-spectroscopy and ${\gamma}$-spectroscopy for concretes and components which will be generated during the decommissioning of the uranium conversion plant. Components and inside walls of the building were contaminated with natural uranium materials. Some parts of the stainless steel pipes and concretes of the walls were sampled and analyzed their alpha and gamma activities respectively. Alpha and gamma activities are well matched each other in the range of high activity region to 0.01 Bq/g and gamma activities are over estimated comparing alpha activities corresponded in below 0.005 Bq/g region for the natural uranium of AUC sample. The $^{238}U$ originated from natural products of conversion process could be distinguished by measuring $^{214}Pb$ or $^{214}Bi$ and $^{234}Th$ or $^{234m}Pa$. Uranium contaminations mainly are in the wall surface of the plant. Decontamination process of generating wastes which can be reached tp background level gamma activities measured by gamma spectroscopy can also be used to conservative assessment data.

• Applied Biological Chemistry
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• v.22 no.4
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• pp.221-226
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• 1979

The soils and plants were sampled from 26 sites of Deogpyeongri, Goisangun, which had been found to be one of the uranium deposit areas. Uranium levels of the samples were determined and the amount of uranium intake by the residents through the food-chains was estimated. The average uranium concentration of Deogpyeongri soils was 15.5ppm with a range of from 4.9 to 43.6ppm showing rather higher values than those of control area, Yangjugun and Icheongun, Gyeonggi-do. The average uranium content of the plant samples from Deogpyeongri was 0.69ppm, about twice the uranium concentration of the control samples. The daily intake of uranium by an adult lived on the agricultural food stuffs produced in Deogpyeongri, was estimated to be about $247{\mu}g$, eqivalent to $0.83{\times}10^{-4}{\mu}Ci$, which is much higher activity compared to the daily intake of uranium by New York citizen, $1.3{\mu}g$. However the calculated uranium level accumulated in the human body of Deogpyeong area was $2.03{\times}10^{-4}{\mu}Ci$ which is still lower than $0.2{\mu}Ci$, the maximum permissible burden in total body recommended by the ICRP.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1372-1384
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• 2024

The discrimination of the source for xenon gases' release can provide an important clue for detecting the nuclear activities in the neighboring countries. In this paper, three machine learning techniques, which are logistic regression, support vector machine (SVM), and k-nearest neighbors (KNN), were applied to develop the predictive models for discriminating the source for xenon gases' release based on the xenon isotopic activity ratio data which were generated using the depletion codes, i.e., ORIGEN in SCALE 6.2 and Serpent, for the probable sources. The considered sources for the neighboring countries of South Korea include PWRs, CANDUs, IRT-2000, Yongbyun 5 MWe reactor, and nuclear tests with plutonium and uranium. The results of the analysis showed that the overall prediction accuracies of models with SVM and KNN using six inputs, all exceeded 90%. Particularly, the models based on SVM and KNN that used six or three xenon isotope activity ratios with three classification categories, namely reactor, plutonium bomb, and uranium bomb, had accuracy levels greater than 88%. The prediction performances demonstrate the applicability of machine learning algorithms to predict nuclear threat using ratios of xenon isotopic activity.