• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.4
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• pp.63-70
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• 2007

The soil samples used in this study were prepared with the residual granite soils passed through the #4 sieve and obtained from Pocheon in Gyeonggi-Ki do. Specifically, five types of samples were prepared. Sample A which is a natural state soil was classified as SM according to the uses. Samples of B, C, D, and E were prepared by mixing Sample A with bentonite and were classified as SC according to the uses. The plasticity indexes of samples B, C, D, and E were 15, 25, 30, and 40, respectively. The specimens, whose dimensions are 100mm by 127.5mm, were prepared by A method of ASTM D 698 with the Proctor mold. In experiments, the loading with the 1%/min was applied. Four different disk diameters, 13mm, 26mm, 38mm, and 52mm were used in the Improved Unconfined Penetration (IUP) tests. To compare the tensile strengths, the split tensile tests were also conducted on the same specimens used for the IUP tests. To find out the effects of moisture contents, plasticity Index of specimens on the tensile strength, six different water contents were used for making a specimen.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.2
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• pp.123-131
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• 2021

The buffer is a key component of an engineered barrier system that safeguards the disposal of high-level radioactive waste. Buffers are located between disposal canisters and host rock, and they can restrain the release of radionuclides and protect canisters from the inflow of ground water. Since considerable heat is released from a disposal canister to the surrounding buffer, the thermal conductivity of the buffer is a very important parameter in the entire disposal safety. For this reason, a lot of research has been conducted on thermal conductivity prediction models that consider various factors. In this study, the thermal conductivity of a buffer is estimated using the machine learning methods of: linear regression, decision tree, support vector machine (SVM), ensemble, Gaussian process regression (GPR), neural network, deep belief network, and genetic programming. In the results, the machine learning methods such as ensemble, genetic programming, SVM with cubic parameter, and GPR showed better performance compared with the regression model, with the ensemble with XGBoost and Gaussian process regression models showing best performance.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.7 no.1
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• pp.63-72
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• 2009

Recently the importance and interest for the microbes has been increased because several important results for the effects of microbes on the radioactive waste disposal have been published continuously. In this study, research status and major results on the various roles and effects of microbes in the radioactive waste disposal have been investigated. We investigated and summarized the roles and major results of microbes in a multi-barrier system consisting of an engineered barrier and a natural barrier which is considered in radioactive waste disposal systems. For the engineered barrier, we discussed about the effects of microbes on the corrosion of a waste container and investigated the survival possibility and roles of microbes in a compacted bentonite buffer. For the natural barrier, the roles of microbes present in groundwaters and rocks were discussed and summarized with major results from natural analogue studies. Furthermore, we investigated and summarized the roles and various interactions processes of microbes and their effects on the radionuclide migration and retardation including recent research status. Therefore, it is expected that the effects and roles of microbes on the radioactive waste disposal can be rigorously evaluated if further researches are carried out for a long-term behavior of the disposal system in the deep geological environments and for the effects of microbes on the radionuclide migration through geological media.

• Economic and Environmental Geology
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• v.56 no.2
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• pp.167-183
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• 2023

Gases originated from the final SNF (spent nuclear fuel) disposal site are very mobile in the barrier and they may also affect the migration of radioactive nuclides generated from the SNF. Mechanisms of gas-nuclide migration in the multi-barrier and their influences on the safety of the disposal site should be understood before the construction of the final SNF disposal site. However, researches related to gas-nuclide coupled movement in the multi-barrier medium have been very little both at home and abroad. In this study, properties of gas generation and migration in the SNF disposal environment were reviewed through previous researches and their main mechanisms were summarized on the hydrogeological evolution stage of the SNF disposal site. Gas generation in the SNF disposal site was categorized into five origins such as the continuous nuclear fission of the SNS, the Cu-canister corrosion, the oxidation-reduction reaction, the microbial activity, and the inflow from the natural barriers. Migration scenarios of gas in porous medium of the multi-barrier in the SNF repository site were investigated through reviews for previous studies and several gas migration types including ① the free gas phase flow including visco-capillary two-phase flow, ② the advection and diffusion of dissolved gas in pore water, ③ dilatant two-phase flow, and ④ tensile fracture flow, were presented. Reviewed results in this study can support information to design the further research for the gas-nuclide migration in the repository site and to evaluate the safety of the Korean SNF disposal site in view points of gas migration in the multi-barrier.