Buffer materials are one of the engineering barrier components in high-level radioactive waste disposal facilities. Compacted bentonite has been known as the most suitable buffer material so far, and research is being conducted worldwide to determine the characteristics of suitable bentonite blocks in each country. Therefore, this study aims to compare and analyze various properties of different buffer material candidates, including thermal, hydraulic, and mechanical properties. Buffer material candidates for Korea disposal system, Kyungju Bentonite (KJ-I, KJ-II), and Bentonil- WRK were compared. The properties were compared and analyzed based on experimental and literature data. The data obtained from this report can be used to understand the behavior of buffer materials and assess whether they meet various criteria, such as temperature and saturation, and ultimately serve as an essential input variable database for safety evaluations of disposal systems.

Bentonite has been considered as a potential buffer material in the engineering barriers of highlevel radioactive waste disposal systems. The intrusion of groundwater and heat from the waste change the temperature of the bentonite, which can alter the hydraulic properties of the bentonite. In this study, temperature effects on permeability were observed in two Ca-type bentonites. Laboratory tests were conducted on two types of block that were compacted using Korean Gyeongju bentonite and bentonil-WRK at different dry densities. Permeability tests were conducted at three different temperatures, namely 30°C, 60°C, and 90°C, using deionized water. Moreover, comparison between two Ca-type bentonites is carried out.

For safety assessment of a high-level radioactive waste disposal system, it is important to predict and analyze the coupled thermo-hydro-mechanical (THM) behaviors of bentonite, which is a buffer candidate material in the engineered barrier system. The Barcelona Basic Model (BBM) is a constitutive model to describe the geomechanical behaviors of partially saturated soils. Complicated tests are required to directly measure BBM parameters of bentonite. In this study, we demonstrate that probable BBM parameters can be sought by calibrating the BBM parameters to match simulation results to observed ones for two kinds of simple tests (swelling pressure test and free swelling test) instead of the complicated direct tests. In the swelling pressure test and free swelling test that were conducted by Japan Atomic Energy Agency (JAEA), water was injected into constrained and unconstrained bentonite core samples, and then swelling pressure and displacements were measured, respectively. We find optimal BBM parameters using a quasi-Newton optimization method that reproduce the observed swelling pressures and displacements in hydro-mechanical simulations. The optimal BBM parameters that are sought in the inversion process can be used to predict the THM behaviors of bentonite barriers in a high-level radioactive waste disposal system.

The buffer is a critical barrier component in an engineered barrier system, and its purpose is to prevent potential radionuclides from leaking out from a damaged canister by filling the void in the repository. No experimental parameters exist that can describe the buffer expansion phenomenon when Kyeongju bentonite, which is a buffer candidate material available in Korea, is exposed to groundwater. As conventional experiments to determine these parameters are time consuming and complicated, simple swelling pressure tests, numerical modeling, and machine learning are used in this study to obtain the parameters required to establish a numerical model that can simulate swelling. Swelling tests conducted using Kyeongju bentonite are emulated using the COMSOL Multiphysics numerical analysis tool. Relationships between the swelling phenomenon and mechanical parameters are determined via an artificial neural network. Subsequently, by inputting the swelling tests results into the network, the values for the mechanical parameters of Kyeongju bentonite are obtained. Sensitivity analysis is performed to identify the influential parameters. Results of the numerical analysis based on the identified mechanical parameters are consistent with the experimental values.

Various models have been proposed to describe the swelling behavior of buffer in high level waster repository. One of the most notable models, the Barcelona Basic Model (BBM), is a mechanical model that simulates the behavior of unsaturated ground and is widely applied to soils that undergo large expansion due to water. Among the BBM parameters of Kyeongju bentonite, which is found in Korea, there are no experimental data for parameters that describe the unsaturated state. Such hydromechanical properties should be characterized through experimental programs. However, such experiments are highly complicated and require long periods of time to produce an unsaturated state through different methods according to the suction range. Although there are several studies in which geotechnical parameters were obtained through a back analysis instead of direct experiments, few studies have employed machine learning methods for the identification of geotechnical parameters. In this study, instead of direct experiments, the results of a relatively simple swelling pressure experiment was compared to the numerical analysis results to propose a method of determining some of BBM parameters. Influential factors were identified by a sensitivity analysis and the values of the factors were estimated using an artificial neural network and optimization method. The obtained parameters were applied to the numerical model to estimate the swelling pressure growth, which was subsequently compared to the experimental value. As a result, it was found that there was no significant difference between the two swelling values.