APro, developed in KAERI for the process-based total system performance assessment (TSPA) of deep geological disposal systems, performs finite element method (FEM)-based multiphysics analysis. In the FEM-based analysis, the mesh element quality influences the numerical solution accuracy, memory requirement, and computation time. Therefore, an appropriate mesh structure should be constructed before the mesh stability analysis to achieve an accurate and efficient process-based TSPA. A generic reference case of DECOVALEX-2023 Task F, which has been proposed for simulating stationary groundwater flow and time-dependent conservative transport of two tracers, was used in this study for mesh stability analysis. The relative differences in tracer concentration varying mesh structures were determined by comparing with the results for the finest mesh structure. For calculation efficiency, the memory requirements and computation time were compared. Based on the mesh stability analysis, an approach based on adaptive mesh refinement was developed to resolve the error in the early stage of the simulation time-period. It was observed that the relative difference in the tracer concentration significantly decreased with high calculation efficiency.

APro, a modularized process-based total system performance assessment framework, was developed at the Korea Atomic Energy Research Institute (KAERI) to simulate radionuclide transport considering coupled thermal-hydraulic-mechanicalchemical processes occurring in a geological disposal system. For reactive transport simulation considering geochemical reactions, COMSOL and PHREEQC are coupled with MATLAB in APro using an operator splitting scheme. Conventionally, coupling is performed within a MATLAB interface so that COMSOL stops the calculation to deliver the solution to PHREEQC and restarts to continue the simulation after receiving the solution from PHREEQC at every time step. This is inefficient when the solution is frequently interchanged because restarting the simulation in COMSOL requires an unnecessary setup process. To overcome this issue, a coupling scheme that calls PHREEQC inside COMSOL was developed. In this technique, PHREEQC is called through the “MATLAB function” feature, and PHREEQC results are updated using the COMSOL “Pointwise Constraint” feature. For the one-dimensional advection-reaction-dispersion problem, the proposed coupling technique was verified by comparison with the conventional coupling technique, and it improved the computation time for all test cases. Specifically, the more frequent the link between COMSOL and PHREEQC, the more pronounced was the performance improvement using the proposed technique.

Various linear system solvers with multi-physics analysis schemes are compared focusing on the near-field region considering thermal-hydraulic-chemical (THC) coupled multi-physics phenomena. APro, developed at KAERI for total system performance assessment (TSPA), performs a finite element analysis with COMSOL, for which the various combinations of linear system solvers and multi-physics analysis schemes should to be compared. The KBS-3 type disposal system proposed by Sweden is set as the target system and the near-field region, which accounts for most of the computational burden is considered. For comparison of numerical analysis methods, the computing time and memory requirement are the main concerns and thus the simulation time is set up to one year. With a single deposition hole problem, PARDISO and GMRESSSOR are selected as representative direct and iterative solvers respectively. The performance of representative linear system solvers is then examined through a problem with an increasing number of deposition holes and the GMRES-SSOR solver with a segregated scheme shows the best performance with respect to the computing time and memory requirement. The results of the comparative analysis are expected to provide a good guideline to choose better numerical analysis methods for TSPA.

When decommissioning a nuclear power plant, the structure must be made to a disposable size. In general, the cutting process is essential when dismantling a nuclear power plant. Mainly, thermal cutting method is used to cutting metal structures. The aerosols generated during thermal cutting have a size distribution of less than 1 μm. The contaminated structures are able to generate radioactive aerosols in the decommissioning. Radioactive aerosols of 1 μm or less are deposited in the respiratory tract by workers’ breathing, causing the possibility of internal exposure. Therefore, workers must be protected from the risk of exposure to radioactive aerosols. Prior knowledge of aerosols generated during metal cutting is important to ensure worker safety. In this study, the physical and chemical properties of the aerosol were evaluated by measuring the number and mass concentrations of aerosols generated when cutting SUS304 and SA508 using the laser cutting method. High-resolution aerosol measuring equipment (HR-ELPI+, DEKATI) was used to measure the concentration of aerosols. The HR-ELPI+ is an impactor-type aerosol measuring equipment that measures the aerosol number concentration distribution in the aerodynamic diameter range of 6 nm to 10 um in real-time. And analyze the mass concentration of the aerosol according to the diameter range through the impactor. ICP-MS was used for elemental mass concentration analysis in the aerosol. Analytical elements were Fe, Cr, Ni and Mn. For the evaluation of physical and chemical properties, the MMAD of each element and CMAD were calculated in the aerosol distribution. Under the same cutting conditions, it was confirmed that the number concentration of aerosols generated from both materials had a uni-modal distribution with a peak around 0.1 um. CMAD was calculated to be 0.072 um for both SUS304 and SA508. The trend of the CMAD calculation results is the same even when the cutting conditions are changed. In the case of MMAD, it was confirmed that SUS304 had an MMAD of around 0.1 μm in size for only Fe, Cr and Mn. And SA508, Fe, Cr, Ni and Mn were all confirmed to have MMAD around 0.1 μm in size. The results of this study show that a lot of aerosols in the range of less than 1 μm, especially around 0.1 μm in size, are generated when metal is cut using laser cutting. Therefore, in order to protect the internal exposure of workers to laser metal cutting when decommissioning NPPs, it is necessary to protect from nano-sized aerosols beyond micron size.

APro, a modularized framework of the process-based total system performance assessment, has been developed by KAERI to simulate the radionuclide transport in geological disposal system considering multi-physics phenomena. However, the target problem including more than 10,000 boreholes and over 100,000 years of simulation time is computationally challenging to deal with numerical solvers provided by COMSOL Multiphysics constituting APro. To alleviate the computational burden, machine learning (ML) techniques have been studied to develop a surrogate model replacing the heavy computation part. In recent studies, attempts have been made to integrate the knowledge of physics and numerical methods into the ML model for partial differential equations (PDEs). Unlike conventional ML approaches solely relying on data-driven method, the integration can help to make the ML model more specialized for solving PDEs. The hybrid neural network (NN) solver method is one of the strategies to develop more efficient PDE solver by interleaving NN with numerical solvers like finite element method (FEM). The hybrid NN model on the premise of numerical solver is easier to train and more stable than the purely data-driven model. For example, one previous study has used the hybrid NN model as a corrector for an incomplete numerical solver for the advection-diffusion problem. In every time step of simulation, NN corrects the error of incomplete solution obtained by a relaxed numerical solver with coarse meshing. The simulation in the next time step starts from the corrected solution, so NN interacts with the numerical solver iteratively. If the corrector is successfully trained, the incomplete but fast solver with corrector can provide reliable results comparable to the original massive solver. This study adopts the hybrid concept to develop a surrogate model for the near-field region, which is the heavy computation part in the simulation of geological disposal system. Various incomplete models such as coarse meshing or emptying the borehole domain are studied to construct a hybrid NN solver. This study also covers how to embed the hybrid NN in COMSOL Multiphysics to train and use it during the simulation.

Domain decomposition method (DDM) has been widely employed for the numerical analysis of large-scale problems due to its applicability to parallel computing. DDM divides the modeling domain into a set of subdomains and obtains the entire solution iteratively until the values of each subdomain which are shared with other subdomains, such as boundary values, are converged. Therefore, in general, DDM is a memory-efficient iterative algorithm with inherent parallelism on the geometric level. APro, the process-based total system performance assessment model, aims for simulating the radionuclide transport considering coupled multi-physics phenomena occurring in large-scale geological disposal system, which are inevitably accompanied by huge memory burden. Therefore, DDM is applicable for the large-scale problem of APro and its performance in parallel computing needs to be examined. The DDM solvers provided by COMSOL which constitute APro can be classified into two methods. One is the overlapping Schwarz method that each subdomain overlaps its neighboring domains and the other is the Schur complement method that subdomains are non-overlapping and separated by boundary domains. For the Schwarz method, the additive, hybrid, multiplicative and symmetric methods can be selected according to the solution update scheme. And for the Schur method, the additive and multiplicative ordering options can be chosen for solving Schur complement system. In this study, the calculation efficiency of the DDM solvers in COMSOL and the applicability to the cluster environment were examined. In aspect of efficiency, the memory requirements with different number of subdomains and calculation schemes were compared in a single node. Then, the memory requirements with increasing number of disposal tunnels and deposition holes were investigated in multiple nodes. As a result, on the cluster environment, with the help of distributed memory architecture which enables efficient memory usage, the applicability of DDM solvers to the large-scale problem of APro was confirmed.

APro, developed by KAERI as a process-based total system performance assessment model, can simulate the radionuclide transport affected by thermal, hydraulic, mechanical and geochemical changes that may occurs in the engineering and natural barriers of a geological disposal system. APro targets a large-scale and heterogeneous 3D system that includes more than 10,000 boreholes located about 500 m underground and hundreds of fractures of different sizes distributed within an area of several km2. Simulating transport and reaction phenomena for such a system through the global implicit approach (GIA) may require considerable computational resources or be intractable in some cases. Therefore, APro adopts the sequential non-iterative approach (SNIA), one of the operator splitting (OS) methods, to separate the mass transport and reaction phenomena into independent problems. By using SNIA, the parallel computation performance in APro with multiple cores is expected to be improved. In this study, the effect of SNIA on the parallel computation performance was analyzed through a simple 1D reactive transport problem. Without SNIA, finite difference equations, discretized from the partial differential equations (PDEs) describing the reactive transport problem, have to be solved at once because all dependent variables are nonlinearly and spatially interconnected through reaction and mass transport terms. When the reaction and mass transport terms are separated through SNIA, the mass transport problem can be converted into independent linear equations for each chemical and the efficient linear system solver can be applied to each linear equation. In particular, since the reaction problem is changed to independent nonlinear equations for each node, the parallel computation performance can be greatly improved. To verify this, the 1D reactive transport problem was implemented in MATLAB, and SNIA and GIA were applied to solve the problem. As a result, there was no significant difference in results between SNIA and GIA for proper spatial and temporal discretization, which verified the accuracy of SNIA. In order to see the parallel computation performance, the calculation times for SNIA and GIA with increasing number of cores were measured and compared. As the number of cores increased, the SNIA calculation speed became faster than that of GIA, which verified that SNIA could improve parallel computation performance in APro. In the future, the effect of SNIA on the parallel computation performance will be verified for the numerical analysis of large-scale geological disposal systems.

The purpose of this study was to identify the structure and characteristics for the reproduction of the armor in the Unified Silla period, and then reproduce and utilize it as a cultural content. In the armor reproduction project excavated from Jaemaejeong, Gyeongju. Jaemaejeong armor is consisting of Singap (身甲, body armor), Sanggap (裳甲, hip armor), and Sangbakgap (上膊甲, upper arm armor) at the time of excavation. Unlike the armor of the Three Kingdoms period, Singap and Sanggap are separated. Singap is Yangdangsik (裲襠式, side opening method) and Gyunggap (頸 甲, gorget) was not unearthed, Sangbakgap was divided into a part that protects the left and right upper arms and a part that protects the chest, so that the unexcavated head and neck cover of the helmet can be protected to the shoulder. In addition, in the case of Chalgap (札甲, lamellar armor), the Oejungsik (外重式, folded from outside to inside) is mainly used, but it is peculiar that Naejungsik (內重式, folded from inside to outside) is used in Sangbakgap of Jaemaejeong armor. It is presumed that this was used as a method to ensure that the armor were closely attached to the human body. In order to design with the parade armor of Gochwidae in Gyeongju based on the reproduced Jaemaejeong armor, the designer’s imagination and historical work of the times were involved due to the characteristics of performance costumes. Reproduced armor as a cultural content should be considered indispensable to simplify and lighten clothing suitable for performances based on the excavated historical armor.

This study was investigated Quality characteristic of “pickled garlic shoots” manufactured using Vacuum impregnation (VI) and Pressure impregnation (PI) technology. Pickled garlic shoots were manufactured by impregnation solution which concentration were dark soy sauce (39.5 %), apple vinegar (39.5 %), brown sugar (19.8 %), soju (1.2 %). Pressure Impregnation carried out 30 Mpa for 5min or Vacuum Impregnation carried out 360 mmHg for 5min, analyzed treated garlic shoots properties. Impregnation condition were chosen by pre-test (Vacuum Impregnation: 160, 360, 560, 680 mmHg, Pressure Impregnation: 40 MPa, 60 MPa, 80 MPa, 100 MPa). Quality characteristics were pH, Brix, salinity, acidity, color, texture and sensory evaluation. In results of quality characteristics, brix, salinity, sensory evaluation were significantly difference between Pressure Impregnation, Vacuum impregnation and Control. According to sensory evaluation, which parameter were taste, flavor, mouthfeel and overall acceptability, Pressure impregnation were scored highest and Vacuum impregnation were second. In the texture analyze, Hardness of “pickled garlic shoots” which were manufactured using Impregnation technology were 4.3 × 105±784.271 N/m2. This was possible to manufacture “pickled garlic shoots” in a short time which were Universal Design food (UDF) 1 class.