The radiological characterization of SSCs (Structure, Systems and Components) plays one of the most important role for the decommissioning of KORI Unit-1 during the preparation periods. Generally, a regulatory body and laws relating to the decommissioning focus on the separation and appropriate disposal or storage of radiological waste including ILW (intermediate level waste), LLW (low level waste), VLLW (very low level waste) and CW (clearance waste), aligned with their contamination characteristics. The result of the preliminary radiological characterization of KORI Unit-1 indicated that, apart from neutron activated the RV (reactor vessel), RVI (reactor vessel internals), and BS (biological shielding concrete), the majorities of contamination were sorted to be less than LLW. Radiological contamination can be evaluated into two methods. Due to the difficulties of directly measuring contamination on the interior surfaces of the pipe, called CRUD, the assessment was implemented by modeling method, that is measuring contamination on the exterior surfaces of the pipes and calculating relative factors such as thickness and size. This indirect method may be affected by the surrounding radiation distribution, and only a few gamma nuclides can be measured. Therefore, it has limitation in terms of providing detailed nuclide information. Especially, α and β nuclides can only be estimated roughly by scaling factors, comparing their relative ratios with the existing gamma results. To overcome the limitation of indirect measurement, a destructive sampling method has been employed to assess the contamination of the systems and component. Samples are physically taken some parts of the systems or components and subsequently analyzed in the laboratory to evaluate detailed nuclides and total contamination. For the characterization of KORI Unit-1, we conducted the radiation measurement on the exterior surfaces of components using portable instruments (Eberline E-600 SPA3, Thermo G20-10, Thermo G10, Thermo FH40TG) at BR (boron recycle system) and SP (containment spray system) in primary system. Based on these results, the ProUCL program was employed to determine the destructive sample collection quantities based on statistical approach. The total of 5 and 8 destructive sample quantities were decided by program and successfully collected from the BR and SP systems, respectively. Samples were moved to laboratory and analyzed for the detail nuclide characteristics. The outcomes of this study are expected to serve as valuable information for estimating the types and quantities of radiological waste generated by decommissioning of KORI Unit-1.

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.

The most important thing in development of a process-based TSPA (Total System Performance Assessment) tool for large-scale disposal systems (like APro) is to use efficient numerical analysis methods for the large-scale problems. When analyzing the borehole in which the most diverse physical phenomena occur in connection with each other, the finest mesh in the system is applied to increase the analysis accuracy. Since thousands of such boreholes would be placed in the future disposal system, the numerical analysis for the system becomes significantly slower, or even impossible due to the memory problem in cases. In this study, we propose a tractable approach, so called global-local iterative analysis method, to solve the large-scale process-based TSPA problem numerically. The global-local iterative analysis method goes through the following process: 1) By applying a coarse mesh to the borehole area the size of the problem of global domain (entire disposal system) is reduced and the numerical analysis is performed for the global domain. 2) Solutions in previous step are used as a boundary condition of the problem of local domain (a unit space containing one borehole and little part of rock), the fine mesh is applied to the borehole area, and the numerical analysis is performed for each local domain. 3) Solutions in previous step are used as boundary conditions of boreholes in the problem of global domain and the numerical analysis is performed for the global domain. 4) steps 2) and 3) are repeated. The solution derived by the global-local iterative analysis method is expected to be closer to the solution derived by the numerical analysis of the global problem applying the fine mesh to boreholes. In addition, since local problems become independent problems the parallel computing can be introduced to increase calculation efficiency. This study analyzes the numerical error of the globallocal iterative analysis method and evaluates the number of iterations in which the solution satisfies the convergence criteria. And increasing computational efficiency from the parallel computing using HPC system is also analyzed.

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.

The electrochemical reduction of carbon dioxide (CO2) to value-added products is a remarkable approach for mitigating CO2 emissions caused by the excessive consumption of fossil fuels. However, achieving the electrocatalytic reduction of CO2 still faces some bottlenecks, including the large overpotential, undesirable selectivity, and slow electron transfer kinetics. Various electrocatalysts including metals, metals oxides, alloys, and single-atom catalysts have been widely researched to suppress HER performance, reduce overpotential and enhance the selectivity of CO2RR over the last few decades. Among them, single-atom catalysts (SACs) have attracted a great deal of interest because of their advantages over traditional electrocatalysts such as maximized atomic utilization, tunable coordination environments and unique electronic structures. Herein, we discuss the mechanisms involved in the electroreduction of CO2 to carbon monoxide (CO) and the fundamental concepts related to electrocatalysis. Then, we present an overview of recent advances in the design of high-performance noble and non-noble singleatom catalysts for the CO2 reduction reaction.

Plasma Arc Melter (MSO) system has been developed for the treatment and the stabilization of various kinds of hazardous and radioactive waste into the readily disposable solidification products. Molten salt oxidation system has been developed for the for the treatment of halogen- and sulfurbearing hazardous and radioactive waste without emissions of PCDD/Fs and acid gases. However, PAM system has showed some difficulty in the off-gas treatment system due to the volatilization of radionuclides and toxic metals at extremely high-temperature plasma arc melter and the emissions of acid gases. MSO system has also showed the difficulty in the treatment of spent molten salt into the disposable waste form. Present study discussed the results of organics destruction performance tests for the PAM-MSO combination system, which is proposed and developed to compensate the drawbacks of each system. The worst-case condition tests for the organics destruction were conducted at lowest temperatures and the worst-case condition tests for the retention of metals and radionuclides were conducted at highested temperatures under the range of normal operating condition. For the worst-case organic destruction test, C6H5Cl was selected as a POHCs (Principal Organic Hazardous Constituents) because of its high incinerability ranking and the property of generation of chlorine gases and PCDD/Fs when incompletely destroyed. Simulated concrete waste spiked with 1 L of C6H5Cl was treated and the emissions of 17 kinds of PCDD/Fs and other hazardous gases such as CO, THCs, NOx, SO2 and HCl/Cl2 were measured. For the worst-case condition tests for the retention of metals and radionuclides, Pb and Cs were selected because of its high volatility characteristics. The emissions of PCDD/Fs was extremely lowered than the emission limit and those of other hazardous constituents were below their emission limit. The results of performance tests on the organics destruction suggested that tested PAM-MSO combination system could readily treat PCBs-bearing spent insulation liquid, spent ion-exchange resins used for the treatment of spent decontamination liquid in the decommission process and the concreted debris bearing hazardous organic coating materials. The decontamination factor of Cs and Co were 1.4×105, 1.4×105, respectively. The emisison of Pb was 0.562 ppm. These results suggested that tested PAM-MSO system treated low-level radioactive and pb-bearing mixed waste.

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.