The safety of deep geological disposal systems has to be ensured to guarantee the isolation of radionuclides from human and related environments for over a million years. Over such a long timeframe, disposal systems can be influenced by climate change, leading to significant long-term impacts on the hydrogeological condition, including changes in temperature, precipitation and sea levels. These changes can affect groundwater flow, alter geochemical conditions, and directly/ indirectly impact the stability of the repository. Hence, it is essential to conduct a safety assessment that considers the long-term evolution induced by climate change. In this context, the Korea Atomic Energy Research Institute (KAERI) is developing the Adaptive Process-based total system performance assessment framework for a geological disposal system (APro). Currently, numerical modules for APro are under development to account for the longterm evolution that can influence groundwater flow and radionuclide transport in the far-field of the disposal system. This study focuses on the development of two numerical modules designed to model permafrost formation and buoyance force due to relative density changes. Permafrost is defined as a ground in which temperature remains below zero-isotherm (0°C) continuously for more than two consecutive years. In regions where permafrost forms, the relative permeability of porous media is significantly reduced. The changes in permeability due to permafrost formation are modelled by calculating the unfrozen fluid content within a porous medium. Meanwhile, buoyancy force can occur when there is a difference in density at the boundary of two distinct water groups, such as seawater (salt water) and freshwater. Sea level change associated with climate change can alter the boundary between seawater and freshwater, resulting in changes in groundwater flow. The buoyancy force due to relative density is modelled by adjusting concentration boundary conditions. Using the developed numerical modules, we evaluated the long-term evolution’s effects by analyzing radionuclide transport in the far-field of the disposal system. Incorporating permafrost and buoyancy force modelling into the APro framework will contribute valuable insights into the complex interactions between geological and climatic factors, enhancing our ability to ensure the secure isolation of radionuclides for extended periods.

Over the years, in the field of safety assessment of geological disposal system, system-level models have been widely employed, primarily due to considerations of computational efficiency and convenience. However, system-level models have their limitations when it comes to phenomenologically simulating the complex processes occurring within disposal systems, particularly when attempting to account for the coupled processes in the near-field. Therefore, this study investigates a machine learning-based methodology for incorporating phenomenological insights into system-level safety assessment models without compromising computational efficiency. The machine learning application targeted the calculation of waste degradation rates and the estimation of radionuclide flux around the deposition holes. To develop machine learning models for both degradation rates and radionuclide flux, key influencing factors or input parameters need to be identified. Subsequently, process models capable of computing degradation rates and radionuclide flux will be established. To facilitate the generation of machine learning data encompassing a wide range of input parameter combinations, Latin-hypercube sampling will be applied. Based on the predefined scenarios and input parameters, the machine learning models will generate time-series data for the degradation rates and radionuclide flux. The time-series data can subsequently be applied to the system-level safety assessment model as a time table format. The methodology presented in this study is expected to contribute to the enhancement of system-level safety assessment models when applied.

The effect of various physicochemical processes, such as seawater intrusion, on the performance of the engineered barrier should be closely analyzed to precisely assess the safety of high-level radioactive waste repository. In order to evaluate the impact of such processes on the performance of the engineered barrier, a thermal-hydrological-chemical model was developed by using COMSOL Multiphysics and PHREEQC. The coupling of two software was achieved through the application of a sequential non-iterative approach. Model verification was executed through a comparative analysis between the outcomes derived from the developed model and those obtained in prior investigations. Two data were in a good agreement, demonstrating the model is capable of simulating aqueous speciation, adsorption, precipitation, and dissolution. Using the developed model, the geochemical evolution of bentonite buffer under a general condition was simulated as a base case. The model domain consists of 0.5 m of bentonite and 49.5 m of granite. The uraninite (UO2) was assigned at the canister-bentonite interface as the potential source of uranium. Assuming the lifetime of canister as 1,000 years, the porewater mixing without uranium leakage was simulated for 1,000 years. After then, the uranium leakage through the dissolution of uraninite was initiated and simulated for additional 1,000 years. In the base case model, where the porewater mixing between the bentonite and granite was the only considered process, the gypsum tended to dissolve throughout the bentonite, while it precipitated in the vicinity of bentonite-granite boundary. However, the precipitation and dissolution of gypsum only showed a limited effect on the performance of the bentonite. Due to the low solubility of uraninite in the reduced environment, only infinitesimal amounts of uranium dissolved and transported through the bentonite. Additional cases considering various environmental processes, such as seawater or cement porewater intrusion, will be further investigated.

Effective containment and disposal of high-level radioactive waste is critical to ensure long-term environmental and human safety. Especially bentonite, which is widely used as a buffer material due to its favorable characteristics such as swelling ability and low permeability, plays an important role in preventing the migration of radioactive waste into the surrounding environment. However, the long-term performance of bentonite buffer remains an area of ongoing investigation, with particular attention focused on erosion mechanisms induced by swelling and groundwater flow. The erosion of the bentonite buffer can significantly impact the integrity of buffer and lead to the formation of colloids, which could potentially facilitate the transport of radionuclides through groundwater. Therefore, quantification of bentonite buffer erosion based on an understanding of the underlying mechanisms and factors that influence bentonite buffer erosion, is essential for the safety assessment of high-level radioactive waste repositories. In this study, we aimed to develop a bentonite buffer erosion model using the Adaptive Processbased total system performance assessment framework for a geological disposal system (APro) proposed by the Korea Atomic Energy Research Institute (KAERI). The impact of bentonite erosion on performance assessment can be broadly divided into bentonite property degradation by the penetration of the bentonite buffer into rock fractures and the formation of pseudocolloids. To simulate this phenomenon, Two-region model based on a dynamic bentonite diffusion model is adopted, which can quantify the extent of bentonite intrusion and loss by erosion. Using this Tworegion model, a numerical model was developed to simulate the degradation of bentonite properties based on the amount of bentonite intrusion, as well as to simulate the migration of pseudocolloids in the near-field by deriving the amount of pseudocolloid production based on the loss of bentonite and the sorption rate of radionuclides. To check the applicability of the developed numerical model, preliminary analysis was performed for the effect of bentonite erosion in terms of process-based performance assessment. It is anticipated that this comprehensive model developed in this study will contribute to the accurate and reliable assessment of the long-term performance and safety of high-level radioactive waste repositories.

The post-closure safety assessment of a repository is typically conducted over an extensive timescale from ten thousand to a million years. Considering that biosphere ecosystems may undergo significant changes over such lengthy periods, it is essential to incorporate the long-term evolution of the biosphere into the safety assessment. Climate change and landscape development are identified as critical drivers with the potential to impact the hydrogeological and hydrogeochemical characteristics of the biosphere. These changes can subsequently alter the migration patterns of radionuclides through the biosphere and influence human exposure doses. Therefore, this study formulates scenarios within the context of long-term biosphere evolution. We examine biosphere assessment processes employed in other countries and conduct a comparative study on scenario conditions. For example, biosphere assessment in Finland has identified sea-level changes and land-use alterations as significant factors in the long-term evolution of the biosphere. These factors are linked to Features, Events, and Processes (FEPs) associated with climate change and human activities. Sea-level changes are related to FEPs regarding climate change, land uplift, and shoreline displacement, while land-use changes are based on human activity-related FEPs (e.g., crop type, livestock and forest management, well construction, and demographics). Based on the literature review, this study has configured long-term evolution scenarios for the safety assessment of a deep geological repository for spent fuels.

Safety assessments for geological disposal systems extend over tens of thousands of years, taking into account the radiotoxicity decay period of spent nuclear fuel. During this extensive period, the biosphere experiences multiple glacial cycles, and fluctuations in seawater amounts, attributed to the formation and melting of glaciers, lead to global sea level changes known as eustacy. These sea level changes can directly influence the land-sea interface and groundwater flow dynamics, consequently affecting the pathways of radionuclide transport - an essential element of dose assessment. Therefore, this study aims to investigate how glacial cycles and sea level changes impact radionuclide transport within geological disposal systems, especially in the biosphere. To achieve this objective, we obtained climate evolution data including sea level changes for the Korean Peninsula over a 200,000-years, simulated by a General Circulation Model (GCM). These data were then employed to predict site and hydrology evolutions. The study site was conceptualized biosphere of Artificial Disposal System (ADioS), and we utilized the Soil and Water Assessment Tool (SWAT) to simulate hydrological evolution. These datasets, encompassing climate, site, and hydrology evolution, were collectively employed as inputs for the biosphere module of Adaptive Process-Based Total System Performance Assessment Framework (APro). Subsequently, the APro’s biosphere module calculated radionuclide transport in groundwater flow and its release into surface water bodies, considering the influences of glacial cycles and sea level changes. The results show that hydrologic changes due to sea level change are relatively minor, while the impact of sea level change on groundwater flow and discharge is significant. Additionally, we identified that among the water bodies within ADioS, including rivers, lakes, and oceans, the ocean exhibits the most substantial radionuclide outflow throughout the entire period. The spatiotemporal distributions of radionuclides computed within APro will be further processed into a grid format and used as input for the dose assessment module. Through this study, it was possible to determine the impact of long-term glacial cycles and sea level changes on radionuclide transport. Additionally, this module can serve as a valuable tool for providing the spatiotemporal variability of radionuclides required for enhanced dose assessments.

Understanding the long-term geochemical evolution of engineered barrier system is crucial for conducting safety assessment in high-level radioactive waste disposal repository. One critical scenario to consider is the intrusion of seawater into the engineered barrier system, which may occur due to global sea level rise. Seawater is characterized by its high ionic strength and abundant dissolved cations, including Na, K, and Mg. When seawater infiltrates an engineered barrier, such dissolved cations displace interlayer cations within the montmorillonite and affect to precipitation/ dissolution of accessory minerals in bentonite buffer. These geochemical reactions change the porewater chemistry of bentonite buffer and influence the reactive transport of radionuclides when it leaked from the canister. In this study, the adaptive process-based total system performance assessment framework (APro), developed by the Korea Atomic Energy Research Institute, was utilized to simulate the geochemical evolution of engineered barrier system resulting from seawater intrusion. Here, the APro simulated the geochemical evolution in bentonite porewater and mineral composition by considering various geochemical reactions such as mineral precipitation/dissolution, temperature, redox processes, cation exchange, and surface complexation mechanisms. The simulation results showed that the seawater intrusion led to the dissolution of gypsum and partial precipitation of calcite, dolomite, and siderite within the engineered barrier system. Additionally, the composition of interlayer cation in montmorillonite was changed, with an increase in Na, K, and Mg and a decrease in Ca, because the concentrations of Na, K, and Mg in seawater were 2-10 times higher than those in the initial bentonite porewater. Further studies will evaluate the geochemical sorption and transport of leaked uranium-238 and iodine-129 by applying TDB-based sorption model.

The Korea Atomic Energy Research Institute (KAERI) is currently developing a process-based performance assessment model known as APro. Distinguished from the previous system-level safety assessment model developed by KAERI, APro exhibits the capacity to encompass a threedimensional biosphere domain, evolving over the long term. In this study, we elucidate the methodology employed in developing the dose assessment module of APro and present the module’s functionalities. The procedural steps underlying radiation dose calculations within the APro framework can be succinctly outlined as follows: 1) Definition of a landscape model, utilizing information derived from a specified snapshot period provided by the APro biosphere transport module; 2) Generation of unit biotope objects spanning the landscape; 3) Evaluation of radionuclide transfer within the soil medium; 4) Calculation of activity concentration for flora and fauna groups; 5) Assessment of the distribution of effective dose among representative human groups; 6) Progressing through successive time steps. The APro dose calculation module exhibits notable capabilities that encompass: 1) Accounting for radionuclide decay and ingrowth; 2) Facilitating transfer through unsaturated porous media; 3) Considering sorption effects; 4) Addressing the inheritance of radioactivity between various landscape models; 5) Offering customizable ecosystem parameters; 6) Providing flexibility for user-defined exposure pathways. Leveraging these functionalities of the dose assessment module, APro is proficient in evaluating the distribution of radiological doses and associated risks for representative population groups, all while accounting for the dynamic, long-term evolution of the biosphere, including alterations in land cover.

Conducting a TSPA (Total System Performance Assessment) of the entire spent nuclear fuel disposal system, which includes thousands of disposal holes and their geological surroundings over many thousands of years, is a challenging task. Typically, the TSPA relies on significant efforts involving numerous parts and finite elements, making it computationally demanding. To streamline this process and enhance efficiency, our study introduces a surrogate model built upon the widely recognized U-network machine learning framework. This surrogate model serves as a bridge, correcting the results from a detailed numerical model with a large number of small-sized elements into a simplified one with fewer and large-sized elements. This approach will significantly cut down on computation time while preserving accuracy comparable to those achieved through the detailed numerical model.

APro, a process-based total system performance assessment (TSPA) tool for a geological disposal system, has a framework for simulating the radionuclide transport affected by thermal, hydraulic, mechanical or geochemical changes occurred in the disposal system. APro aims to be applied for the TSPA to long-term (> 100,000) evolution scenarios in real-world repository having more than 10,000 boreholes. In this large-scale TSPA, it is important not only to develop a high-performance numerical approach, but also to apply an efficient post-processing approach to massive spatiotemporal data. The post-processing refers to validating numerical analysis results, analyzing and evaluating target systems through data processing or visualization. Since APro uses COMSOL interface, the postprocessing function in COMSOL can be used. However, when the data size increases due to largescale numerical analysis, the time for the COMSOL post-processing increases, resulting in a problem that the analysis and evaluation are not performed effectively. In this case, it is possible to extract necessary data using the COMSOL exporting function and importing it into an external postprocessing program for the analysis and evaluation. In this study, the efficiency of external post-processing with extracted data from COMSOL was reviewed. And, we derived a proper data extraction approach (format and structure) that can increase efficiency of external post-processing.

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.

Bentonite is a widely used buffer material in high-level radioactive waste repositories due to its favorable properties, including its ability to swell and low permeability. Bentonite buffers play an important role in safe disposal by providing a low permeability barrier and preventing radionuclides migration into the surrounding rock. However, the long-term performance of the bentonite buffer is still an area of research, and one of the main concerns is the erosion of the buffer due to swelling and groundwater flow. Erosion of the bentonite buffer can have a significant impact on repository safety by reducing the integrity of the buffer and forming colloids that can transport radionuclides through groundwater, potentially increasing the risk of radionuclide migration. Therefore, understanding the mechanisms and factors that influence the erosion of the bentonite buffer is critical to the safety assessment of high-level radioactive waste repositories. In this study, we attempted to develop the bentonite buffer erosion model using Adaptive Processbased total system performance assessment framework for a geological disposal system (APro) proposed by the Korea Atomic Energy Research Institute (KAERI). First, the erosion phenomenon was divided into two stages: bentonite buffer penetration into rock fractures and colloid formation. As an initial step in the development of the buffer erosion model, a bentonite buffer intrusion into the fracture and consequent degradation of buffer property were considered. For this purpose, a tworegion model based on the dynamic bentonite diffusion model was adopted which is one of the methods for simulating bentonite buffer intrusion. And, it was assumed that the buffer properties, such as density, porosity and permeability, thermal conductivity, modulus of elasticity, and mechanical strength, are degraded as the buffer erodes. The bentonite buffer degradation model developed in this study will serve as a foundation for the comprehensive buffer erosion model, in conjunction with the colloidal formation model in the future.

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.

The timescale of safety assessment for a geological disposal system is considered up to hundreds of thousands of years when the radionuclides in spent nuclear fuel decay to levels comparable to natural radioactivity. During this long period, a variety of climate changes are expected to occur, including variations in temperature and precipitation as well as long-term sea level changes and glacial cycles. These climate changes can either directly affect water balance components or indirectly affect water balance by altering terrain and vegetation that have an impact on water balance. Water balance is a significant element of safety assessment, because it affects the radionuclide transport via groundwater flow, which in turn affects the radiological risk to humans and other biotas. Therefore, it is important to understand the hydrologic response to climate changes for proving the long-term safety of the disposal system. To this end, this study performed hydrological simulations using the SWAT (Soil and Water Assessment Tool) for several climate change scenarios. SWAT is the watershed-scale hydrological model developed by the USDA-ARS (United States Department of Agriculture - Agricultural Research Service) and has been widely used to quantify the water balance in a watershed. It calculates the hydrologic cycle based on the water balance equation with different physical processes for water balance components such as evapotranspiration, surface runoff, and groundwater recharge. This study assumed several climate change scenarios (e.g., variations in temperature and precipitation, sea level change, and formation of permafrost) and analyzed how the components of the water balance would respond under different scenarios and which scenarios would have the greatest impact on the water balance. These findings can provide valuable insights for future long-term safety assessments on the Korean Peninsula and can also be used as input data for the biosphere module of APro (Adaptive process-based total system performance assessment framework).

To conduct numerical simulation of a disposal repository of the spent nuclear fuel, it is necessary to numerically simulate the entire domain, which is composed on numerous finite elements, for at least several tens of thousands of years. This approach presents a significant computational challenge, as obtaining solutions through the numerical simulation for entire domain is not a straightforward task. To overcome this challenge, this study presents the process of producing the training data set required for developing the machine learning based hybrid solver. The hybrid solver is designed to correct results of the numerical simulation composed of coarse elements to the finer elements which derive more accurate and precise results. When the machine learning based hybrid solver is used, it is expected to have a computational efficiency more than 10 times higher than the numerical simulation composed of fine elements with similar accuracy. This study aims to investigate the usefulness of generating the training data set required for the development of the hybrid solver for disposal repository. The development of the hybrid solver will provide a more efficient and effective approach for analyzing disposal repository, which will be of great importance for ensuring the safe and effective disposal of the spent nuclear fuel.

With the increasing demand for a repository to safely dispose of high-level radioactive waste (HLW), it is imperative to conduct a safety assessment for HLW disposal facilities for ensuring the permanent isolation of radionuclides. For this purpose, the Korea Atomic Energy Research Institute (KAERI) is currently developing the Adaptive Process-based total system performance assessment framework for a geological disposal system (APro). A far-field module, which specifically focuses on fluid flow and radionuclide transport in the host rock, is one of several modules comprising APro. In Korea, crystalline rock is considered the host rock for deep geological disposal facilities due to its high thermal conductivity and extremely low permeability. However, the presence of complex fracture system in crystalline rock poses a significant challenge for managing fluid flow and nuclide transport. To address this challenge, KAERI is participating in DECOVALEX-2023 Task F1, which seeks to compare and verify modeling results using various levels of performance assessment models developed by each country for reference disposal systems. Through the benchmark problems suggested by DECOVALEX-2023 Task F1, KAERI adopts the Discrete Fracture-Matrix (DFM) as the primary fracture modeling approach. In this study, the transport processes of reactive tracers in fractured rock, modeled with DFM, are simulated. Specifically, three different tracers (conservative, decaying, adsorbing) are introduced through the fracture under identical injecting conditions. Thereafter, the breakthrough curves of each tracer are compared to observe the impact of reactive tracers on nuclide transport. The results of this study will contribute to a better understanding of nuclide behavior in subsurface fractured rock under various conditions.

The development of Features, Events, and Processes (FEPs) and scenarios, which consider the longterm evolution of repository, is underway, along with the construction of input data and a model database for the adaptive process-based total system performance assessment framework, APro. PAPiRUS serves as an integrated information processing platform, enabling users to seamlessly access, search, and extract essential information. To enhance data usability, it is crucial to establish well-structured metadata for each dataset. Regarding FEPs, individual FEPs consist of extensive text-based data and sets of other short textual data. To enhance the searchability of these FEPs, precise keywords must be assigned to each FEP. For user convenience, the PAPiRUS FEP database contains several FEPs not only the long-term evolution FEPs developed by KAERI but also thousands of FEPs form the databases such as NEA PFEPs and Posiva FEPs. Generating keywords for thousands of FEPs proves to be a labor-intensive task. Consequently, this study explores natural language processing techniques for keyword analysis to boost the productivity of the keyword generation process. Specifically, we employ Generative Pretrained Transformer (GPT) models for keyword extraction. Our test results for keyword extraction demonstrate that, although not flawless, providing suitable prompts yields sufficiently useful keyword sets. We identified several optimal prompts and developed an Excel-based program to derive keywords from the existing FEP database using these prompts. By using the outcomes of this study, initial versions of keyword sets for thousands of FEPs can be rapidly produced and subsequently refined through expert review and editing. The generated keywords will serve as metadata within PAPiRUS.

The Korean Nuclear Safety and Security Commission has established a general guideline for the disposal of high-level waste, which requires that radiological effects from a disposal facility should not exceed the regulatory safety indicator, a radiological risk. The post-closure safety assessment of the disposal facility aims to evaluate the radiological dose against a representative person, taking into account nuclide transport and exposure pathways and their corresponding probabilities. The biosphere is a critical component of radiation protection in a disposal system, and the biosphere model is concerned with nuclide transport through the surface medium and the doses to human beings due to the contaminated surface environment. In past studies by the Korea Atomic Energy Research Institute (KAERI), the biosphere model was constructed using a representative illustration of surface topographies and groundwater conditions, assuming that the representative surface environment would not change in the future. Each topography was conceptualized as a single compartment, and distributed surface contamination over the geometrical domain was abstracted into 0D. As a result, the existing biosphere model had limitations, such as a lack of quantitative descriptions of various transport and exposure pathways, and an inability to consider the evolution of the surface environment over time. These limitations hinder the accurate evaluation of radiological dose in the safety assessment. To overcome these limitations, recent developments in biosphere modeling have incorporated the nuclide transport process over a 2D or 3D domain, integrating the time-dependent evolution of the surface environment. In this study, we reviewed the methodology for biosphere modeling to assess the radiological dose given by distributed surface contamination over a 2D domain. Based on this review, we discussed the model requirements for a numerical module for biosphere dose assessment that will be implemented in the APro platform, a performance assessment tool being developed by the KAERI. Finally, we proposed a conceptual model for the numerical module of dose assessment.

In the engineered barrier system of deep geological disposal repository, complex physicochemical phenomena occur throughout the entire disposal time, consequently impacting the safety function. The bentonite buffer, a significant component of the engineered barrier system, can be geochemically altered due to the changes in host rock groundwater, temperature, and redox condition. Such changes may have direct or indirect effects on radionuclide migration in case of canister failure. Therefore, a modeling tool that accounts for coupled thermal-hydraulic-mechanical-chemical (THMC) processes is necessary for the safety assessment. To this end, the Korea Atomic Energy Research Institute (KAERI) has developed the APro, a modeling interface for conducting safety assessment of deep geological disposal repository. The APro considers coupled THMC processes that influence radionuclide migration. Here, the solute transport considering thermal and hydraulic processes are calculated using the COMSOL multi-physics, while geochemical reactions are carried out in PHREEQC. The two software are coupled using a sequential non-iterative operator splitting approach, and transport of non-water H, non-water O, and charge were additionally considered to enhance the coupling model stability. Finally, the applicability of APro to simulate long-term geochemical evolution of bentonite was demonstrated through benchmark studies to evaluate the effects of mineral precipitation/dissolution, temperature, redox, and seawater intrusion.

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.