Review on Screening Process of Radionuclides List for a Safety Assessment of Geological Disposal

Heejae Ju,Jung-Woo Kim 한국방사성폐기물학회 2022 한국방사성폐기물학회 학술논문요약집 Vol.20 No.1

An objective of a safety assessment for geological disposal is to evaluate the radiological impact by radionuclides release from radioactive wastes. Computational estimation of all radionuclides transport in the disposal system, however, is not neccessary because some radionuclides has negligible effect on radiological doses. For this reason, prioritization of radionuclides list is preceded before the safety assessment. The Korea Atomic Energy Research Institue (KAERI) has assessed the long-term safety of a disposal system for spent nculear fuels. Currently, thirty eight radionuclides and twenty three elements are considered in the safety assessment activity of the KAERI. Nevertheless, a screening process for radionulides selection has not been articulated yet. In this study, we reviewed radionuclides selection process in forign countries to re-establish screening criteria for the KAERI’s radionuclides list. Screeing models of the Swedish Nuclear Fuel and Waste Management Company (SKB), the Deparment of Eenrgy (US DOE), and the Japan Nuclear Cycle Development Istitute (JNC) were compared. We found that each country developed different screening model depending on scenarios of radionuclides release. Nonetheless, there were common properties that determines the importance of radionuclides. These properties for radionuclides include halflife, radiotoxicity (or specific activity), and mobility in underground medium. Based on the review results, we proposed radionuclides selection process to prioritize the importance of radionucldies in the KAERI safety assessment.

Review of Degradation of the Spent Nuclear Fuel Matrix for a Safety Assessment

Heejae Ju,Jung-woo Kim,Dong-Keun Cho 한국방사성폐기물학회 2021 한국방사성폐기물학회 학술논문요약집 Vol.2021 No.06

Systematic model for estimation of future inadvertent human intrusion into deep rad-waste repository by domestic groundwater well drilling

Ju, Heejae,Hwang, Il-Soon North-Holland Pub. Co 2018 Nuclear engineering and design Vol.327 No.-

<P><B>Abstract</B></P> <P>Future human intrusion into a geological repository for spent nuclear fuels and radioactive waste is a safety case that inherently involves a high uncertainty, especially in areas with a high population density. The uncertainty associated with inadvertent human intrusion needs to account for the complexity of various conceivable circumstances with the long-term evolution of society or technology. In this study, a new dynamic Monte Carlo model is developed to properly incorporate the potential future human intrusion frequency, which has never been performed in past studies. The developed model for inadvertent deep groundwater well drilling into a repository focuses on the assessment of the quantitative effects of factors mitigating or enhancing future human intrusion risk. Assuming the current groundwater well depth distribution in the Gyeongsangnam-do region of the Republic of Korea, the future human intrusion frequency is estimated to be 5.89 × <SUP> 10 - 4 </SUP> 1 / yr for a repository with a depth of 500 m and a hypothetical area of 5.27 × <SUP> 10 - 1 </SUP> <SUP> km 2 </SUP> . The model predicts that the frequency may reach up to 2.18 × <SUP> 10 - 3 </SUP> 1 / yr as the depth of a groundwater well increases in the future, as expected from the data trending performed in this study. A sensitivity analysis shows that a proper design can suppress the frequency, which increases positively with the repository area and negatively with the depth of the repository. However, mitigation by a repository design tends to be weakened as the well depth distribution increases. Since the average well depth increases with time, the mitigation effects achieved by reducing the area or increasing the depth of a repository may not be effective against the current expectation. In this case, the most reliable approach for minimizing future human intrusion risk will be a reduction in the radiotoxicity concentration of the waste.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Frequency and risk of human intrusion into a geological repository are assessed. </LI> <LI> Dynamic Monte Carlo model is developed to incorporate various factors increasing or decreasing the risk of human intrusion human intrusion. </LI> <LI> Regulatory enforcement, knowledge, depth and area of repository are mitigating factors. </LI> <LI> Demand of groundwater and utilization of surface above repository are factors enhancing the risk of human intrusion. </LI> <LI> Reduced radiotoxicity concentration of a radioactive waste is effective to diminish the risk of human intrusion than reduced area or increased depth of repository. </LI> </UL> </P>

System Understanding of Long-term Safeguards for a Closed Repository

Heejae Ju,Il Soon Hwang,Sungyeol Choi 한국방사성폐기물학회 2018 한국방사성폐기물학회 학술논문요약집 Vol.2018 No.10

Game-Theoretic Approach for Safeguards Program of a Geological Repository for Spent Nuclear Fuels During Post-Closure Period

Heejae Ju,Il Soon Hwang,Sungyeol Choi 한국방사성폐기물학회 2018 한국방사성폐기물학회 학술논문요약집 Vol.2018 No.05

Conceptual Model Development for a Biosphere Dose Assessment Module in a Performance Assessment Tool (the APro)

Heejae Ju,Minjeong Kim,Jung-Woo Kim 한국방사성폐기물학회 2023 한국방사성폐기물학회 학술논문요약집 Vol.21 No.1

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.

Geochemical Model for the Oxidative Dissolution UO2 in a Geological Repository

Heejae Ju,Ji-Hun Ryu,Seung Yeop Lee,Jae-Kwang Lee 한국방사성폐기물학회 2019 한국방사성폐기물학회 학술논문요약집 Vol.2019 No.10

Methodology and Capability of APro’s Dose Assessment Module

Heejae Ju,Minjeong Kim,Soobin Kim,Jung-Woo Kim 한국방사성폐기물학회 2023 한국방사성폐기물학회 학술논문요약집 Vol.21 No.2

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.

Markov chain model for inadvertent human intrusion into geological repositories for high level wastes

Ju, Heejae,Choi, Sungyeol,Hwang, Il-Soon Elsevier 2019 Nuclear engineering and design Vol.341 No.-

<P><B>Abstract</B></P> <P>Inadvertent human intrusion into a geological repository for radioactive waste is an incident of low frequency but high consequence. Until now, many studies have considered the frequency of deep borehole drilling for resource explorations in the site of the repository as a time-independent variable. However, future activities and technology of the human race will not be the same as today. Therefore, this study develops a new Markov chain model to estimate the frequency of human intrusion using time-dependent drilling frequencies based on the statistics of oil and gas exploration worldwide. The results showed that the frequency of human intrusion during the early time period is substantially reduced. After a few hundred years, the frequency steadily increases and approaches the value of the time-independent model. The low frequency during the early time period is attributed to enforcement of regulation, continuous knowledge of repository, and low utility of repository area. As these effects disappear, the frequency rapidly increases due to the future demand of resource exploration, which is a significant factor in increasing the risk of human intrusion. In addition, the reduction of average radiotoxicity in final waste is effective in reducing the risk, while the reduction of waste volume is insignificant for the frequency of human intrusion in the long-term.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Assess Frequency and risk of human intrusion into a geological repository. </LI> <LI> Consider a time-dependent drilling probability in a new model for resource exploration. </LI> <LI> Human intrusion becomes vigorous for demands of resource explorations in the long-term. </LI> <LI> Human intrusion is mitigated by enforcement of regulation and continuous knowledge during early time. </LI> <LI> Reduced average radiotoxicity is effective to diminish the risk than reduced volume. </LI> </UL> </P>

A Methodology Using Machine Learning for System-Level Safety Assessment Considering Complex Processes in the Near-Field of Geological Disposal System

Heejae Ju,Jung-Woo Kim,Jaewon Lee,Gil-Eon Jeong,Dong-Keun Cho 한국방사성폐기물학회 2023 한국방사성폐기물학회 학술논문요약집 Vol.21 No.2

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.