• Journal of Korea Trade
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• v.27 no.2
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• pp.96-114
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• 2023

Purpose - This paper elucidates a nexus between the occurrence of rare disaster events and the volatility of economic growth by distinguishing the likelihood of rare events from stochastic volatility. We provide new empirical facts based on a quarterly time series. In particular, we focus on the role of financial liberalization in spreading the economic crisis in developing countries. Design/methodology - We use quarterly data on consumption expenditure (real per capita consumption) from 44 countries, including advanced and developing countries, ending in the fourth quarter of 2020. We estimate the likelihood of rare event occurrences and stochastic volatility for countries using the Bayesian Markov chain Monte Carlo (MCMC) method developed by Barro and Jin (2021). We present our estimation results for the relationship between rare disaster events, stochastic volatility, and growth volatility. Findings - We find the global common disaster event, the COVID-19 pandemic, and thirteen country-specific disaster events. Consumption falls by about 7% on average in the first quarter of a disaster and by 4% in the long run. The occurrence of rare disaster events and the volatility of gross domestic product (GDP) growth are positively correlated (4.8%), whereas the rare events and GDP growth rate are negatively correlated (-12.1%). In particular, financial liberalization has played an important role in exacerbating the adverse impact of both rare disasters and financial market instability on growth volatility. Several case studies, including the case of South Korea, provide insights into the cause of major financial crises in small open developing countries, including the Asian currency crisis of 1998. Originality/value - This paper presents new empirical facts on the relationship between the occurrence of rare disaster events (or stochastic volatility) and growth volatility. Increasing data frequency allows for greater accuracy in assessing a country's specific risk. Our findings suggest that financial market and institutional stability can be vital for buffering against rare disaster shocks. It is necessary to preemptively strengthen the foundation for financial stability in developing countries and increase the quality of the information provided to markets.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.156-156
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• 2021

본 연구는 지역빈도해석을 기반으로한 인공신경망 모델과 기존에 널리 사용되는 방법인 홍수지수법의 성능을 몬테카를로 시뮬레이션을 이용하여 평가하였다. 컴퓨터 기술이 발달함에 따라 인공지능에 대한 접근성이 좋아지며 수문학을 포함한 다양한 분야에 적용되고 있다. 인공지능을 이용하여 강수량 및 유량 등 다양한 수문자료에 대한 예측이 이루어지고 있으나 빈도해석에 관한 연구는 비교적 적다. 본 연구에서 사용된 인공 지능 모델은 대상 지점의 지형학적 자료와 수문학적 자료를 이용하여 인공신경망을 통해 지점의 확률강우량(QRT-ANN) 및 확률분포형의 매개변수 (PRT-ANN)를 추정한다. 지형학적 자료로는 위도, 경도 그리고 고도가 사용되었으며 수문학적 자료로는 대상 지점의 최근 30년 일일연최대강우량을 사용하였다. 지역빈도해석의 정확도는 지역 내 통계적 특성이 비슷한 지점들이 포함되면 될수록 높아진다. 통계적 특성으로는 불일치 척도, 이질성 척도, 적합성 척도가 있으며 다양한 조건의 통계적 특성에 따른 세 개의 지역빈도해석 방법의 성능을 평가하고자 하였다. 대상 지역 내 n개의 지점이 있다고 가정하였을 때, 홍수지수법의 경우 n-1개의 지점으로 추정한 지역 성장곡선을 이용하여 나머지 1개 지점의 확률강우량을 산정할 수 있으며 인공신경망 모델들 또한 n-1개 지점들의 자료를 이용하여 모델을 구축한 뒤 나머지 지점의 확률강우량 및 확률분포형의 매개변수를 예측할 수 있다. PRT-ANN의 경우 예측된 매개변수를 이용하여 확률강우량을 산정하며 시뮬레이션 시행마다 발생시킨 자료의 지점빈도해석 결과에 대한 나머지 세 방법의 평균 제곱근 상대오차 (Relative root mean square error, RRMSE)를 계산하였다. 몬테카를로 시뮬레이션을 이용한 성능 분석을 통하여 관측값의 다양한 통계적 특성에 맞는 지역빈도해석 방법을 제시할 수 있을 것으로 판단된다.

• Journal of Radiation Protection and Research
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• v.48 no.2
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• pp.90-99
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• 2023

Background: Quantitative risk assessments should be accompanied by uncertainty analyses of the risk models employed in the calculations. In this study, we aim to develop a computational code named SUMRAY for use in cancer risk projections from radiation exposure taking into account uncertainties. We also aim to make SUMRAY publicly available as a resource for further improvement of risk projection. Materials and Methods: SUMRAY has two versions of code written in R and Python. The risk models used in SUMRAY for all-solid-cancer mortality and incidence were those published in the Life Span Study of a cohort of the atomic bomb survivors in Hiroshima and Nagasaki. The confidence intervals associated with the evaluated risks were derived by propagating the statistical uncertainties in the risk model parameter estimates by the Monte Carlo method. Results and Discussion: SUMRAY was used to calculate the lifetime or time-integrated attributable risks of cancer under an exposure scenario (baseline rates, dose[s], age[s] at exposure, age at the end of follow-up, sex) specified by the user. The results were compared with those calculated using another well-known web-based tool, Radiation Risk Assessment Tool (RadRAT; National Institutes of Health), and showed a reasonable agreement within the estimated confidential interval. Compared with RadRAT, SUMRAY can be used for a wide range of applications, as it allows the risk projection with arbitrarily specified risk models and/or population reference data. Conclusion: The reliabilities of SUMRAY with the present risk-model parameters and their variance-covariance matrices were verified by comparing them with those of the other codes. The SUMRAY code is distributed to the public as an open-source code under the Massachusetts Institute of Technology license.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2578-2590
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• 2023

In this work, a 24-month two-batch fuel management strategy for the APR1400 using LEU + has been investigated, where enrichments of 5.9 and 5.2 w/o are utilized in lieu of the conventional 4-5 w/o UO₂ fuel. In addition, an Accident Tolerant Fuel (ATF) clad based on the swaging technology is applied to APR1400 fuel assemblies. In this special ATF clad design, both outer and inner SS316 layers protect the conventional zircaloy clad. Erbia (Er₂O₃) is introduced as a burnable absorber with two-fold goals to lower the critical boron concentration in the long-cycle LEU + loaded core as well as to handle the LEU + fuel in the existing front-end fuel facilities without renewing the license. Two types of fuel assemblies with different loading of gadolinia (Gd₂O₃) are considered to control both the reactivity and the core radial power distribution. The erbia burnable absorber is uniformly admixed with UO₂ in all fuel pins except for the gadolinia-bearing ones. In this study, two core designs were devised with different erbia loading, and core performance and safety parameters were evaluated for each case in comparison with a core design without any burnable absorbers. The core analysis was done using the two-step method. First, cross-sections are generated by the SERPENT 2 Monte Carlo code, and the 3-D neutronic analysis is performed with an in-house multi-physics nodal code KANT.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.99-99
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• 2022

Jeju island has a humid subtropical climate and this climate zone is expected to migrate northward toward the main land, Korea Peninsula, as temperature increases are accelerated. Vegetation type has been inevitably shifted along with the climatic change, having more subtropical species native in southeast Asia or even in Africa. With the forest composition shift, it becomes more important than ever to analyze the water balance of the forest wihth the ongoing as well as upcoming climate change. Here, we implemented the Ecosystem Demography Biosphere Model (ED2) by initializing the key variables using forest inventory data (diameter at breast height in 2012). Out of 10,000 parameter sets randomly generated from prior distribution distributions of each parameter (i.e., Monte-Carlo Method), we selected four behavioral parameter sets using remote-sensing data (LAI-MOD15A2H, GPP-MOD17A2H, and ET-MOD16A2, 8-days at 500-m during 2001-2005), and evaluated the performances using eddy-covariance carbon flux data (2012 Mar.-Sep. 30-min) and remote sensing data between 2006-2020. We simulated each of the four RCP scenarios (2.6, 4.5, 6.0, and 8.5) from four climate forcings (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5 from ISIMIP2b). Based on those 64 simulation sets, we estimate the changes in water balance resulting from the forest composition shift, and also uncertainty in the estimates and the sensitivity of the estimates to the parameters, climate forcings, and RCP scenarios.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.1
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• pp.57-65
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• 2024

In a fire-resistant structure, uncertainties arise in factors such as ventilation, material elasticity modulus, yield strength, coefficient of thermal expansion, external forces, and fire location. The ventilation uncertainty affects thefactor contributes to uncertainties in fire temperature, subsequently impacting the structural temperature. These temperatures, combined with material properties, give rise to uncertain structural responses. Given the nonlinear behavior of structures under fire conditions, calculating fire fragility traditionally involves time-consuming Monte Carlo simulations. To address this, recent studies have explored leveraging machine learning algorithms to predict fire fragility, aiming to enhance efficiency while maintaining accuracy. This study focuses on predicting the fire fragility of a steel moment frame building, accounting for uncertainties in fire size, location, and structural material properties. The fragility curve, derived from nonlinear structural behavior under fire, follows a log-normal distribution. The results demonstrate that the proposed method accurately and efficiently predicts fire fragility, showcasing its effectiveness in streamlining the analysis process.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1204-1212
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• 2024

To accurately calculate the heating distribution of the fast reactor, a neutron-photon library in MATXS format named Knight-B7.1-1968n × 94γ was processed based on the ENDF/B-VII.1 library for ultrafine groups. The neutron cross-section processing code MGGC2.0 was used to generate few-group neutron cross sections in ISOTXS format. Additionally, the self-developed photon cross-section processing code NGAMMA was utilized to generate photon libraries for neutron-photon coupled heating calculations, including photo-atom cross sections for the ISOTXS format, prompt photon production cross sections, and kinetic energy release in materials (KERMA) factors for neutrons and photons, and the self-shielding effect from the capture and fission cross sections of neutron to photon have been taken into account when the photon source generated by neutron is calculated. The interface code GSORCAL was developed to generate the photon source distribution and interface with the DIF3D code to calculate the neutron-photon coupling heating distribution of the fast reactor core. The neutron-photon coupled heating calculation route was verified using the ZPPR-9 benchmark and the RBEC-M benchmark, and the results of the coupled heating calculations were analyzed in comparison with those obtained from the Monte Carlo code MCNP. The calculations show that the library was accurately processed, and the results of the fast reactor neutron-photon coupled heating calculations agree well with those obtained from MCNP.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4287-4294
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• 2023

In order to meet the energy demand, energy production must be done continuously. Hydrogen seems to be the best alternative for this energy production, because it is both an environmentally friendly and renewable energy source. In this study, the hydrogen fuel production of the peaceful nuclear explosives (PACER) fusion blanket as the energy source integrated with Fe-Cl thermochemical water splitting cycle have been investigated. Firstly, neutronic analyzes of the PACER fusion blanket were performed. Necessary neutronic studies were performed in the Monte Carlo calculation method. Molten salt fuel has been considered mole-fractions of heavy metal salt (ThF₄, UF₄ and ThF₄+UF₄) by 2, 6 and 12 mol. % with Flibe as the main constituent. Secondly, potential of the hydrogen fuel production as a result of the neutronic evaluations of the PACER fusion blanket integrated with Fe-Cl thermochemical cycle have been performed. In these calculations, tritium breeding (TBR), energy multiplication factor (M), thermal power ratio (1 - 𝜓), total thermal power (P_hpf) and mass flow rate of hydrogen (ṁ_H2) have been computed. As a results, the amount of the hydrogen production (ṁ_H2) have been obtained in the range of 232.24x10⁶ kg/year and 345.79 x10⁶ kg/year for the all mole-fractions of heavy metal salts using in the blanket.

• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2740-2747
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• 2024

The sintering process acquired ferromagnetic copper ferrite ceramic material with a small concentration of Ni ion at 1100 ℃ for 1 h. Previously, copper ferrite with Ni proportions powder was acquired by the wet chemical process according to the relation CuFe_2-xNi_xO₄ where x takes values 0.0, 0.015, 0.03, 0.04, and 0.05. The role of Ni ion in the copper ferrite structure was investigated by X-ray analysis, Scanning electron microscope, EDX analysis, and density measurements. The gamma-ray shielding properties for the fabricated CuFeNiO ceramics samples were evaluated using the Monte Carlo simulation method. The obtained results show an enhancement in the linear attenuation coefficient for the fabricated ceramics with increasing the insertions of Ni ions within the fabricated samples, where increasing the Ni ions concentration between 0 and 1.19 wt% increases the linear attenuation by between 1.581 and 1.771 cm^-1 (at 0.103 MeV), 0.304-0.338 cm^-1 (at 0.662 MeV), and 0.160-0.178 cm^-1 (at 2.506 MeV), respectively. Simultaneously, the radiation protection efficiency for a 1 cm thickness of the fabricated samples increased between 14.8 and 16.3% with increasing the Ni ions between 0 and 1.19 wt%. Although the Ni doping concentration does not exceed 1.5 wt% of the total composition of the fabricated ceramics, the shielding capacity of the fabricated ceramics was enhanced by more than 11%, along the studied energy interval. Therefore, the fabricated samples can be used in gamma-ray shielding applications.

• Journal of Radiation Protection and Research
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• v.49 no.3
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• pp.102-113
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• 2024

Diffusing alpha-emitters radiation therapy (DaRT) represents a groundbreaking development in cancer therapy, offering a solution to the limitations of conventional radiation therapy. By deploying ²²⁴Ra embedded seeds, DaRT achieves targeted delivery of high-dose alpha particles directly to tumor sites, showing considerable efficacy in tumor control and minimal damage to adjacent healthy tissues. This comprehensive review analyzes the published literature regarding mechanisms, seed production, dose calculation, measurement, and biological experiments related to DaRT. It includes in-depth discussions on mathematical models, Monte Carlo simulations for dose distribution, real-time in vivo dosimetry developments, and biological experiments both in vitro and in vivo. Clinical trial outcomes are also examined to evaluate the therapy's effectiveness in various cancer types. DaRT utilizes ²²⁴Ra-labeled seeds, using the decay chain of ²²⁴Ra to deliver alpha particles effectively within a tumor. Several asymptotic diffusion-leakage models were developed to calculate the alpha dose distribution of DaRT. In vivo dosimetry techniques have been developed for real-time monitoring. Biological experiments demonstrated the cytotoxic effects of DaRT across various cancer cells, with varying radiosensitivity. Additionally, the enhanced effects of combined therapy with chemotherapy and immunotherapy were suggested by many in vivo studies. Clinical trials have shown high complete response rate in squamous cell carcinoma, with minimal side effects, suggesting DaRT's feasibility and safety. DaRT emerges as a highly localized cancer treatment method with minimal side effects compared to traditional radiation therapy. It directly ablates tumors and potentially enhances immune responses, indicating a significant advance in cancer therapy. Future research and ongoing clinical trials will further elucidate its efficacy across different cancer types and in combination with other treatments.