• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.179-185
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• 2010

In a sensitivity analysis, an uncertainty importance measure is often used to assess how much uncertainty of an output is attributable to the uncertainty of an input, and thus, to identify those inputs whose uncertainties need to be reduced to effectively reduce the uncertainty of output. A function is called monotonic if the output is either increasing or decreasing with respect to any of the inputs. In this paper, for a monotonic function, we propose a method for evaluating the measure which assesses the expected percentage reduction in the variance of output due to ascertaining the value of input. The proposed method can be applied to the case that the output is expressed as linear and nonlinear monotonic functions of inputs, and that the input follows symmetric and asymmetric distributions. In addition, the proposed method provides a stable uncertainty importance of each input by discretizing the distribution of input to the discrete distribution. However, the proposed method is computationally demanding since it is based on Monte Carlo simulation.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4698-4707
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• 2022

As part of the ICRP Task Group 103 project, we developed ten thyroid models for the pediatric mesh-type reference computational phantoms (MRCPs). The thyroid is not only a radiosensitive target organ needed for effective dose calculation but an important source region particularly for radioactive iodines. The thyroid models for the pediatric MRCPs were constructed by converting those of the pediatric voxel-type reference computational phantoms (VRCPs) in ICRP Publication 143 to a high-quality mesh format, faithfully maintaining their original topology. At the same time, we improved several anatomical parameters of the thyroid models for the pediatric MRCPs, including the mass, overlying tissue thickness, location, and isthmus dimensions. Absorbed doses to the thyroid for the pediatric MRCPs for photon external exposures were calculated and compared with those of the pediatric VRCPs, finding that the differences between the MRCPs and VRCPs were not significant except for very low energies (<0.03 MeV). Specific absorbed fractions (target ⟵ thyroid) for photon internal exposures were also compared, where significant differences were frequently observed especially for the target organs/tissues close to the thyroid (e.g., a factor of ~1.2-~327 for the thymus as a target) due mainly to anatomical improvement of the MRCP thyroid models.

• Journal of the Korean Geotechnical Society
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• v.22 no.4
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• pp.73-83
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• 2006

Seepage analysis through unsaturated zone based on the theory of unsaturated flow is commonly performed to evaluate dam safety. However, the concepts of unsaturated soil behavior have not been transferred into the hands of practicing geotechnical engineers since the problems involving unsaturated soils often have the appearances of being extremely complex. There is variability and uncertainty associated with the unsaturated hydraulic properties that in turn will lead to variability in predicting unsaturated soil behavior such as seepage rate and the pore water pressure distribution. In this paper, measurements of the soil-water characteristic curve and saturated hydraulic conductivity for the core material of dam were conducted. Then, finite element stochastic analysis was used to capture the effect of unsaturated hydraulic properties on the seepage behavior of dam. It is observed that the amount of seepage increases, as the values of unsaturated soil parameters a and n increase. The values of m and p showed opposite trend.

• Journal of the Korean Geotechnical Society
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• v.22 no.6
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• pp.51-61
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• 2006

An efficient and accurate hybrid reliability analysis method is proposed in this paper to quantify the risk of an axially loaded single pile considering pile-soil interaction behavior and uncertainties in various design variables. The proposed method intelligently integrates the concepts of the response surface method, the finite difference method, the first-order reliability method, and the iterative linear interpolation scheme. The load transfer method is incorporated into the finite difference method for the deterministic analysis of a single pile-soil system. The uncertainties associated with load conditions, material and section properties of a pile and soil properties are explicitly considered. The risk corresponding to both serviceability limit state and strength limit state of the pile and soil is estimated. Applicability, accuracy and efficiency of the proposed method in the safety assessment of a realistic pile-soil system subjected to axial loads are verified by comparing it with the results of the Monte Carlo simulation technique.

• Composites Research
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• v.19 no.3
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• pp.7-14
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• 2006

In this paper, an integrated probabilistic strength analysis was conducted to predict the reliability of a composite pressure vessel under inner pressure loading condition. As a probabilistic strength analysis, the probabilistic progressive failure model consisting of progressive failure model and Monte Carlo simulation was incorporated with a commercial FEA code, ABAQUS Standard, to perform the probabilistic failure analysis of composite structure which has a complex shape and boundary conditions. As design random variables, the laminar strengths of each direction were considered. Finally, from probabilistic strength analysis, the scattering of burst pressure could be explained and the reliability of composite pressure vessel could be obtained for each component. In case of composite structures in mass production, the effects of uncertainties in material and manufacturing on the performance of composite structures would apparently become larger. So, the probabilistic strength analysis is essential for the structural design of composite structures in mass production.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.1949-1958
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• 2023

The International Commission on Radiological Protection (ICRP) Publication 116 was released to provide a comprehensive dataset of the dose coefficients (DCs) for external exposures produced with the adult reference voxel phantoms of ICRP Publication 110. Although an advanced skeletal dosimetry method for photons and neutrons using fluence-to-dose response functions (DRFs) was introduced in ICRP Publication 116, the ICRP-116 skeletal DCs were calculated by using the simple method conventionally used (i.e., doses to red bone marrow and endosteum approximated by doses to spongiosa and/or medullary cavities). In the present study, the photon and neutron DRFs were used to produce skeletal DCs of the ICRP-110 reference phantoms, which were then compared with the ICRP-116 DCs. For photons, there were significant differences by up to ~2.8 times especially at energies <0.3 MeV. For neutrons, the differences were generally small over the entire energy region (mostly <20%). The general impact of the DRF-based skeletal DCs on the effective dose calculations was negligibly small, supporting the validity of the ICRP-116 effective DCs despite their skeletal DCs derived from the simple method. Meanwhile, we believe that the DRF-based skeletal DCs could be beneficial in better estimates of skeletal doses of individuals for risk assessments.

• 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.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2380-2387
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• 2023

Hyperspectral data and its ability to explore the minerals and their associated rocks have a remarkable application in mineral exploration and lithological characterization. The present study aims to explore the radiation shielding aspects of the iron ore in Kerala with the aid of the Hyperion hyperspectral dataset. The reflectance-spectra obtained from the laboratory conditions as well as from the image show various absorptions. The results from the spectra are validated with geochemical data and GPS points. The Monte Carlo simulation employed to evaluate the radiation shielding ability. Raising the oxygen ions caused a noteworthy decrease in the µ values of the studied rocks which is accompanied by an increase in Δ_0.5 and Δ_eq values. The Δ_0.5 and Δ_eq values increased by factors of approximately 77 % with raising the oxygen ions between 44.32 and 47.57 wt.%. The µ values varies with the oxygen concentrations, where the µ values decreased from 2.531 to 0.925 cm^-1 (at 0.059 MeV), from 0.381to 0.215 cm^-1 (at 0.662 MeV), and from 0.279 to 0.158 cm^-1 (at 1.25 MeV) with raising the oxygen ions from 44.32 to 47.43 wt.%.

• 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 IKEEE
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• v.27 no.4
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• pp.657-667
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• 2023

This paper proposes two-stage optimization framework to re-estimate the photovoltaic (PV) hosting capacity (HC) by improving parameters for voltage controls of the smart inverter. In the first stage, PV HC is estimated considering Volt-Var (VV) and Volt-Watt (VW) controls, aligning with IEEE Std 1547-2018 guidelines. In the second stage, adjust parameters of VV and VW to improve HC. To investigate the performance of the proposed algorithm, simulations conducted using OpenDSS on an IEEE 37-bus system. The results demonstrate that effectively increases PV HC.