• Nuclear Engineering and Technology
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• v.41 no.1
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• pp.11-20
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• 2009

Radiation effects on materials are inherently multiscale phenomena in view of the fact that various processes spanning a broad range of time and length scales are involved. A multiscale modeling approach to embrittlement of pressure vessel steels is presented here. The approach includes an investigation of the mechanisms of defect accumulation, microstructure evolution and the corresponding effects on mechanical properties. An understanding of these phenomena is required to predict the behavior of structural materials under irradiation. We used molecular dynamics (MD) simulations at an atomic scale to study the evolution of high-energy displacement cascade reactions. The MD simulations yield quantitative information on primary damage. Using a database of displacement cascades generated by the MD simulations, we can estimate the accumulation of defects over diffusional length and time scales by applying kinetic Monte Carlo simulations. The evolution of the local microstructure under irradiation is responsible for changes in the physical and mechanical properties of materials. Mechanical property changes in irradiated materials are modeled by dislocation dynamics simulations, which simulate a collective motion of dislocations that interact with the defects. In this paper, we present a multi scale modeling methodology that describes reactor pressure vessel embrittlement in a light water reactor environment.

• Journal of Korean Society on Water Environment
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• v.36 no.5
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• pp.373-384
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• 2020

Hydrological models are based on a combination of parameters that describe the hydrological characteristics and processes within a watershed. For this reason, the model performance and accuracy are highly dependent on the parameters. However, model uncertainties caused by parameters with stochastic characteristics need to be considered. As a follow-up to the study conducted by Choi et al (2020), who developed a relatively simple semi-distributed hydrological model, we propose a tool to estimate the posterior distribution of model parameters using the Metropolis-Hastings algorithm, a type of Markov-Chain Monte Carlo technique, and analyze the uncertainty of model parameters and simulated stream flow. In addition, the uncertainty caused by the parameters of each version is investigated using the lumped and semi-distributed versions of the applied model to the Hapcheon Dam watershed. The results suggest that the uncertainty of the semi-distributed model parameters was relatively higher than that of the lumped model parameters because the spatial variability of input data such as geomorphological and hydrometeorological parameters was inherent to the posterior distribution of the semi-distributed model parameters. Meanwhile, no significant difference existed between the two models in terms of uncertainty of the simulation outputs. The statistical goodness of fit of the simulated stream flows against the observed stream flows showed satisfactory reliability in both the semi-distributed and the lumped models, but the seasonality of the stream flow was reproduced relatively better by the distributed model.

• Journal of the Korean Society of Radiology
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• v.16 no.5
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• pp.527-536
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• 2022

The radiation shielding characteristic of neutron shielding material has been studied as the preliminary study in order to design cosmic-ray shielding material. Specially, Soft Magnetic Material, known to be effective in EMP and radiation shielding, has been investigated to check if the material would be applicable to cosmic-ray shielding. In this work, thermal neutron shielding experiment was conducted and the Monte Carlo N-Particle(MCNP) was applied to employ skymap.dat, which is cosmic-ray data embedded in MCNP. As a result, polyethylene, borated polyethylene, and carbon nano tube, containing carbon or hydrogen, have been found to be effective in reduction of neutron flux below 20 MeV (including thermal, epithermal, evaporation). In contrast, the materials composed of iron such as SS316 and Soft Magnetic Material show a good shielding performance in the cascade energy range (above 20 MeV). Since Soft Magnetic Material is consisting of 13% of boron, it can also decrease thermal neutron flux, so it is expected that it would show a significant reduction on the entire range of neutron energy if the Soft Magnetic Material is used with hydrogen and carbon, so called low Z material.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.72-77
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• 2002

The development of a Pay Adjustment (PA) procedure for implementing Performance-related Specifications (PRS) is known to be a difficult task faced by most State Highway Agencies (SHAs) due to the difficulty in such areas as selecting pay factor items, modeling the relationship between stochastic variability of pay factor items and pavement performance, and determining an overall lot pay adjustment. This led to the need for an effective way of developing a scientific pay adjustment procedure by incorporating Life Cycle Cost Analysis (LCCA) embedded Monte Carlo approach. In this work, we propose a prototype system to determine a PA specifically using the data in the pavement management information systems at Wisconsin Department of Transportation (WisDOT) as an exemplary to other SHAs. It is believed that the PRS methodology demonstrated in this study can be used in real projects by incorporating the more accurate and reliable performance prediction models and LCC model.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.10
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• pp.1-10
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• 2000

A rigorous modeling of ultra-low energy implantation is becoming increasingly more important as devices shrink to deep submicron dimensions. In this paper, we have developed an efficient three-dimensional Monte Carlo ion implantation model based on a modified Binary Collision Approximation(BCA). To this purpose, the modified electronic stopping model and the multi-body collision model have been taken into account in this simulator. The dopant and damage profiles show very good agreement with SIMS(Secondary Ion Mass Spectroscopy) data and RBS(Rutherford Backscattering Spectroscopy) data, respectively. Moreover, the ion distribution replica method has been implemented into the model to get a computational efficiency in a 3D simulation, and we have calculated the 3D Monte Carlo simulation into the topographically complex structure.

• Journal of the Korean Society of Radiology
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• v.15 no.2
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• pp.191-199
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• 2021

The purpose of this research is to analyze the radiation shielding effect of soft magnetic material to confirm the applicability to the military facilities. The soft magnetic material is known to be effective in shielding EMP. If this material is also effective in radiation shielding, it is expected that it has a lot of applicability in military protection. In particular, this material contains boron, so it will be effective in shielding neutrons. In this research, experiments were conducted using Cs-137 and Co-60 sources to check the gamma ray shielding effect. In addition, the Monte Carlo N-Particle(MCNP) modeling was applied to evaluate the gamma ray and neutron shielding effect of a military command tent. As a result, as the soft magnetic thickness increased, the shielding performance improved according the linear attenuation law of gamma ray and neutron. Therefore, this research verified that the application of soft magnetic material for military purposes in radiation shielding would be effective.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.12
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• pp.31-36
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• 2007

This paper presents a novel statistical characterization for accurate timing analysis in Partially-Depleted Silicon-On-Insulator (PD-SOI) circuits in BSIMSOI3.2 100nm technology. The proposed timing estimate algorithm is implemented in Matlab, Hspice, and C, and it is applied to ISCAS85 benchmarks. The results show that the error is within 5% compared with Monte Carlo simulation results.

• Journal of the Korean Society of Groundwater Environment
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• v.2 no.1
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• pp.9-13
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• 1995

In the stream-aquifer setting, this study evaluated the effects of spatial variability in nonpoint sources and hydraulic conductivity on groundwater outflow concentration history. Monte Carlo experiments based on the advection-dispersion equation were used to determine the statistical moments of groundwater outflow concentration history. The comparison between a spatially distributed model and spatially integrated model (SID) was made in order to examine the possibility of applying SID to the problems of nonpoint source groundwater pollution.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1621-1629
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• 2016

This paper studies Bayesian pooling for analysis of categorical data from small areas. Many surveys consist of categorical data collected on a contingency table in each area. Statistical inference for small areas requires considerable care because the subpopulation sample sizes are usually very small. Typically we use the hierarchical Bayesian model for pooling subpopulation data. However, the customary hierarchical Bayesian models may specify more exchangeability than warranted. We, therefore, investigate the effects of pooling in hierarchical Bayesian modeling for the contingency table from small areas. In specific, this paper focuses on the methods of direct or indirect pooling of categorical data collected on a contingency table in each area through Dirichlet priors. We compare the pooling effects of hierarchical Bayesian models by fitting the simulated data. The analysis is carried out using Markov chain Monte Carlo methods.

• Structural Engineering and Mechanics
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• v.38 no.4
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• pp.503-516
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• 2011

Uncertainty in concrete properties, including concrete modulus of elasticity and modulus of rupture, are predicted by developing a microstructural homogenization model. The homogenization model is developed by analyzing a concrete representative volume element (RVE) using the finite element (FE) method. The concrete RVE considers concrete as a three phase composite material including: cement paste, aggregate and interfacial transition zone (ITZ). The homogenization model allows for considering two sources of variability in concrete, randomly dispersed aggregates in the concrete matrix and uncertain mechanical properties of composite phases of concrete. Using the proposed homogenization technique, the uncertainty in concrete modulus of elasticity and modulus of rupture (described by numerical cumulative probability density function) are determined. Deflection uncertainty of reinforced concrete (RC) beams, propagated from uncertainties in concrete properties, is quantified using Monte Carlo (MC) simulation. Cracked plane frame analysis is used to account for tension stiffening in concrete. Concrete homogenization enables a unique opportunity to bridge the gap between concrete materials and structural modeling, which is necessary for realistic serviceability prediction.