• Water for future
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• v.18 no.4
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• pp.335-345
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• 1985

The purpose of stochastic models for synthetic generation of river flows based on the short-term observed data is to provide abundant input data to the water resources systems of which the system performance and operation policy are to be determined beforehand. Among many of such models the Monte Carlo Method of synthetic generation, which is usually known to be appropriate for annual data generation, is employed to check if it can be applied for the generation of monthly flows. For the purpose of comparisons the statistical parameters of the generated monthly flows by Monte Carlo model based on the appropriate probability distribution for each month were compared with those of the generated flows by Thoms-Fiering multiseason model and with those of the observed monthly flows. On the other hand, the statistical parameters of the annual river flows obtained by adding the generated monthly flows year by year based on the Monte Carlo and Thomas-Fiering models were compared with those of the annual flows generated directly by annual Monte Carlo model with reference to those for the observed annual river flows. Based on the above comparative studies, the discussions are made and conclusions derived.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.3
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• pp.127-133
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• 2009

In this study, dimensionless-cumulative rainfall curves were generated by multivariate Monte Carlo method. For generation of rainfall curve rainfall storms were divided and made into dimensionless type since it was required to remove the spatial and temporal variances as well as differences in rainfall data. The dimensionless rainfall curves were divided into 4 types, and log-ratio method was introduced to overcome the limitations that elements of dimensionless-cumulative rainfall curve should always be more than zero and the sum total should be one. Orthogonal transformation by Johnson system and the constrained non-normal multivariate Monte Carlo simulation were introduced to analyse the rainfall characteristics. The generative technique in stochastic rainfall variation using multivariate Monte Carlo method will contribute to the design and evaluation of hydrosystems and can use the establishment of the flood disaster prevention system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.12
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• pp.536-543
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• 2006

This paper uses Monte Carlo technique, which is one of probabilistic methods of estimating the economical quantity of electric power generation in consideration of voltage stability in the aspect of power generation companies. In the power exchange system in Korea, when power generation companies participate in tenders for power generation capacity at the power exchange, they need to determine their power supply capacity considering the stability of electric power system. Thus, we purposed to propose an algorithm for estimating economical power generation capacity in theaspect of power generation companies, through which we can estimate the margin for voltage stability through P-V curve analysis by capacity according to the change of power generation capacity in a simulated system and to conduct Monte Carlo simulation in consideration of the margin

• Journal of the Optical Society of Korea
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• v.13 no.2
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• pp.267-271
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• 2009

The aim of this study is to evaluate wavelength dependence for laser-assisted lipolysis using a mathematical simulation. In this study, a Monte Carlo simulation was performed to simulate light transport in fat and dermal tissue with 3 different laser wavelengths (${\lambda}\;=\;1064\;nm$, 1320 nm, and 1444 nm) that are currently used in clinic settings for laser-assisted lipolysis. The relative rates of heat generation versus penetration depth showed that the greatest amount of heat generation was seen in the tissues at ${\lambda}\;=\;1444\;nm$. This Monte Carlo simulation may help lend insight into the thermal events occurring inside the fat and dermal tissue during laser-assisted lipolysis.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.5
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• pp.554-562
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• 2012

Processing of Scanning electron microscope imaging has been analyzed in both secondary electron (SE) imaging and backscattered electron (BSE) image. Because of unique characteristics of both secondary electron and backscattered electron image, mechanism of imaging process and image quality are quite different each other. For the sake of characterize imaging process, Monte Carlo simulation code have been developed. It simulates electron penetration and depth profile in certain material. In addition, secondary electron and backscattered electron generation process as well as their spatial distribution and energy characteristics can be simulated. Geometries that has fundamental feature have been imaged using the developed Monte Carlo code. Two, SE and BSE images generation process will be discussed. BSE imaging process can be readily used to discriminate in both material and geometry by simply changing position and direction of BSE detector. The developed MC code could be useful to design BSE detector and their position. Furthermore, surface reconstruction technique is possibly developed at the further research efforts. Basics of Monte Carlo simulation method will be discussed as well as characteristics of SE and BSE images.

• Nuclear Engineering and Technology
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• v.44 no.2
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• pp.161-176
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• 2012

McCARD is a Monte Carlo (MC) neutron-photon transport simulation code. It has been developed exclusively for the neutronics design of nuclear reactors and fuel systems. It is capable of performing the whole-core neutronics calculations, the reactor fuel burnup analysis, the few group diffusion theory constant generation, sensitivity and uncertainty (S/U) analysis, and uncertainty propagation analysis. It has some special features such as the anterior convergence diagnostics, real variance estimation, neutronics analysis with temperature feedback, $B_1$ theory-augmented few group constants generation, kinetics parameter generation and MC S/U analysis based on the use of adjoint flux. This paper describes the theoretical basis of these features and validation calculations for both neutronics benchmark problems and commercial PWR reactors in operation.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.811-816
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• 2022

This work presents the methodology used to expand the capabilities of the Monte Carlo code OpenMC for the calculation of reactor kinetic parameters: effective delayed neutron fraction β_eff and neutron generation time L. The modified code, OpenMC(Time-Dependent) or OpenMC(TD), was then used to calculate the effective delayed neutron fraction by using the prompt method, while the neutron generation time was estimated using the pulsed method, fitting Λ to the decay of the neutron population. OpenMC(TD) is intended to serve as an alternative for the estimation of kinetic parameters when licensed codes are not available. The results obtained are compared to experimental data and MCNP calculated values for 18 benchmark configurations.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3450-3463
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• 2023

In the two-step analysis of Pebble-Bed type High-Temperature Gas-Cooled Reactor (PB-HTGR), the lattice physics calculation for the generation of homogenized cross-sections is based on the fuel pebble. However, the randomly-dispersed fuel particles in the fuel pebble introduce double heterogeneity and randomness. Compared to the deterministic method, the Monte Carlo method which is flexible in geometry modeling provides a high-fidelity treatment. Therefore, the Monte Carlo code NECP-MCX is extended in this study to perform the lattice physics calculation of the PB-HTGR. Firstly, the capability for the simulation of randomly-dispersed media, using the explicit modeling approach, is developed in NECP-MCX. Secondly, the capability for the generation of the homogenized cross-section is also developed in NECP-MCX. Finally, simplified PB-HTGR problems are calculated by a two-step neutronics analysis tool based on Monte Carlo homogenization. For the pebble beds mixed by fuel pebble and graphite pebble, the bias is less than 100 pcm when compared to the high-fidelity model, and the bias is increased to 269 pcm for pebble bed mixed by depleted fuel pebble. Numerical results show that the Monte Carlo lattice physics calculation for the two-step analysis of PB-HTGR is feasible.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.6 no.3
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• pp.63-74
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• 1986

A methodology for the probabilistic determination of active storage capacity of an impounding reservoir is proposed with due considerations to the durations and return periods of the low flow series at the reservoir site. For more reliable probabilistic analysis the best-fit stochastic generation model of Monte Carlo type was first selected for the generation of monthly flow series, the models tested being the Month Carlo Model based on the month-by-month flow series (Monte Carlo-A Type), Monte Carlo Model based on the standardized sequential monthly flow series (Monte Carlo-B Type), and the Thomas-Fiering Model. Monte Carlo-B Model was final1y selected and synthetic monthly flows of 200 years at Hong Cheon dam site were generated. With so generated 200 years' monthly flows partial duration series of low flows were developed for various durations. Each low flow series was further processed by a nonsequential mass analysis for specified draft rates. This mass analysis furnished the storage-draft-recurrence interval relationship which gives the reservoir storage requirement for a specified water demand from the reservoir during a drought of given return period. Illustrations are given on the application of these results in analyzing the water supply capacity of a particlar reservoir, existing or proposed.

• Communications for Statistical Applications and Methods
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• v.18 no.5
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• pp.595-601
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• 2011

A community of the social network refers to the subset of nodes linked more densely among them than to others. In this study, we propose a Monte-Carlo method for generating random social unipartite and bipartite networks with two or more communities. Proposed random networks can be used to verify the small world phenomenon of the social networks with several communities.