• Nuclear Engineering and Technology
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• v.41 no.3
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• pp.279-286
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• 2009

Improving over a previous study [1], this paper provides a Monte Carlo method for the heat conduction analysis of problems with complicated geometry (such as a pebble with dispersed fuel particles). The method is based on the theoretical results of asymptotic analysis of neutron transport equation. The improved method uses an appropriate boundary layer correction (with extrapolation thickness) and a scaling factor, rendering the problem more diffusive and thus obtaining a heat conduction solution. Monte Carlo results are obtained for the randomly distributed fuel particles of a pebble, providing realistic temperature distributions (showing the kernel and graphite-matrix temperatures distinctly). The volumetric analytic solution commonly used in the literature is shown to predict lower temperatures than those of the Monte Carlo results provided in this paper.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.4
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• pp.479-486
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• 2012

Two of fundamental approaches that can be used to understand ion-solid interaction are Monte Carlo (MC) and Molecular Dynamic (MD) simulations. For the simplicity of simulation Monte Carlo simulation method is widely preferred. In this paper, basic consideration and algorithm of Monte Carlo simulation will be presented as well as simulation results. Sputtering caused by incident ion beam will be discussed with distribution of sputtered particles and their energy distributions. Redeposition of sputtered particles that are experienced refraction at the substrate-vacuum interface additionally presented. In addition, reflection of incident ions with reflection coefficient will be presented together with spatial and energy distributions. This Monte Carlo simulation will be useful in simulating and describing ion beam related processes such as Ion beam induced deposition/etching process, local nano-scale distribution of focused ion beam implanted ions, and ion microscope imaging process etc.

• Structural Engineering and Mechanics
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• v.17 no.2
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• pp.267-279
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• 2004

This paper presents an improved Monte Carlo simulation for the probabilistic determination of initial cable forces of cable-stayed bridges under dead loads using the response surfaces method. A response surface (i.e. a quadratic response surface without cross-terms) is used to approximate structural response. The use of the response surface eliminates the need to perform a deterministic analysis in each simulation loop. In addition, use of the response surface requires fewer simulation loops than conventional Monte Carlo simulation. Thereby, the computation time is saved significantly. The statistics (e.g. mean value, standard deviation) of the structural response are calculated through conventional Monte Carlo simulation method. By using Monte Carlo simulation, it is possible to use the existing deterministic finite element code without modifying it. Probabilistic analysis of a truss demonstrates the proposed method' efficiency and accuracy; probabilistic determination of initial cable forces of a cable-stayed bridge under dead loads verifies the method's applicability.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.4
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• pp.8-14
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• 2008

This paper aims at finding out dominant robot configurations with maximal position errors, which can be attributed to the parameter errors, by using Monte-Carlo simulation for error analysis of a 3-axis SCARA(Selective Compliance Assembly Robot Arm) type robot. In particular, the Monte-Carlo simulation is used for virtually measuring on the position errors, instead of physical measurement. In order to measure the observability of the model parameters with respect to a set of robot configurations, we propose the observability index which is defined as the product of singular values for error propagation matrices. Thus the index can be used for discriminating dominant robot configurations from a set of simulated ones in conjunction with standard deviation of positional errors, This paper analyzed error by robot positional error.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.780-786
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• 2013

In the reliability-based design optimization of electromagnetic devices, the accurate and efficient reliability assessment method is very essential. The first-order sensitivity-assisted Monte Carlo Simulation is proposed in the former research. In order to improve its accuracy for wide application, in this paper, the second-order sensitivity analysis is presented by using the hybrid direct differentiation-adjoint variable method incorporated with the finite element method. By combining the second-order sensitivity with the Monte Carlo Simulation method, the second-order sensitivity-assisted Monte Carlo Simulation algorithm is proposed to implement reliability calculation. Through application to one superconductor magnetic energy storage system, its accuracy is validated by comparing calculation results with other methods.

• Journal of the Korean Society of Safety
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• v.32 no.3
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• pp.54-59
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• 2017

This paper presents an efficient finite analysis model and a simulation-based reliability analysis method for stowage device system failure of a container crane with respect to lateral load. A quasi-static analysis model is introduced to simulate the nonlinear resistance characteristics and failure of tie-down and stowage pin, which are the main structural stowage devices of a crane. As a reliability analysis method, a subset simulation method is applied considering the uncertainties of later load and mechanical characteristic parameters of stowage devices. An efficient Markov chain Monte Carlo (MCMC) method is applied to sample random variables. Analysis result shows that the proposed model is able to estimate the probability of failure of crane system effectively which cannot be calculated practically by crude Monte Carlo simulation method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.39-40
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• 2010

• Electrical & Electronic Materials
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• v.8 no.6
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• pp.685-692
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• 1995

The electron transport coefficients in argon gas is studied over the range of E/N values from 85 to 566 Td by the Monte Carlo method considering the latest cross section data. The result of the Monte Carlo method analysis shows that the value of the electron transport coefficients such as the electron drift velocity, the ratio of the longitudinal and transverse diffusion coefficients to the mobility. It is also found that the electron transport coefficients calculated by the two-term approximation analysis agree well with those by Monte Carlo calculation. The electron energy distributions function were analysed in argon at E/N=283, and 566 Td for a case of the equilibrium region in the mean electron energy. A momentum transfer cross section for the argon atom which was consistent with both of the present electron transport coefficients was derived over the range of mean electron energy from 10.3 to 14.5 eV, also suggested as a set of electron cross section for argon atom. The validity of the results obtained has been confirmed by a Monte Carlo simulation method.

• Journal of Aerospace System Engineering
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• v.7 no.4
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• pp.1-11
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• 2013

In this study, probabilistic reliability analysis was conducted for hybrid rocket performance using Monte-Carlo Simulation. For the accuracy, reliability analysis was performed with experimental data. To simplify the analysis process, the oxidizer was supplied with constant pressure, so that pressure variation with time can be eliminated. And time-space averaged regression rate model was used. The regression rate is obtained with a series of experiments. For reliability analysis of thrust, constant exponent of regression rate is assumed that has probabilistic character. So, the efficiency of characteristic velocity has also probabilistic values. As a results, probability distribution of the thrust is obtained by Monte-Carlo simulation using random samples of the input parameter and validated under the 95% confidence level.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2712-2722
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• 2023

For an accurate and efficient time-dependent Monte Carlo (TDMC) neutron transport analysis, several advanced methods are newly developed and implemented in the Seoul National University Monte Carlo code, McCARD. For an efficient control of the neutron population, a dynamic weight window method is devised to adjust the weight bounds of the implicit capture in the time bin-by-bin TDMC simulations. A moving geometry module is developed to model a continuous insertion or withdrawal of a control rod. Especially, the history-based batch method for the TDMC calculations is developed to predict the unbiased variance of a bin-wise mean estimate. The developed methods are verified for three-dimensional problems in the C5G7-TD benchmark, showing good agreements with results from a deterministic neutron transport analysis code, nTRACER, within the statistical uncertainty bounds. In addition, the TDMC analysis capability implemented in McCARD is demonstrated to search the optimum detector positions for the pulsed-neutron-source experiments in the Kyoto University Critical Assembly and AGN201K.