• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.6
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• pp.1341-1345
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• 2005

Sequential Monte Carlo techniques are a set of powerful and versatile simulation-based methods to perform optimal state estimation in nonlinear non-Gaussian state-space models. We can use Monte Carlo particle filters adaptively, i.e. so that they simultaneously estimate the parameters and the signal. However, Sequential Monte Carlo techniques require the use of special panicle filtering techniques which suffer from several drawbacks. We consider here an alternative approach combining particle filtering and Sequential Hybrid Monte Carlo. We give some examples of applications in fisheries(luespotted mud hopper data).

• 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.

• 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.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.193-196
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• 1987

We reported that hot electron phenomena in submicron nMOSFET by Monte Carlo method. In order to predict the influence of the hot electron effects on the device reliability, either simple analytical model or a complete two dimensional numerical simulation has been adopted. Results of numerical simulation, based on the static mobility model, may be inaccurate when gate length of MOSFET is scaled down to less than 1um. Most of device simulation packages utilize the static nobility model. Monte Carlo method based on stochastic analysis of carrier movement may be a powerful tool to characterize hot electrons. In this work, energy and velocity distribution of carriers were obtained to predict the relative degree of short channel effects for different device parameters. Our analysis shows a few interesting results when $V_{ds}$ is 5 volt, average electron energy does not increase with gate bias as evidenced by substrate current.

• Journal of Information Technology Services
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• v.9 no.4
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• pp.123-133
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• 2010

There are many occasions on which the critical decisions should be made in software projects. Those decisions are basically related to estimating and predicting project parameters such as costs, efforts, and duration. The project managers are looking for methods to make better decisions. The decisions about project parameters are recommended to be performed based on historical data of Similar projects. The measures of the tasks in past projects may have different shapes of distributions. we need to add those measures to get a predicted project measures. To add measures with different shapes of distribution, we need to use Monte Carlo Simulation. In this paper, we suggest applying Monte Carlo Simulation for supporting decision makings in software project. We implemented best-fit case and scheduling estimations with Cristal Ball, a commercial product of Monte Carlo simulation and showed how the suggested approach supports those critical decision makings.

• Tunnel and Underground Space
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• v.14 no.2
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• pp.97-107
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• 2004

Various kinds of rock mass properties, which can be obtained from laboratory tests as well as field tests, can be reasonably applied to the design of earth structures. An extrapolation technique can be used for this application and it generally guarantee its quality from a sufficient amount of test results because it is based on the RMR value in most cases. When the confident RMR can not be obtained because of the insufficient testing results, the Monte Carlo Simulation technique can be introduced fer deducing the proper RMR and this assessed RMR can be reused fur the major input parameters. Authors' proposed method can be verified from the comparison between the results of numerical analysis and the evidences of field site.

• Journal of Ocean Engineering and Technology
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• v.34 no.5
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• pp.316-324
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• 2020

This paper presents comparative studies of reliability analysis and meta-modeling using the sampling method of Monte Carlo simulation for the structure design of an automatic ocean salt collector (AOSC). The thickness sizing variables of structure members are considered as random variables. Probabilistic performance functions are selected from strength performances evaluated via the finite element analysis of an AOSC. The sampling methods used in the comparative studies are simple random sampling and Sobol sequences with varied numbers of sampling. Approximation methods such as the Kriging model is applied to the meta-model generation. Reliability performances such as the probability failure and distribution are compared based on the variation of the sampling method of Monte Carlo simulation. The meta-modeling accuracy is evaluated for the Kriging model generated from the Monte Carlo simulation and Sobol sequence results. It is discovered that the Sobol sequence method is applicable to not only to the reliability analysis for the structural design of marine equipment such as the AOSC, but also to Kriging meta-modeling owing to its high numerical efficiency.

• Journal of the Korean Ceramic Society
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• v.53 no.3
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• pp.288-294
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• 2016

The densification process during liquid-phase sintering was simulated by Monte Carlo simulation. The Potts model, which had been applied to coarsening during liquid-phase sintering, was modified to include vapor particles. The results of two- and threedimensional simulations showed a temporal decrease in porosity, in other words, densification, and an increase in the average size of pores. The results also showed growth of solid grains and the effect of wetting angle on microstructure.

• Proceedings of the Korea Concrete Institute Conference
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• 1998.04b
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• pp.447-454
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• 1998

The main object of the study is that axial force-moment relationships for high strength concrete structures using reliability theory(Linear statstical method, Monte Carlo Simulation) including probability conception. And mean stress factors and centroid factors proposed to high strength concrete structures using reliability theory(Linear statstical method, Monte Carlo Simulation). Finally, The established experimental data for axial force-moment relationships are compared to the analytical data(data for Linear statstical method and Monte Carlo Simulation) for axial force-moment relationships in this analytical method.

• Journal of the Korean Ceramic Society
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• v.23 no.5
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• pp.47-54
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• 1986

The structures of crystalline vitreous and liquid $SiO_2$ were Monte carlo simulated employing the potential energy function comprising Lennard-Jones 2-body and Axilrod-Teller 3-body potentials. Although the Si-O-Si angular distribution functions obtained in the simulation appear to be higher than the experimental results the other simulation results including SiO, O-O and Si-Si radial distribution functions and O-Si-O anglular distribution functions agree well with experimental data within acceptable limits. Themost important outcome in this study is that various $SiO_2$forms were successfully reproduced with the same potential energy function.