• 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.

• 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.

• Asia-Pacific Journal of Business
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• v.14 no.1
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• pp.149-169
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• 2023

Purpose - The main purpose of this study is to develop the stress test model for Korean banks by exploring the optimal Monte Carlo simulation and BIS forecasting model. Design/methodology/approach - This study selects 15 Korean banks as sample financial firms and collects relevant 76 quarterly data for the period between year 2000 and 2018 from KRX(Korea Excange), Bank of Korea, and FnGuide. The Regression analysis, Unit-root test, and Monte Carlo simulation are hired to analyze the data. Findings - First, most of the sample banks failed to keep 8% BIS ratio for the adverse and severely Adverse Scenarios, implying that Korean banks must make every effort to realize better BIS ratios under adverse market conditions. Second, we suggest the better Monte Carlo simulation model for the Korean banks by finding that the more appropriate volatility should be different depending on variables rather than simple two-sigma which has been used in the previous studies. Third, we find that the stepwise regression model is better fitted than simple regression model in forecasting macro-economic variables for the BIS variables. Fourth, we find that, for the more robust and significant statistical results in designing stress tests, Korean banks are required to construct more valid time-series and cross-sectional data-base. Research implications or Originality - The above results all together show that the optimal volatility in designing optimal Monte Carlo simulation varies depending on the country, and many Korean banks fail to pass sress test under the adverse and severely adverse scenarios, implying that Korean banks need to make improvement in the BIS ratio.

• Safety and Health at Work
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• v.15 no.1
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• pp.33-41
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• 2024

Background: Dust generated during the processing of building materials enterprises can pose a serious health risk. The study aimed to compare and analyze the results of ART and the Monte Carlo model for the dust exposure assessment in building materials enterprises, to derive the application scope of the two models. Methods: First, ART and the Monte Carlo model were used to assess the exposure to dust in each of the 15 building materials enterprises. Then, a comparative analysis of the exposure assessment results was conducted. Finally, the model factors were analyzed using correlation analysis and the scope of application of the models was determined. Results: The results show that ART is mainly influenced by four factors, namely, localized controls, segregation, dispersion, surface contamination, and fugitive emissions, and applies to scenarios where the workplace information of the building materials enterprises is specific and the average dust concentration is greater than or equal to 1.5 mg/m³. The Monte Carlo model is mainly influenced by the dust concentration in the workplace of building materials enterprises and is suitable for scenarios where the dust concentration in the workplace of the building materials enterprises is relatively uniform and the average dust concentration is less than or equal to 6mg/m³. Conclusion: ART is most accurate when workplace information is specific and average dust concentration is > 1.5 mg/m³; whereas, The Monte Carlo model is the best when dust concentration is homogeneous and average dust concentration is < 6 mg/m³.

• 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 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 the Korean Institute of Electrical and Electronic Material Engineers
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• v.11 no.7
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• pp.571-580
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• 1998

The numerical model that can describe the ignition of pseudospark discharge using hybrid fluid-particle(Monte Carlo )method has been developed. This model consists of the fluid expression for transport of electrons and ions and Poisson's equation in the electric field. The fluid equation determines the spatiotemporal dependence of charged particle densities and the ionization source term is computed using the Monte carlo method. This model has been used to study the evolution of a discharge in Argon at 0.5 torr, with an applied voltage if 1kV. The evolution process of the discharge has been divided into four phases along the potential distribution : (1) Townsend discharge, (2) plasma formation, (3) onset of hollow cathode effect, (4) plasma expansion. From the numerical results, the physical mechanisms that lead to the rapid rise in current associated with the onset of pseudospark could be identified.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.1 s.104
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• pp.39-44
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• 2006

This paper proposes a method of moments(MoM)/Monte-Carlo simulation and Physical Optics(PO) model to determine Bistatic Coherent Reflectivity of sea surfaces at various wind speeds. For the MoM simulation, a Gaussian random rough sea surface was generated based on the data of Tae-An ocean at various wind speeds and sea surface heights. The numerical results of the MoM/Monte Carlo simulations were used to verify the validity region of the PO model. It was found that the numerical result for a flat surface agrees quite well with the Fresnel reflection coefficient. The validity of the PO model on the rough sea surface is shown by using ray tracing method.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.113.2-113.2
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• 2005

• Journal of the Korea Society for Simulation
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• v.9 no.3
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• pp.43-51
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• 2000

In regression model, we estimate the unknown parameters by using various methods. There are the least squares method which is the most general, the least absolute deviation method, the regression quantile method and the asymmetric least squares method. In this paper, we will compare each others with two cases: firstly the theoretical comparison in the asymptotic sense and then the practical comparison using Monte Carlo simulation for a small sample size.