• Title/Summary/Keyword: Monte-Carlo Simulation Method

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Reliability Analysis of Stowage System of Container Crane using Subset Simulation with Markov Chain Monte Carlo Sampling (마르코프 연쇄 몬테 카를로 샘플링과 부분집합 시뮬레이션을 사용한 컨테이너 크레인 계류 시스템의 신뢰성 해석)

  • Park, Wonsuk;Ok, Seung-Yong
    • 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.

Interference Analysis based on the Monte-Carlo Method (Monte-Carlo 기반의 간섭분석에 관한 연구)

  • Kim, Seong-Kweon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.3 no.2
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    • pp.58-64
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    • 2008
  • In this paper, we proposed the methodology of interference analysis based on monte-carlo method for effective use of Industrial, Scientific, Medical (ISM) band. The interference scenario is divided according to the distance and density. The simulation of interference analysis evaluates the interference probability according to distribution density of Interfering Transmitters (It) in the Secure Interference Area (SIA). The SIA is gained from the Interference Efficiency Range that satisfied to Interference Permissible Range of Victim Receiver (Vr). Simulation result that apply the proposed interference scenario to the WLAN and bluetooth, Interference Permissible Range was 60~400m. And the WLAN was acceptable within interference permissible range to six bluetooth that exist in the SIA. In the same condition, when applied Listen Before Talk (LBT) based on Cognitive Radio (CR) to the bluetooth using Frequency Hopping (FH), interference probability was decreased sharply. The Spectrum Engineering Advanced Monte Carlo Analysis Tool (SEAMCAT) that has been developed based on the monte-carlo method by European Radio-communications Office (ERO) were used to the interference simulation.

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Linearization of Nonlinear Random Vibration Beam by Equivalent Energy Method (비선형 불규칙 진동 보의 등가에너지법에 의한 선형화)

  • Lee, Sin-Young;Cai, G.Q.
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.17 no.1
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    • pp.71-76
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    • 2008
  • Nonlinear dynamic system under random excitation was analyzed by using stochastic method. A linearization method was used in order to linearize non-linear structural characteristics but the parametric excitation was used as it was given. An equivalent energy method which equalizes the expectation value of energy of the original nonlinear system and that of quasi-linearized system was proposed. Ito's differential rule was applied to obtain steady state moments. Quasi-linearization coefficients can be obtained the iterative calculation of linearization scheme and steady state moments. Monte Carlo simulation was used to verify the results of the proposed method. Nonlinear vibration of a slender beam was analyzed in this research. The analysis results were compared with Monte Carlo simulation result and showed good agreement. As the spectral density of the given excitation increased, the analysis results showed the better agreement with Monte Carlo simulation.

Monte Carlo simulation of the estimators for nonlinear regression model (비선형 회귀모형 추정량들의 몬데칼로 시뮬레이션에 의한 비교)

  • 김태수;이영해
    • Proceedings of the Korea Society for Simulation Conference
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    • 2000.11a
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    • pp.6-10
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    • 2000
  • In regression model we estimate the unknown parameters using various methods. There are the least squares method which is the most general, the least absolute deviation, the regression quantile and the asymmetric least squares method. In this paper, we will compare each others with two case: to begin with the theoretical comparison in the asymptotic sense, and then the practical comparison using Monte Carlo simulation for a small sample size.

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A Study on Monte Carlo Simulation in Resin of New Austria Tunnel Method by admixture for Shrinkage Compensating Concrete (무수축 콘크리트 혼화제를 활용한 New Austria Tunnel Method 수지에서 Monte Carlo 시뮬레이션에 관한 연구)

  • Kim, Ki-Jun;Sung, Wan-Mo;Kim, Joo-Han;Jung, Hyung-Hak
    • Journal of the Korean Applied Science and Technology
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    • v.34 no.1
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    • pp.125-131
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    • 2017
  • The influences of scatterer and absorber in turbid material by light scattering in concrete admixture were interpreted for the scattered intensity and wavelength. The molecular properties have been studied by Monte Carlo simulation in resin of New Austria Tunnel Method. It has been found that the effects of optical properties in scattering media could be investigated by the optical parameters(${\mu}_s$, ${\mu}_a$,${\mu}_t$). Monte Carlo Simulation method for modelling of light transport in the civil engineering and construction field was applied. The results using a phantom were discussed that the admixture for shrinkage compensating concrete in NATM-rasin from source to detector is measured, and scattering intensity is stronger with those obtained through Monte Carlo Simulation. It may also aid in designing the best model for coatings and corrosion for the durability of metal constructions.

A Kinetic Monte Carlo Simulation of Individual Site Type of Ethylene and α-Olefins Polymerization

  • Zarand, S.M. Ghafelebashi;Shahsavar, S.;Jozaghkar, M.R.
    • Journal of the Korean Chemical Society
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    • v.62 no.3
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    • pp.191-202
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    • 2018
  • The aim of this work is to study Monte Carlo simulation of ethylene (co)polymerization over Ziegler-Natta catalyst as investigated by Chen et al. The results revealed that the Monte Carlo simulation was similar to sum square error (SSE) model to prediction of stage II and III of polymerization. In the case of activation stage (stage I) both model had slightly deviation from experimental results. The modeling results demonstrated that in homopolymerization, SSE was superior to predict polymerization rate in current stage while for copolymerization, Monte Carlo had preferable prediction. The Monte Carlo simulation approved the SSE results to determine role of each site in total polymerization rate and revealed that homopolymerization rate changed from site to site and order of center was different compared to copolymerization. The polymer yield was reduced by addition of hydrogen amount however there was no specific effect on uptake curve which was predicted by Monte Carlo simulation with good accuracy. In the case of copolymerization it was evolved that monomer chain length and monomer concentration influenced the rate of polymerization as rate of polymerization reduced from 1-hexene to 1-octene and increased when monomer concentration proliferate.

Random Vibration of Non-linear System with Multiple Degrees of Freedom (다자유도 비선형계의 불규칙 진동 해석)

  • Lee, Sin-Young
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.15 no.5
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    • pp.21-28
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    • 2006
  • Vibration of a non-linear system with multiple degrees of freedom under random parametric excitations was evaluated by probabilistic method. The non-linear characteristic terms of system structure were quasi-linearized and excitation terms were remained as they were. An analytical method where the expectation values of square mean of error was minimized was used. The numerical results were compared with those obtained by Monte Carlo simulation. A linear congruential generator and Box-Muller method were used in Monte Carlo simulation. The comparison showed the results by probabilistic method agreed well with those by Monte Carlo simulation.

Reliability Analysis for Structure Design of Automatic Ocean Salt Collector Using Sampling Method of Monte Carlo Simulation

  • Song, Chang Yong
    • 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.

Reliability Evaluation of Transmission System using Monte Carlo Simulation Method (Monte Carlo Simulation기법을 이용한 송전계통의 신뢰도 평가)

  • Moon, Seung-Pil;Kim, Hong-Sik;Choi, Jae-Seok;Cha, Jun-Min
    • Proceedings of the KIEE Conference
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    • 2001.05a
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    • pp.169-171
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    • 2001
  • This paper presents a method fer evaluation nodal probabilistic congestion and reliability indices of transmission systems using Monte Carlo simulation methods. Quantitative evaluation of transmission system reliability is very important because successful operation of an electric power system. In the deregulated electricity market depends on transmission system reliability management Monte Carlo methods are often preferable, when complex operating conditions are involved and/or the number of sever events is relatively large. To evaluate the reliability of a real power system, Monte Carlo Methods will be more useful. The characteristics and effectiveness of this methodology are illustrated by the case study using a small test system.

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Tolerance Allocation Method for IR Optics Fabrication Using Monte-Carlo Simulation Based on Measured Reflective Eccentricity (편심측정 결과가 반영된 몬테카를로 시뮬레이션을 이용한 적외선 광학계 조립정렬 공차 할당 기법)

  • Yoo, Jae-Eun
    • Korean Journal of Optics and Photonics
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    • v.22 no.4
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    • pp.161-169
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    • 2011
  • In this paper, a tolerance allocation method using Monte-Carlo simulation with measured reflective eccentricity for high-sensitive IR optics is proposed. During optics fabrication and alignment, reflective eccentricity was measured using an optical centration measurement instrument. A Monte-Carlo simulation was performed using measured eccentricity data, and it gives statistical estimated performance of the optics after fabrication. The validity of the proposed tolerance allocation method was verified comparing the estimated MTF result with the measured MTF result of the fabricated optics.