• Title/Summary/Keyword: Monte-Carlo simulation method

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기체 유량 측정에서 몬테 카를로 모사를 이용한 측정불확도 평가 (Uncertainty Assessment Using Monte Carlo Simulation in Gas Flow Measurement)

  • 이대성;양인영;김춘택;양수석
    • 대한기계학회논문집B
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    • 제27권12호
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    • pp.1758-1765
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    • 2003
  • Monte Carlo simulation(MC) method was used as an uncertainty assessment tool for gas flow measurement in this paper. Uncertainty sources for gas flow measurement were analyzed, and probability distribution characteristics of each source were discussed. Detailed MC methodology was described including the effect of the number of simulation. The uncertainty result was compared with that of the conventional sensitivity coefficient method, and it was revealed that the results were different from each other for this particular gas flow measurement case of which the modelling equation was nonlinear. The MC was comparatively simple, convenient and accurate as an uncertainty assessment method, especially in cases of complex, nonlinear measurement modelling equations. It was noted that the uncertainty assessment method should be selected carefully according to the mathematical characteristics of the measurement.

A Stochastic Linear Scheduling Method using Monte Carlo Simulation

  • Soderlund, Chase;Park, Borinara
    • 국제학술발표논문집
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    • The 6th International Conference on Construction Engineering and Project Management
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    • pp.169-173
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    • 2015
  • The linear scheduling method or line-of-balance (LOB) is a popular choice for projects that involve repetitive tasks during project execution. The method, however, produces deterministic schedule that does not convey a range of potential project outcomes under uncertainty. This results from the fact the basic scheduling parameters such as crew production rates are estimated to be deterministic based on single-point value inputs. The current linear scheduling technique, therefore, lacks the capability of reflecting the fluctuating nature of the project operation. In this paper the authors address the issue of how the variability of operation and production rates affects schedule outcomes and show a more realistic description of what might be a realistic picture of typical projects. The authors provide a solution by providing a more effective and comprehensive way of incorporating the crew performance variability using a Monte Carlo simulation technique. The simulation outcomes are discussed in terms of how this stochastic approach can overcome the shortcomings of the conventional linear scheduling technique and provide optimum schedule solutions.

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A Novel Simulation Architecture of Configurational-Bias Gibbs Ensemble Monte Carlo for the Conformation of Polyelectrolytes Partitioned in Confined Spaces

  • Chun, Myung-Suk
    • Macromolecular Research
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    • 제11권5호
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    • pp.393-397
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    • 2003
  • By applying a configurational-bias Gibbs ensemble Monte Carlo algorithm, priority simulation results regarding the conformation of non-dilute polyelectrolytes in solvents are obtained. Solutions of freely-jointed chains are considered, and a new method termed strandwise configurational-bias sampling is developed so as to effectively overcome a difficulty on the transfer of polymer chains. The structure factors of polyelectrolytes in the bulk as well as in the confined space are estimated with variations of the polymer charge density.

Application of Monte Carlo Simulation to Intercalation Electrochemistry II. Kinetic Approach to Lithium Intercalation into LiMn2O4 Electrode

  • Kim, Sung-Woo;Pyun, Su-Il
    • 전기화학회지
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    • 제5권2호
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    • pp.86-92
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    • 2002
  • 속도론적 관점에서 키네틱 몬테 카를로 방법의 전기화학적 리튬 인터칼레이션에로의 응용에 대하여 다루었다. 우선 키네틱 몬테 카를로 방법과 전이상태이론의 기본 개념을 소개하였고, 확산거동을 평가하기 위한 시뮬레이션 과정을 설명하였다. 마지막으로 인터칼레이션 화합물중 $LiMn_2O_4$전극에 대해 전류 추이곡선과 선형 포텐셜 전류곡선을 해석하기 위해서 전이상태이론에 근거한 키네틱 몬테 카를로 방법을 셀-저항 제어조건하에서 사용하였다. 이로부터 키네틱 몬테 카를로 방법이 전기화학분야에서 리튬 인터칼레이션의 속도론적 연구에 매우 유용함을 알 수 있었다.

불규칙 매개변수 가진을 받는 비선형계의 확률론적 진동평가 (Vibration of Non-linear System under Random Parametric Excitations by Probabilistic Method)

  • 이신영
    • 한국정밀공학회지
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    • 제23권12호
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    • pp.72-79
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    • 2006
  • Vibration of a non-linear system under random parametric excitations was evaluated by probabilistic methods. The non-linear characteristic terms of a system structure were quasi-linearized and excitation terms were remained as they were An analytical method where the square mean of error was minimized was used An alternative method was an energy method where the damping energy and restoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.

확률론 방법에 의한 불규칙 진동 비선형 계의 준선형화 (Quasi-linearization of non-linear systems under random vibration by probablistic method)

  • 이신영
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2008년도 추계학술대회A
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    • pp.785-790
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    • 2008
  • Vibration of a non-linear system under random parametric excitations was evaluated by probablistic methods. The non-linear characteristic terms of a system were quasi-linearized and excitation terms were remained as they were given. An analytical method where the square mean of error was minimized was ysed. An alternative method was an energy method where the damping energy and rstoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.

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불규칙 가진을 받는 비선형계의 확률론적 진동평가 (Vibration Evaluation of Non-linear System under Random Excitations by Probabilistic Method)

  • 이신영
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2006년도 춘계학술대회 논문집
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    • pp.113-114
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    • 2006
  • Vibration of a non-linear system under random excitations was evaluated by probabilistic methods. The non-linear characteristic terms of a system structure were quasi-linearized and excitation terms were remained as they were. An analytical method where the square mean of error was minimized was used. An alternative method was an energy method where the damping energy and restoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.

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Implementation of functional expansion tally method and order selection strategy in Monte Carlo code RMC

  • Wang, Zhenyu;Liu, Shichang;She, Ding;Su, Yang;Chen, Yixue
    • Nuclear Engineering and Technology
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    • 제53권2호
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    • pp.430-438
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    • 2021
  • The spatial distribution of neutron flux or reaction rate was calculated by cell or mesh tally in traditional Monte Carlo simulation. However, either cell or mesh tally leads to the increase of memory consumption and simulation time. In this paper, the function expansion tally (FET) method was developed in Reactor Monte Carlo code RMC to solve this problem. The FET method was applied to the tallies of neutron flux distributions of uranium block and PWR fuel rod models. Legendre polynomials were used in the axial direction, while Zernike polynomials were used in the radial direction. The results of flux, calculation time and memory consumption of different expansion orders were investigated, and compared with the mesh tally. Results showed that the continuous distribution of flux can be obtained by FET method. The flux distributions were consistent with that of mesh tally, while the memory consumption and simulation time can be effectively reduced. Finally, the convergence analysis of coefficients of polynomials were performed, and the selection strategy of FET order was proposed based on the statistics uncertainty of the coefficients. The proposed method can help to determine the order of FET, which was meaningful for the efficiency and accuracy of FET method.

시뮬레이션에 의한 CH4 기체의 전리 및 확산계수 (Ionization and Diffusion Coefficients in CH4 Gas by Simulation)

  • 김상남
    • 전기학회논문지P
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    • 제63권4호
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    • pp.317-321
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    • 2014
  • This paper describes the information for quantitative simulation of weakly ionized plasma. We must grasp the meaning of the plasma state condition to utilize engineering application and to understand materials of plasma state. Using quantitative simulations of weakly ionized plasma, we can analyze gas characteristic. In this paper, the electron Ionization and diffusion Coefficients in $CH_4$ has been analysed over the E/N range 0.1~300[Td], at the 300[$^{\circ}K$] by the two term approximation Boltzmann equation method and Monte Carlo Simulation. Boltzmann equation method has also been used to predict swarm parameter using the same cross sections as input. The behavior of electron has been calculated to give swarm parameter for the electron energy distribution function has been analysed in $CH_4$ at E/N=10, 100 for a case of the equilibrium region in the mean energy. A set of electron collision cross section has been assembled and used in Monte Carlo simulation to predict values of swarm parameters. The result of Boltzmann equation and Monte Carlo Simulation has been compared with experimental data by Ohmori, Lucas and Carter. The swarm parameter from the swarm study are expected to sever as a critical test of current theories of low energy scattering by atoms and molecules.

Monte Carlo Simulation을 이용한 각 부하지점별 확률론적 발전비산정 (Nodal Probabilistic Production Cost Evaluation using Monte Carlo Simulation Methods)

  • 문승필;김홍식;최재석
    • 대한전기학회논문지:전력기술부문A
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    • 제51권9호
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    • pp.425-432
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    • 2002
  • This Paper illustrates a method for evaluating nodal probabilistic production cost using the CMELDC. A new method for constructing CMELDC(CoMposite Power System Equivalent Load Duration Curve) has been developed by authors. The CMELDC can be obtained by convolution integral processing between the probability distribution functions of the fictitious generators outage capacity and the load duration curves at each load point. In general, if complex operating conditions are involved and/or the number of severe events is relatively large, Monte Carlo methods are more efficient. Because of that reason, Monte Carlo Methods are applied for the construction of CMELDC in this study. And IEEE-RTS 24 buses model is used as our case study with satisfactory results.