• 제목/요약/키워드: Monte carlo method

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혼성 유체-입자(몬테칼로)법을 이용한 유사스파크 방전의 기동 특성 해석 (Analysis on the lgnition Charac teristics of Pseudospark Discharge Using Hybrid Fluid-Particle(Monte Carlo) Method)

  • 심재학;주홍진;강형부
    • 한국전기전자재료학회논문지
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    • 제11권7호
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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.

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바다 표면의 Bistatic Coherent Reflectivity 계산을 위한 Monte-Carlo/모멘트 법과 PO 모델 비교 (Comparison of Moment Method/Monte-Carlo Simulation and PO for Bistatic Coherent Reflectivity of Sea Surfaces)

  • 김상근;오이석
    • 한국전자파학회논문지
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    • 제17권1호
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    • pp.39-44
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    • 2006
  • 본 논문에서는 바다 표면에서 전파의 페이딩 현상을 해석하는데 필요한 bistatic coherent reflectivity를 Monte-Carlo/모멘트 법과 physical optics(PO) 모델을 이용하여 비교하고 계산하였다. 모멘트 법 계산을 위해서 우선 Gaussian 형태로 불규칙한 바다 표면을 생성하였다. 풍속과 유의 파고 등에 대한 태안 앞바다에서의 실제 측정 데이터를 사용하여 이 표면을 생성하였으며, 두 변수간의 관계식을 유도함으로써 측정하기 쉬운 변수인 풍속에 의해 바다 표면 상태를 예측할 수 있는 모델을 만들었다. 평면에서의 결과를 비교함으로써 모멘트 법 모델을 검증하였고, 거친 표면의 경우에 비교적 정확한 수치 해석 방법인 Monte-Carlo/모멘트 법과 간단히 계산이 가능한 이론식인 PO 모델을 비교함으로써 거친 표면에서 PO 모델의 적용 가능한 조건을 찾아내었으며, 전파 경로 해석법을 이용하여 실제 전파의 페이딩 현상을 해석할 때에 사용되는 PO 모델의 유효성을 검증하였다.

Fuzzy Monte Carlo simulation을 이용한 물리 사면 모델 기반의 상주지역 산사태 취약성 분석 (Physically Based Landslide Susceptibility Analysis Using a Fuzzy Monte Carlo Simulation in Sangju Area, Gyeongsangbuk-Do)

  • 장정윤;박혁진
    • 자원환경지질
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    • 제50권3호
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    • pp.239-250
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    • 2017
  • 정량적인 산사태 취약성 분석 중 물리 모델 기반의 분석(physically based approach)은 산사태의 발생 메커니즘 과정을 고려할 수 있는 장점으로 인해 다양한 취약성 분석기법 중 가장 효과적인 기법으로 알려져 있다. 물리 모델 분석은 사면의 지형학적 및 지질공학적 특성과 관련된 입력 자료들을 활용하는데, 현장으로부터 지질공학적 특성을 획득하는 과정에서 지반의 공간적 변동성과 복잡한 지질조건으로 인해 불확실성이 발생하며 이는 부정확한 결과를 초래한다. 따라서 이러한 불확실성을 정량화하기 위하여 확률론적 기법이 활용되어 왔다. 그러나 확률론적 분석을 수행하기 위해 필요한 입력변수의 확률특성은 현장 조사나 실험에서의 수량 제약으로 인하여 정확하게 파악하기 힘들다는 문제가 발생한다. 따라서 본 연구에서는 이러한 원인으로 인해 발생하는 불확실성을 다루기 위하여 퍼지집합이론(fuzzy set theory)을 활용하였다. 특히, 본 연구에서는 퍼지집합이론과 몬테카를로기법(Monte Carlo simulation)을 결합한 분석기법을 제안하였고 이를 실제 산사태가 발생한 연구지역에 적용하여 적정성을 파악하였다. 이를 위하여 1998년 8월 대규모의 산사태가 발생한 경상북도 상주시 일대를 연구지역으로 선정하고 산사태 취약성 분석을 수행하였다. 또한 퍼지몬테카를로기법(Fuzzy Monte Carlo simulation)의 예측 정확도 비교를 위해, 기존의 확률론적 기법인 몬테카를로기법(Monte Carlo simulation)과 안전율 수행 결과와 비교분석 하였다. 그 결과 퍼지몬테카를로기법(Fuzzy Monte Carlo simulation)이 다른 기법에 비해 가장 좋은 예측의 정확도를 보였다.

Monte Carlo법에 의한 복합전력계통의 유효부하지속곡선 작성법 및 개발 및 신뢰도 해석 (Development of the ELDC and Reliability Analysis of Composite Power System by Monte Carlo Method)

  • 문승필;최재석;신흥교;이순영;송길영
    • 대한전기학회논문지:전력기술부문A
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    • 제48권5호
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    • pp.508-516
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    • 1999
  • This paper presents a method for constructing composite power system effective load duration curves(CMELDC) at load points by Monte Carlo method. The concept of effective load duration curves(ELDC) in power system planning is useful and important in both HLII. CMELDC can be obtained from convolution integral processing of the probability function of unsupplied power and the load duration curve at each load point. This concept is analogy to the ELEC in HLI. And, the reliability indices (LOLP, EDNS) for composite power system are evaluated using CMELDC. Differences in reliability levels between HLI and HLII come from considering with the uncertainty associated with the outages of the transmission system. It is expected that the CMELDC can be applied usefully to areas such as reliability evaluation, probabilistic production cost simulation and analytical outage cost assessment, etc. in HLII, DC load flow and Monte Carlo method are used for this study. The characteristics and effectiveness of thes methodology are illustrated by a case study of the IEEE RTS.

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

  • Song, Chang Yong
    • 한국해양공학회지
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    • 제34권5호
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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.

Monte Carlo Method을 이용한 GaAs 전자전송특성의 온도의존성에 관한 연구 (A Study on Temperature Dependence of the Electron Transport Properties of Gallium Arsenide using a Monte Carlo Method)

  • 윤진섭;하성철
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 1988년도 춘계학술대회 논문집
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    • pp.56-59
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    • 1988
  • Electron transport properties of gallium arsenide in an electric field are simulated the drift velocity, Mn.energy, electron occupation, mobility in the temperature range $77^{\circ}K-500^{\circ}K$ using a Monte Carlo Method. Therefore it can be used for a GaAs MESFET design.

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Monte Carlo Resonance Treatment for the Deterministic Transport Lattice Codes

  • Kim Kang-Seog;Lee Chung Chan;Chang Moon Hee;Zee Sung Quun
    • Nuclear Engineering and Technology
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    • 제35권6호
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    • pp.581-595
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    • 2003
  • Transport lattice codes require the resonance integral tables for the resonant nuclides where the resonance integral is a function of the background cross section and can be prepared through a special program solving the slowing down equation. In case the cross section libraries do not include the resonance integral table for the resonant nuclides, the computational prediction produces a large error. We devised a new method using a Monte Carlo calculation for the effective resonance cross sections to solve this problem provisionally. We extended this method to obtain the resonance integral table for general purpose. The MCNP code is used for the effective resonance integrals and the LIBERTE code for the effective background cross sections. We modified the HELIOS library with the effective cross sections and the resonance integral tables obtained by the newly developed Monte Carlo method, and performed sample calculations using HELIOS and LIBERTE. The results showed that this method is very effective for the resonance treatment.

A PRICING METHOD OF HYBRID DLS WITH GPGPU

  • YOON, YEOCHANG;KIM, YONSIK;BAE, HYEONG-OHK
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제20권4호
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    • pp.277-293
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    • 2016
  • We develop an efficient numerical method for pricing the Derivative Linked Securities (DLS). The payoff structure of the hybrid DLS consists with a standard 2-Star step-down type ELS and the range accrual product which depends on the number of days in the coupon period that the index stay within the pre-determined range. We assume that the 2-dimensional Geometric Brownian Motion (GBM) as the model of two equities and a no-arbitrage interest model (One-factor Hull and White interest rate model) as a model for the interest rate. In this study, we employ the Monte Carlo simulation method with the Compute Unified Device Architecture (CUDA) parallel computing as the General Purpose computing on Graphic Processing Unit (GPGPU) technology for fast and efficient numerical valuation of DLS. Comparing the Monte Carlo method with single CPU computation or MPI implementation, the result of Monte Carlo simulation with CUDA parallel computing produces higher performance.

사전확률분포와 Marcov Chain Monte Carlo법을 이용한 최적보전정책 연구 (Optimal Maintenance Policy Using Non-Informative Prior Distribution and Marcov Chain Monte Carlo Method)

  • 하정랑;박민재
    • 한국신뢰성학회지:신뢰성응용연구
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    • 제17권3호
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    • pp.188-196
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    • 2017
  • Purpose: The purpose of this research is to determine optimal replacement age using non-informative prior information and Bayesian method. Methods: We propose a novel approach using Bayesian method to determine the optimal replacement age in block replacement policy by defining the prior probability with data on failure time and repair time. The Marcov Chain Monte Carlo simulation is used to investigate the asymptotic distribution of posterior parameters. Results: An optimal replacement age of block replacement policy is determined which minimizes cost and nonoperating time when no information on prior distribution of parameters is given. Conclusion: We find the posterior distribution of parameters when lack of information on prior distribution, so that the optimal replacement age which minimizes the total cost and maximizes the total values is determined.

A note on the test for the covariance matrix under normality

  • Park, Hyo-Il
    • Communications for Statistical Applications and Methods
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    • 제25권1호
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    • pp.71-78
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    • 2018
  • In this study, we consider the likelihood ratio test for the covariance matrix of the multivariate normal data. For this, we propose a method for obtaining null distributions of the likelihood ratio statistics by the Monte-Carlo approach when it is difficult to derive the exact null distributions theoretically. Then we compare the performance and precision of distributions obtained by the asymptotic normality and the Monte-Carlo method for the likelihood ratio test through a simulation study. Finally we discuss some interesting features related to the likelihood ratio test for the covariance matrix and the Monte-Carlo method for obtaining null distributions for the likelihood ratio statistics.