• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2005년도 하계학술대회 논문집 Vol.6
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• pp.578-580
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• 2005

Energy distribution function for electrons in SF6-Ar mixtures gas used by MCS-BEq algorithm has been analysed over the E/N range 30~300[Td] by a two term Boltzmann equation and by a Monte Carlo Simulation using a set of electron cross sections determined by other authors, experimentally the electron swarm parameters for 0.2[%] and 0.5[%] $SF_6$-Ar mixtures were measured by TOF method, The results show that the deduced electron drift velocities, the electron ionization or attachment coefficients, longitudinal and transverse diffusion coefficients and mean energy agree reasonably well with theoretical for a rang of E/N values. The results obtained from Boltzmann equation method and Monte Carlo simulation have been compared with present and previously obtained data and respective set of electron collision cross sections of the molecules.

• 전기학회논문지P
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• 제56권1호
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• pp.1-5
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• 2007

Study on the electron transport coefficient in mixtures of CF4 and Ar, have been analyzed over a range of the reduced electric field strength between 0.1 and 350[Td] by the two-term approximation of the Boltzmann equation (BEq.) method and the Monte Carlo simulation (MCS). The calculations of electron swarm parameters require the knowledge of several collision cross-sections of electron beam. Thus, published momentum transfer, ionization, vibration, attachment, electronic excitation, and dissociation cross-sections of electrons for $CF_4$ and Ar, were used. The differences of the transport coefficients of electrons in $CF_4$ mixtures of Ar, have been explained by the deduced energy distribution functions for electrons and the complete collision cross-sections for electrons. The results of the Boltzmann equation and the Monte Carlo simulation have been compared with the data presented by several workers. The deduced transport coefficients for electrons agree reasonably well with the experimental and simulation data obtained by Nakamura and Hayashi. The energy distribution function of electrons in $CF_4-Ar$ mixtures shows the Maxwellian distribution for energy. That is, $f({\varepsilon})$ has the symmetrical shape whose axis of symmetry is a most probably energy. The proposed theoretical simulation techniques in this work will be useful to predict the fundamental process of charged particles and the breakdown properties of gas mixtures. A two-term approximation of the Boltzmann equation analysis and Monte Carlo simulation have been used to study electron transport coefficients.

• 대한전기학회논문지:전력기술부문A
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• 제53권2호
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• pp.121-128
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• 2004

This paper presents a new approach for determining an accurate incentive levels of Direct Load Control (DLC) program using sequential Monte Carlo Simulation (MCS) techniques. The economic analysis of DLC resources needs to identify the hourly-by-hourly expected energy-not-served resulting from the random outage characteristics of generators as well as to reflect the availability and duration of DLC resources, which results the computational explosion. Therefore, the conventional methods are based on the scenario approaches to reduce the computation time as well as to avoid the complexity of economic studies. In this paper, we have developed a new technique based on the sequential MCS to evaluate the required expected load control amount in each hour and to decide the incentive level satisfying the economic constraints. In addition, the mathematical formulation for DLC programs' economic evaluations are developed. To show the efficiency and effectiveness of the suggested method, the numerical studies have been performed for the modified IEEE reliability test system.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제24권1호
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• pp.79-84
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• 2020

In this article, we implement a recently developed fast Monte Carlo simulation (MCS) for pricing equity-linked securities (ELS), which is most commonly issued autocallable structured financial derivative in South Korea, on the mobile platform. The fast MCS is based on Brownian bridge technique. Although mobile platform devices are easy to carry around, mobile platform devices are slow in computation compared to desktop computers. Therefore, it is essential to use a fast algorithm for pricing ELS on the mobile platform. The computational results demonstrate the practicability of Android application implementation for pricing ELS.

• Structural Engineering and Mechanics
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• 제66권6호
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• pp.677-691
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• 2018

Reliability assessment of complex structures using simulation methods is time-consuming. Thus, surrogate models are usually employed to reduce computational cost. AK-MCS is a surrogate-based Active learning method combining Kriging and Monte-Carlo Simulation for structural reliability analysis. This paper proposes three modifications of the AK-MCS method to reduce the number of calls to the performance function. The first modification is related to the definition of an initial Design of Experiments (DoE). In the original AK-MCS method, an initial DoE is created by a random selection of samples among the Monte Carlo population. Therefore, samples in the failure region have fewer chances to be selected, because a small number of samples are usually located in the failure region compared to the safe region. The proposed method in this paper is based on a uniform selection of samples in the predefined domain, so more samples may be selected from the failure region. Another important parameter in the AK-MCS method is the size of the initial DoE. The algorithm may not predict the exact limit state surface with an insufficient number of initial samples. Thus, the second modification of the AK-MCS method is proposed to overcome this problem. The third modification is relevant to the type of regression trend in the AK-MCS method. The original AK-MCS method uses an ordinary Kriging model, so the regression part of Kriging model is an unknown constant value. In this paper, the effect of regression trend in the AK-MCS method is investigated for a benchmark problem, and it is shown that the appropriate choice of regression type could reduce the number of calls to the performance function. A stepwise approach is also presented to select a suitable trend of the Kriging model. The numerical results show the effectiveness of the proposed modifications.

• 전기학회논문지P
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• 제51권1호
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• pp.28-32
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• 2002

Energy distribution function for electrons in $SF_6+Ar$ mixtures gas used by MCS-BEq algorithm bas been analysed over the E/N range 30-300[Td] by a two term Boltzmann equation and by a Monte Carlo Simulation using a set of electron cross sections determined by other authors, experimentally the electron swarm parameters for 0.2[%] and 0.5[%] $SF_6+Ar$ mixtures were measured by time-of-flight(TOF) method. The results show that the deduced electron drift velocities, the electron ionization or attachment coefficients, longitudinal and transverse diffusion coefficients and mean energy agree reasonably well with theoretical for a rang of E/N values.

• 한국항공우주학회지
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• 제34권8호
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• pp.24-32
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• 2006

결정론적인 최적 설계 방법을 이용하는 경우 불확실성의 영향으로 인하여 제약조건의 위반이나 목표 성능의 저하를 초래할 수 있다. 이러한 까닭에 불확실성하에서 제약 조건에 대한 신뢰성을 보장하고 목적함수의 강건성을 확보하는 설계가 필요하다. 그러므로 본 연구에서는 강건성과 신뢰성을 평가하기 위하여 Monte Carlo Simulation(MCS)을 이용하였으며, 계산 효율의 증가를 위하여 MCS에 적합한 근사모델을 선정하는 과정을 거쳐 신경망 모델을 채택하게 되었다. 이를 공력-구조가 연동된 항공기 날개 설계 문제에 적용하여 봄으로써 그 가능성을 타진하였다. 불확실성을 고려한 최적 설계를 수행한 결과 요구되는 신뢰도 수준을 만족시키면서 baseline보다 강건한 최적해를 탐색하는 것이 가능하였다.

• 대한토목학회논문집
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• 제33권4호
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• pp.1433-1446
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• 2013

본 연구에서는 도시하천을 대상으로 Monte Carlo Simulation (MCS)에 의한 모의발생 기법 적용으로 최적화된 강우-유출 모형과 홍수위 추적모형 연계를 통한 고수위 Rating Curve 작성법을 제안하였다. 대상유역의 관측 자료로부터 작성된 수위-유량곡선식은 유량측정의 오차와 더불어 고수위에 대한 불확실성을 내포하고 있음을 확인할 수 있었으며, 관측치와의 표준오차($S_e$)는 0.056으로, 무작위 불확실성($2S_{mr}$)은 평균 ${\pm}1.43%$, 최대 ${\pm}4.27%$로 분석되었다. 또한, 전대수지법과 Stevens방법에 의한 고수위 연장은 도시하천 유역 규모에 비하여 수위에 따른 홍수량이 과대 산정되는 문제점이 있는 것으로 분석되었다. 마지막으로, MCS에 의한 다량의 수문자료군 확보를 통한 수위-유량 관계곡선의 연장방법은 고수위에 대한 불확실성을 감소시켜며, 보다 신뢰성 있는 고수위 연장이 가능하였다. 향후 본 연구의 결과는 MCS에 의한 고수위 연장 시스템 구축을 통한 도시하천유역의 실시간 홍수 예 경보 활용에 적용이 가능할 것으로 사료된다.

• Steel and Composite Structures
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• 제8권2호
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• pp.129-144
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• 2008

This paper demonstrates an application of the perturbation based stochastic finite element method (SFEM) for predicting the performance of structural systems made of composite sections with random material properties. The composite member consists of materials in contact each of which can surround a finite number of inclusions. The perturbation based stochastic finite element analysis can provide probabilistic behavior of a structure, only the first two moments of random variables need to be known, and should therefore be suitable as an alternative to Monte Carlo simulation (MCS) for realizing structural analysis. A summary of stiffness matrix formulation of composite systems and perturbation based stochastic finite element dynamic analysis formulation of structural systems made of composite sections is given. Two numerical examples are presented to illustrate the method. During stochastic analysis, displacements and sectional forces of composite systems are obtained from perturbation and Monte Carlo methods by changing elastic modulus as random variable. The results imply that perturbation based SFEM method gives close results to MCS method and it can be used instead of MCS method, especially, if computational cost is taken into consideration.

• 대한환경공학회지
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• 제30권11호
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• pp.1123-1131
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• 2008

본 연구는 대기 중 PM2.5의 미량금속 중 As을 중성자방사화분석법을 이용하여 분석할 때 발생되는 측정불확도를 ISO GUM 방법과 MCS 방법을 모두 적용하여 비교, 평가하였다. 불확도의 요인은 ISO GUM을 엄격하게 준용하여 파악하였으며 특정일에 채취된 PM2.5 내 As 농도에 대해 두 방법의 계산 결과가 4% 미만으로 크게 다르지 않는 것으로 나타났다. 연구기간 중 채취된 총 60개의 PM2.5 시료에 대해 As 농도의 확장불확도를 역시 MCS 방법을 이용하여 산출하였는데, 연구지역에서의 As의 개별 농도값에 대한 95% 신뢰구간의 확장불확도는 대부분 10%의 범위에서 존재하는 것으로 나타났다. 확장불확도에 대한 표준불확도 요인의 기여율은 계측통계오차(62.3%), 검출효율(18.5%), 시료 채취 시 유량(12.3%), flux 변동(2.3%), 특정감마선 방출률(1.8%) 등의 순으로 크게 나타났다.