• 물과 미래
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• 제26권2호
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• pp.89-97
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• 1993

Monte Carlo 기법을 이용하여 저수지군으로부터 위험도나 신뢰도를 고려한 시스템 편익을 최적화하기 위해서는 수많은 모의발생 유입량 자료군을 이용하여야 한다. 본 연구에서는 저수지군 연계운영을 위한 모의 발생 유입량 자료를 시스템 목적함수나 운영기간들을 고려하여 전처리함으로써 수많은 모의 발생 자료군으로부터 이산화된 확율값과 운영기간을 갖는 극히 제한된 대표 유입량을 선택한다. 선택된 대표 유입량 자료를 사용하여 확정론적 최적화 기법에 의거 이산화된 위험도나 신뢰도 수준을 갖는 기대편익을 산정하게 된다. 이와 같은 기법을 5개 저수지를 고려한 한강수계 저수지 시스템으로부터 전처리 된 평가함수별 신뢰도 수준을 갖는 발전편익 산정에 적용하였으며, 적용결과 신뢰도를 고려한 기대편익은 전형적인 Monte Carlo 기법에 의한 결과와 비슷한 수중이었으나 훨씬 적은 계산만을 요구하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 A
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• pp.636-638
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• 2003

This paper presents a new approach which is able to determine the reasonable incentive levels of direct load control using sequential Monte Carlo simulation techniques. The economic analysis needs to determine the reasonable incentive level. However, the conventional methods have been based on the scenario methods because they had not considered all cases of the direct load control situations. To overcome there problems, this paper proposes a new technique using sequential Monte Carlo simulation. The Monte Carlo method is a simple and flexible tool to consider large scale systems and complex models for the components of the system. To show its effectiveness, numerical studies were performed to indicate the possible applications of the proposed technique.

• 터널과지하공간
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• 제14권2호
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• pp.97-107
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• 2004

실내시험 및 현장시험 등으로부터 구해진 각종 암반 물성치를 설계에 반영시키기 위해 여러 가지 외삽법이 적용되고 있으며, 이 기법들은 대체적으로 충분한 현장 조사 및 시험을 통해 합리적인 RMR값을 도출한 뒤, 이를 토대로 강성 및 강도 정수를 산정하는 수순을 따르고 있다. 그러나 현장 여건상 충분한 시험조사가 이루어지지 못하여 RMR값의 정확한 도출이 곤란한 경우가 있을 수도 있으므로 이러한 경우를 대비하여 Monte Carlo Simulation 기법을 도입, 비교적 합리적이고 객관적인 RMR값을 역으로 추정하고 이를 통해 설계에 필요한 지반정수를 산정하는 새로운 기법을 제안코자 한다. 이렇게 제안된 새로운 지반정수 산정기법은 수치해석결과와 현장상황의 비교분석을 통해 그 타당성이 규명될 수 있을 것이다.

• 산업기술연구
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• 제22권B호
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• pp.3-12
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• 2002

Monte-Carlo simulation technique has advantages over deterministic simulation in various engineering analysis since Monte-Carlo simulation can take into consideration of scattering of various design variables, which is inherent characteristics of physical world. In this work, Monte-Carlo simulation of steady-state cornering behavior of a truck with design variables like hard points and busing stiffness. The purpose of the simulation is to improve understeer gradient of the truck, which exhibits a small amount of instability when the lateral acceleration is about 0.4g. Through correlation analysis, design variables that have high impacts on the cornering behavior were selected, and significant performance improvement has been achieved by appropriately changing the high impact design variables.

• Architectural research
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• 제8권2호
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• pp.27-36
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• 2006

Structural uncertainties are generally modeled using probabilistic approaches in order to quantify uncertainties in behaviors of structures. This uncertainty results from the uncertainties of structural parameters. Monte Carlo methods have been usually carried out for analyses of uncertainty problems where no analytical expression is available for the forward relationship between data and model parameters. In such cases any direct mathematical treatment is impossible, however the forward relation materializes itself as an algorithm allowing data to be calculated for any given model. This study addresses a new method which is utilized as a basis for the uncertainty estimates of structural responses. It applies double uniform random numbers (i.e. DURN technique) to conventional Monte Carlo algorithm. In DURN method, the scenarios of uncertainties are sequentially selected and executed in its simulation. Numerical examples demonstrate the beneficial effect that the technique can increase uncertainty degree of structural properties with maintaining structural stability and safety up to the limit point of a breakdown of structural systems.

• Structural Engineering and Mechanics
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• 제81권1호
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• pp.103-115
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• 2022

The prediction error variances for frequencies are usually considered as unknown in the Bayesian system identification process. However, the error variances for mode shapes are taken as known to reduce the dimension of an identification problem. The present study attempts to explore the effectiveness of Bayesian approach of model parameters updating using Markov Chain Monte Carlo (MCMC) technique considering the prediction error variances for both the frequencies and mode shapes. To remove the ergodicity of Markov Chain, the posterior distribution is obtained by Gaussian Random walk over the proposal distribution. The prior distributions of prediction error variances of modal evidences are implemented through inverse gamma distribution to assess the effectiveness of estimation of posterior values of model parameters. The issue of incomplete data that makes the problem ill-conditioned and the associated singularity problem is prudently dealt in by adopting a regularization technique. The proposed approach is demonstrated numerically by considering an eight-storey frame model with both complete and incomplete modal data sets. Further, to study the effectiveness of the proposed approach, a comparative study with regard to accuracy and computational efficacy of the proposed approach is made with the Sequential Monte Carlo approach of model parameter updating.

• 한국방재학회 논문집
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• 제9권3호
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• pp.127-133
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• 2009

본 연구에서는 다변량 Monte Carlo 기법을 이용하여 무차원 누가강우량 곡선을 생성하였다. 이를 위해 30년 이상의 관측년수를 갖는 강우자료를 활용하여 강우사상을 분리하고 이를 무차원화하여 강우의 지역적, 시간적 변동성을 제거하였다. 그리고 이들 무차원화된 누가강우량곡선을 4가지 형태로 구분하여 강우자료 특성을 반영한 누가강우량 곡선을 생성하였다. 무차원 누가 강우량 곡선의 절점이 항상 0이상이고 전체의 합이 1이 되어야 하는 제약조건을 극복하기 위해 log-ratio 기법을 도입하였고 Monte Carlo 기법을 이용한 다변량 생성시 요구되는 정규화와 상관계수 반영의 문제점을 Johnson 시스템과 직교변환을 도입하여 모형에 적용함으로서 제약조건을 극복할 수 있었다. 본 연구에서 적용한 다변량 Monte Carlo 기법을 이용한 강우변동생성기법은 실제 강우량 자료의 특성을 가공없이 반영할 수 있어 해당 유역의 특성을 정확히 반영할 수 있었고 유역의 홍수대책 수립, 수공구조물 설계 및 분석 등 활용성이 매우 클 것으로 판단된다.

• Journal of electromagnetic engineering and science
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• 제5권2호
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• pp.87-91
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• 2005

This paper presents a Monte-Carlo FDTD technique to determine the scattered field from a perfectly conducting surface like a sea surface, from which the useful information on the incoherent pattern tendency could be observed. A one-dimensional sea surface used to analysis scattering was generated using the Pierson-Moskowitz model. In order to verify the numerical results by this technique, these results are compared with those of the small perturbation method, which show a good match between them. To investigate the incoherent pattern tendency involved, the dependence of the back scattering coefficients on the different wind speed(U) is discussed for the back scattering case.

• 한국전산유체공학회지
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• 제4권3호
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• pp.63-70
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• 1999

A Direct simulation Monte-Carlo (DSMC) code is developed, which employs the Monte-Carlo statistical sampling technique to investigate hypersonic rarefied gas flows accompanying chemical reactions. The DSMC method is a numerical simulation technique for analyzing the Boltzmann equation by modeling a real gas flow using a representative set of molecules. Due to the limitations in computational requirements. the present method is applied to a flow around a simple two-dimensional object in exit velocity of 7.6 km/sec at an altitude of 90 km. For the calculation of chemical reactions an air model with five species (O₂, N₂, O, N, NO) and 19 chemical reactions is employed. The simulated result showed various rarefaction effects in the hypersonic flow with chemical reactions.

• 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.