• 한국식품과학회지
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• 제38권4호
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• pp.589-593
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• 2006

돈육 가공 공정에 대한 QRA에 Monte Carlo simulation이 적용된 바 있는데, 새로운 방법으로 fuzzy 연산을 적용하여 Monte Carlo simulation과 비교 분석하였다. Carcass단계에 대한 오염 예측치인 fuzzy 값과 Monte Carlo simulation 확률분포 값의 기술통계량인 평균값은 각각 -4.393 log $CFU/cm^2$, -4.589 log $CFU/cm^2$ 로 나타났으며, processing 단계에서는 -4.185 log $CFU/cm^2$, -4.466 log $CFU/cm^2$으로 두 가지 접근 방법들이 비슷한 경향을 보였다. Fuzzy 값은 Monte Carlo simulation 확률분포 값을 포함하는 것으로 나타났다. 한편 최근 국내에서는 위해 평가에 대한 연구가 많이 이루어지고 있는데 대부분 데이터 분석은 Monte Carlo simulation에만 의존하고 있고, 다른 접근 방법에 대한 연구는 미진한 실정이다. 따라서 본 연구는 위해 평가를 위한 방법적 도구들을 개발하는데 새로운 접근 방향을 제시하였다 또한 향후 fuzzy 연산법은 데이터가 불충분한 위해 평가의 초기 단계에서 유용하게 사용될 수 있는 방법이 될 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.

• 한국정밀공학회지
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• 제29권4호
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• pp.479-486
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• 2012

Two of fundamental approaches that can be used to understand ion-solid interaction are Monte Carlo (MC) and Molecular Dynamic (MD) simulations. For the simplicity of simulation Monte Carlo simulation method is widely preferred. In this paper, basic consideration and algorithm of Monte Carlo simulation will be presented as well as simulation results. Sputtering caused by incident ion beam will be discussed with distribution of sputtered particles and their energy distributions. Redeposition of sputtered particles that are experienced refraction at the substrate-vacuum interface additionally presented. In addition, reflection of incident ions with reflection coefficient will be presented together with spatial and energy distributions. This Monte Carlo simulation will be useful in simulating and describing ion beam related processes such as Ion beam induced deposition/etching process, local nano-scale distribution of focused ion beam implanted ions, and ion microscope imaging process etc.

• Structural Engineering and Mechanics
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• 제32권1호
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• pp.1-20
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• 2009

The present contribution addresses uncertainty quantification and uncertainty propagation in structural mechanics using stochastic analysis. Presently available procedures to describe uncertainties in load and resistance within a suitable mathematical framework are shortly addressed. Monte Carlo methods are proposed for studying the variability in the structural properties and for their propagation to the response. The general applicability and versatility of Monte Carlo Simulation is demonstrated in the context with computational models that have been developed for deterministic structural analysis. After discussing Direct Monte Carlo Simulation for the assessment of the response variability, some recently developed advanced Monte Carlo methods applied for reliability assessment are described, such as Importance Sampling for linear uncertain structures subjected to Gaussian loading, Line Sampling in linear dynamics and Subset simulation. The numerical example demonstrates the applicability of Line Sampling to general linear uncertain FE systems under Gaussian distributed excitation.

• 대한화학회지
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• 제62권3호
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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.

• JSTS:Journal of Semiconductor Technology and Science
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• 제9권1호
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• pp.67-74
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• 2009

Monte Carlo simulation is widely used for predicting ion implantation profiles in amorphous targets. Here, we compared Monte Carlo simulation results with a vast database of ion implantation secondary ion mass spectrometry (SIMS), and showed that the Monte Carlo data sometimes deviated from the experimental data. We modified the electron stopping power model, calibrated its parameters, and reproduced most of the database. We also demonstrated that Monte Carlo simulation can accurately predict profiles in a low energy range of around 1keV once it is calibrated in the higher energy region.

• 한국농공학회지
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• 제32권E호
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• pp.59-66
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• 1990

Abstract The formulation of the probabilistic finite element method was briefly reviewed. The method was implemented into a computer program for frame analysis which has the same analogy as finite element analysis. Another program for Monte Carlo simulation of finite element analysis was written. Two sample structures were assumed and analized. The characteristics of the second moment statistics obtained by the probabilistic finite element method was examined through numerical studies. The applicability and limitation of the method were also evaluated in comparison with the data generated by Monte Carlo simulation.

• Structural Engineering and Mechanics
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• 제17권2호
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• pp.267-279
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• 2004

This paper presents an improved Monte Carlo simulation for the probabilistic determination of initial cable forces of cable-stayed bridges under dead loads using the response surfaces method. A response surface (i.e. a quadratic response surface without cross-terms) is used to approximate structural response. The use of the response surface eliminates the need to perform a deterministic analysis in each simulation loop. In addition, use of the response surface requires fewer simulation loops than conventional Monte Carlo simulation. Thereby, the computation time is saved significantly. The statistics (e.g. mean value, standard deviation) of the structural response are calculated through conventional Monte Carlo simulation method. By using Monte Carlo simulation, it is possible to use the existing deterministic finite element code without modifying it. Probabilistic analysis of a truss demonstrates the proposed method' efficiency and accuracy; probabilistic determination of initial cable forces of a cable-stayed bridge under dead loads verifies the method's applicability.

• 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.

• 대한화학회지
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• 제47권1호
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• pp.31-37
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• 2003

측정 및 화학분석에 많이 이용되는 한 점 교정식에 대하여 측정 불확도 표기 지침서(GUM)의 근사법과 Monte-Carlo Simulation에 의해 계산된 각각의 확장불확도를 비교하였다. 이 비교를 위하여 임의의 자료들을 여러 농도 수준에서 정규 분포 또는 t-분포로 가정하여 계산하였다. 나눗셈에 의한 한 점 교정식의 비선형성과 t-분포 형식을 함에 따른 입력량의 과도한 퍼짐으로 인하여, 경우에 따라서, GUM의 근사법으로 계산된 불확도가 Monte-Carlo Simulation에 의해 계산된 것보다 약 50% 이상의 오류가 있다는 것이 확인되었다. 그러나, 검출 하한을 계산하기 위하여 한 점 교정식을 이용하는 경우, 반응량의 표준불확도가 상대적으로 매우 크고 비선형성에 희한 계산 오류가 상대적으로 무시되므로 근사식에 따른 계산 오류가 발생하지 않았다.