• Journal of the Korean Society for Railway
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• v.7 no.4
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• pp.302-306
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• 2004

Many long railway tunnels without emergency evacuation system or ventilation system are under construction or in-use in Korea. In the case of tunnel-fire, many fatalities are occur in current condition. Current safety level is estimated in this study, for the efficient investment on safety. But so many uncertainties in major input parameters make the safety estimation difficult. In this study, probabilistic techniques are applied for the consideration of uncertainties in major input parameters. As results of this study, accident scenarios and survival ratio under tunnel fire accident are determined for various conditions.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.4
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• pp.124-132
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• 2008

In this paper, a dynamical filter called the Highest Probability Data Association Filter(HPDAF) improved by adding target feature information is proposed for robust target detection and tracking in clutter. IIR contains 2-dimensional kinematic coordinate, intensity, and feature information. In data association of the HPDAF for track initiation, feature information is utilized in addition to coordinate and intensity information. The performance of the proposed HPDA algorithm is tested and compared with the conventional HPDAF algorithm for track initiation by a series of Monte Carlo simulation runs for a 3-dimensional missile-target engagement. scenario.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.739-747
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• 2010

In this paper, we propose new data association method called the Highest Probability Data Association(HPDA) using a Signal Amplitude information ordering method applied to active sonar tracking and track initiation in cluttered environment. The performance of HPDA is tested in a series of Monte Carlo simulations runs and is compared with the existing Probabilistic Data Association with Amplitude Information(PDA-AI) for active sonar tracking in clutter. The proposed HPDA algorithm is also applied to automatic track initiation in clutter and its performance is compared with the existing IPDA-AI algorithm.

• Annual Conference of KIPS
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• 2015.10a
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• pp.204-207
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• 2015

이 연구는 공학 및 실험과학에서 활용되는 몬테 칼로 시뮬레이션 기법 중 하나인 무작위 행보 알고리즘의 성능 개선을 목표로 하였다. 이를 위해 무작위 행보 과정에서 난수 발생부와 행보 진행부를 분리하여 처리 시간을 단축하는 방안과, 문제 영역의 계산 규모를 2단계로 분할하여 시뮬레이션의 수렴 속도를 향상 시키는 방안을 제안한다. 또한 대규모 문제를 병렬처리 가능하도록 구현하고, 서로 다른 작업 분할 방식을 혼합하여 최적화를 수행 하였다. 순차 알고리즘만으로 실험한 결과 단순 구현방법과 비교해 실행시간과 에너지 소모량이 각각 18%의 성능향상을 얻었으며, 병렬 알고리즘을 8개의 노드(16코어)의 클러스터에서 실행했을 때 행 분할 방식의 성능이 블록 분할 방식보다 8% 빨라지는 것을 확인하였다.

• Proceedings of the KIEE Conference
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• summer
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• pp.39-41
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• 2004

This paper presents a analytical method for the reliability evaluation of distribution system, including the distributed generations. Unlike the generators of transmission system, those of distribution system have complexities in analyzing and determining the operation. In the process of evaluate reliability, it could be shown that the analytical method is simpler than the monte-carlo simulation. Modeling technique of distributed generation to analysis distribution system reliability using frequency and duration method is proposed in this paper, and is compared with the simulation method as a result of the distribution system reliability evaluation.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.217-217
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• 2016

강우는 시 공간적 변동성이 크고 지형특성으로 인한 지역 편차가 큰 특성을 가지고 있다. 따라서 강우 발생을 분석하는 경우, 강우의 시 공간적 변동성과 지역특성을 고려해야한다. 본 연구에서는 지역특성을 고려한 강우 앙상블을 생성하였다. 강우의 지역특성을 고려하기 위해 2010~2015년 동안 발생한 강우사상 중 서울지역을 통과하는 대류성 강우사상 30개를 선정하였다. 지역특성 고려하기 위한 매개변수로 강우강도와 풍향을 선정하고, 매개변수의 가중인자를 결정하였다. 또한 매개변수의 정량화를 위해 강우강도의 경우 대수정규분포, 풍향의 경우 Von mises분포를 매개변수의 확률분포로 선정하고, 선정된 두 확률분포에 Copula함수를 적용하여 결합확률분포를 추정하였다. 아울러 추정된 결합확률분포에 Monte-Carlo Simulation기법을 적용하여 매개변수에 대한 난수를 발생시키고, 이를 이용하여 지역특성을 고려한 강우 앙상블을 생성하였다.

• Journal of the Korea Society for Simulation
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• v.8 no.3
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• pp.77-89
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• 1999

Simulating rare events, such as probability of cell loss in ATM networks, machine failure in highly reliable systems, requires huge simulation efforts due to the low chance of occurrence. Importance Sampling (IS) has been applied to accelerate the occurrence of rare events. However, it has a drawback of effective biasing scheme to make the estimator of IS unbiased. Adaptive Importance Sampling (AIS) employs an estimated sampling distribution of IS to the system of interest during the course of simulation. We propose Nonparametric Adaptive Importance Sampling (NAIS) technique which is nonparametrical version of AIS. We test NAIS to estimate a probability of rare event in M/M/1 queueing model. Comparing with classical Monte Carlo simulation, the computational efficiency and variance reductions gained via NAIS are substantial. A possible extension of NAIS regarding with random number generation is also discussed.

• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.282-288
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• 2015

A monte carlo simulation about shielding material and thickness of the syringe shield for radiation shield was performed. As a result of analysis, high atomic number materials such as tungsten, lead and bismuth have the highest shielding effect. However, $^{18}F$, $^{67}Ga$ and $^{111}In$ show high energy distribution in the region with thin shielding thickness. As the thickness of shielding materials increased, the energy distribution decreased due to reduction of ${\gamma}$-ray. In the case of low atomic number materials, they, showed energy distribution from highest to lowest, were barium sulfate, steel, stainless, iron and copper. Aluminum, plastic, concrete and water showed diverse aspect. they showed relatively high energy distribution because of increased ${\gamma}$-ray that penetrate the shield.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.3
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• pp.169-176
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• 2019

In the present study, a CFD/DSMC hybrid method performed by a coupled analysis between the CFD method and the DSMC method was developed to obtain the flow information on the rarefied gas flows effectively. Flow simulations around the high speed vehicles on the transition flow regimes were conducted by using the developed method. The FRESH-FX vehicle made of cone and cylinder shapes was considered for the simulations. The results of the hybrid method were compared with the results of the pure CFD and the pure DSMC method to confirm the reliability and efficiency of the hybrid method. It was found that the gradient and the intensity of the shock waves were weakened due to the relatively low density on the transition flow regime. It was confirmed that the results of the hybrid analysis were different to those of the pure CFD analysis and almost identical to those of the pure DSMC analysis. In addition, the computational time of the hybrid method was reduced than that of the pure DSMC method. As a result, it was obtained that the validity and the efficiency of the CFD/DSMC hybrid method.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.1
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• pp.61-67
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• 2017

For a project network analysis, a fundamental problem is to estimate the distribution function of the project completion time. In this paper, we propose a method for evaluating moments(mean, variance, skewness, kurtosis) of the project completion time under the assumption that the durations of activities are independently and normally distributed. The proposed method utilizes the technique of discretization to replace the continuous probability density function(pdf) of activity duration with its discrete pdf and a random number generation. The proposed method is easy to use for large-sized project networks, and the computational results of the proposed method indicate that the accuracy is comparable to that of direct Monte Carlo simulation.