• 한국군사과학기술학회지
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• 제14권5호
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• pp.859-870
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• 2011

The purpose of this paper is to develop reliability analysis procedures for repairable systems with interval failure time data and apply the procedures for assessing the storage reliability of a subsystem of a certain type of guided missile. In the procedures, the interval failure time data are converted to pseudo failure times using the uniform random generation method, mid-point method or equispaced intervals method. Then, such analytic trend tests as Laplace, Lewis-Robinson, Pair-wise Comparison Nonparametric tests are used to determine whether the failure process follows a renewal or non-renewal process. Monte Carlo simulation experiments are conducted to compare the three conversion methods in terms of the statistical performance for each trend test when the underlying process is homogeneous Poisson, renewal, or non-homogeneous Poisson. The simulation results show that the uniform random generation method is best among the three. These results are applied to actual field data collected for a subsystem of a certain type of guided missile to identify its failure process and to estimate its mean time to failure and annual mean repair cost.

• 응용통계연구
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• 제15권2호
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• pp.297-310
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• 2002

Liang과 Zeger는 이산형 혹은 연속형 반복측정자료를 분석하기 위한 일반화 추정방정식 (GEE)을 제안하였다 GEE모형은 범주형 반복측정자료의 모형으로 확장될 수 있으며, 이 GEE추정량은 대표본인 경우 다변량 정규분포를 따른다. 그러나 GEE는 대표본근사이론에 기초한다. 본 논문에서는 소표본인 경우 반복 측정된 순서자료에 대한 GEE추정량의 성질을 연구한다. 우리는 두가지 방법을 사용하여 두그룹의 반복 측정된 순서자료를 생성하며 모의실험을 통하여 소표본인 경우 여러 개 범주를 갖는 순서반응 자료에 대하여 GEE추정량의 1종 오류율, 검정력, 상대효율, 두 그룹의 표본크기가 다를 경우 효과, 그리고 분산 추정량의 성질등을 연구한다.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2005년도 추계 학술대회논문집
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• pp.11-19
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• 2005

First, methods of numerical analysis of gas-particle flows is classified into micro, meso and macro scale approaches based on the concept of multi-scale mechanics. Next, the explanation moves on to discrete particle simulation where motion of individual particles is calculated numerically using the Newtonian equations of motion. The author focuses on the cases where particle-to-particle interaction has significant effects on the phenomena. Concerning the particle-to-particle interaction, two cases are considered: the one is collision-dominated flows and the other is the contact-dominated flows. To treat this interaction mathematically, techniques named DEM(Distinct Element Method) or DSMC (Direct Simulation Monte Carlo) have been developed DEM, which has been developed in the field of soil mechanics, is useful for the contact -dominated flows and DSMC method, developed in molecular gas flows, is for the collision-dominated flows. Combining DEM or DSMC with CFD (computer fluid dynamics), the discrete particle simulation becomes a more practical tool for industrial flows because not only the particle-particle interaction but particle-fluid interaction can be handled. As examples of simulations, various results are shown, such as hopper flows, particle segregation phenomena, particle mixing in a rotating drum, dense phase pneumatic conveying, spouted bed, dense phase fluidized bed, fast circulating fluidized bed and so on.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2002년도 학술발표회 발표논문집
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• pp.237-240
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• 2002

Design rainfall using LH-moments following the consecutive duration were derived by the regional and at-site analysis using the observed and simulated data resulted from Monte Carlo techniques. RRMSE, RBIAS and RR in RRMSE for the design rainfall were computed and compared in the regional and at-site frequency analysis. Consequently, it was shown that the regional analysis can substantially more reduce the RRMSE, RBIAS and RR in RRMSE than at-site analysis in the prediction of design rainfall. RE for an optimal order of L-moments was also computed by the methods of L, L1, L2, L3 and L4-moments for GEV distribution. It was found that the method of L-moments is more effective than the others for getting optimal design rainfall according to the regions and consecutive durations in the regional frequency analysis. Diagrams for the design rainfall derived by the regional frequency analysis using L-moments were drawn according to the regions and consecutive durations by GIS techniques.

• 한국조명전기설비학회지:조명전기설비
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• 제10권2호
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• pp.45-53
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• 1996

평균조도 계산법 중에서 국내에서 주로 사용되는 3배광법과 ZCM의 정확도를 비교하고, 그 적용한계를 파악하였다. 비교방법은 전반확산형 조명기구와 직접식 조명기구에 대하여 3배광법과 ZCM에 의한 조명률을 계산하고, 이 값들을 이용하여 여러 상황하에서의 평균조도를 계산하였다. 몬테카를로 시뮬레이션으로 동일상황에서의 조도값을 구하고, 이 값과 3배광법과 ZCM의 조도값을 각각 비교하였다. MCS법의 정확도는 Moon위 해석적인 방법과 비교하여 입증하였다. 연구결과는 다음과 같다. 1. 방의 크기에 따른 평균조도 비교에서 전반확　형 조명기구와 직접식 조명기구의 경우 3배광법 보다 ZCM이 평균조도 오차가 적었다. 2. 광원의 수 변화에 따른 평균조도 비교에서 직접식 조명기구의 경우 3배광법은 광원의 수가 증가할수록 평균조도 오차가 감소하다가 다시 증가하였고 ZCM 은 점차적으로 감소하였다. 3. 실내면 반사율 변화에 따른 비교에서 직접식 조명기구의 경우 오차 범의가 3배광법에서 크고 ZCM에서 적게 나타냈다. 4. 방의 형태 변화에 따른 평균조도 비교에서 직접식 조명기구의 경우 방의 폭이 좁고 길이가 긴 공간에서 3배광법과 ZCM모두 오차가 크게 낱났다. 또 정방형에서 가까울수록 오차는 작아지면서 3배광법 보다 ZCM의 오차가 적었다. 그러므로 우리나라에서 혼용되고 있는 3배광법과 ZCM중에서 정확도가 높은 ZCM선택이 바람직하다.

• Structural Engineering and Mechanics
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• 제32권1호
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• pp.95-126
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• 2009

The present contribution addresses the parallelization of advanced simulation methods for structural reliability analysis, which have recently been developed for large-scale structures with a high number of uncertain parameters. In particular, the Line Sampling method and the Subset Simulation method are considered. The proposed parallel algorithms exploit the parallelism associated with the possibility to simultaneously perform independent FE analyses. For the Line Sampling method a parallelization scheme is proposed both for the actual sampling process, and for the statistical gradient estimation method used to identify the so-called important direction of the Line Sampling scheme. Two parallelization strategies are investigated for the Subset Simulation method: the first one consists in the embarrassingly parallel advancement of distinct Markov chains; in this case the speedup is bounded by the number of chains advanced simultaneously. The second parallel Subset Simulation algorithm utilizes the concept of speculative computing. Speedup measurements in context with the FE model of a multistory building (24,000 DOFs) show the reduction of the wall-clock time to a very viable amount (<10 minutes for Line Sampling and ${\approx}$ 1 hour for Subset Simulation). The measurements, conducted on clusters of multi-core nodes, also indicate a strong sensitivity of the parallel performance to the load level of the nodes, in terms of the number of simultaneously used cores. This performance degradation is related to memory bottlenecks during the modal analysis required during each FE analysis.

• Structural Engineering and Mechanics
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• 제25권3호
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• pp.311-330
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• 2007

Model-based predictions of structural behavior are negatively affected by uncertainties of various type and in various stages of the structural analysis. The present paper focusses on dynamic analysis and addresses the effects of uncertainties concerning material and geometric parameters, mainly in the context of modal analysis of large-scale structures. Given the large number of uncertain parameters arising in this case, highly scalable simulation-based methods are adopted, which can deal with possibly thousands of uncertain parameters. In order to solve the reliability problem, i.e., the estimation of very small exceedance probabilities, an advanced simulation method called Line Sampling is used. In combination with an efficient algorithm for the estimation of the most important uncertain parameters, the method provides good estimates of the failure probability and enables one to quantify the error in the estimate. Another aspect here considered is the uncertainty quantification for closely-spaced eigenfrequencies. The solution here adopted represents each eigenfrequency as a weighted superposition of the full set of eigenfrequencies. In a case study performed with the FE model of a satellite it is shown that the effects of uncertain parameters can be very different in magnitude, depending on the considered response quantity. In particular, the uncertainty in the quantities of interest (eigenfrequencies) turns out to be mainly caused by very few of the uncertain parameters, which results in sharp estimates of the failure probabilities at low computational cost.

• 한국자동차공학회논문집
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• 제11권5호
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• pp.89-94
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• 2003

Rolling stock structures such as bogie frame and car body play an important role for the support of vehicle leading. In general, more than 25 years' durability is needed for them. A lot of study has been carried out for the prediction of the fatigue life of the bogie frame and car body in experimental and theoretical domains. One of the new methods is a probabilistic fatigue lift evaluation. The objective of this paper is to estimate the fatigue lift of the bogie frame of an electric car, which was developed by the Korea Railroad Research Institute (KRRI). We used two approaches. In the first approach probabilistic distribution of S-N curve and limit state function of the equivalent stress of the measured stress spectra are used. In the second approach, limit state function is also used. And load spectra measured by strain gauges are approximated by the two-parameter Weibull distribution. Other probabilistic variables are represented by log-normal and normal distributions. Finally, reliability index and structural integrity of the bogie frame are estimated.

• Earthquakes and Structures
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• 제14권5호
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• pp.425-436
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• 2018

The design of seismically isolated structures considering the stochastic nature of excitations, base isolators' design parameters, and superstructure properties requires robust reliability analysis methods to calculate the failure probability of the entire system. Here, by applying artificial neural networks, we proposed a robust technique to accelerate the estimation of failure probability of equipped isolated structures. A three-story isolated building with susceptible facilities is considered as the analytical model to evaluate our technique. First, we employed a sensitivity analysis method to identify the critical sources of uncertainty. Next, we calculated the probability of failure for a particular set of random variables, performing Monte Carlo simulations based on the dynamic nonlinear time-history analysis. Finally, using a set of designed neural networks as a surrogate model for the structural analysis, we assessed once again the probability of the failure. Comparing the obtained results demonstrates that the surrogate model can attain precise estimations of the probability of failure. Moreover, our proposed approach significantly increases the computational efficiency corresponding to the dynamic time-history analysis of the structure.

• 응용통계연구
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• 제27권7호
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• pp.1115-1123
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• 2014

제 1상 임상시험의 주목적은 시험약의 독성을 평가하여 부작용을 최소화하고 안전하게 투여할 수 있는 적정 용량인 최대허용용량(Maximum Tolerated Dose; MTD)의 추정이다. 기존에 최대허용용량 추정 방법에는 SM방법(Storer, 1989; Korn 등, 1994), ATD방법(Simon 등, 1997) 그리고 DM방법(Dixon과 Mood, 1948) 등이 있다. 본 논문에서는 초기 가속 단계를 적용하여 약효가 없는 낮은 용량에 많은 피험자들이 배정되는 점을 보완하고, 이 초기 가속 단계로 빠르게 용량을 증가함으로 인해 떨어진 안전성을 개선하기 위해 용량감량을 허용하는 방법을 적용시켜 MTD 를 추정하는 방법을 제안하였다. 기존의 방법들과 본 논문에서 제안한 방법을 모의실험을 통해 비교하였다.