• Journal of Technology Innovation
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• v.6 no.2
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• pp.178-207
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• 1998

This article suggests a methodology to decide the priority of investment project for venture business under the dynamic circumstance. By the Monte Carlo procedure on the probability distribution of cost and revenue, the model simulates the investment project to estimate profit ratio and risk. The profit ratio is calculated on the yearly basis for the relative comparison. The project risk is calculated as semi-variance under the target yield. After sufficient simulations in this fashion for several projects, the efficient projects with more profit and less risk are selected by the dominance principle. Then the regression equation of the selected projects is produced to find the relative value of the projects. The relative value is obtained through dividing the raw profit ratio by the estimated one on the equation. This value shows the degree to which the simulated project yields over the equation. The priority of investment is decided by this value. An examplary venture business of chemical development for semi-conductor is presented as a case study.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.1
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• pp.104-115
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• 1997

This paper investigates PN code acquistion algorithm and demodulation performance of the RAKE receiver in the DS/CDMA(direct sequence code division multiple access) sysytems under a multipath fading channel with multiusers. To speed up the acquisition process, PN matched filter is applied and postdetection integration technique comable withthe dynamic threshold set method is proposed. the Maximum-Likelihood algorithmin serial fashion is able to find PN code delay estimates for the RAKE branches using sliding window in a multipath fading channel. The correct acquistion probability and mean acquistion time are used as a performance measure of the system using the Monte Carlo method. The performance of the RAKEreceiver, afte the code acquisition is achieved is the CDMA systems, is also investigated for three major combining techniques.

• Structural Engineering and Mechanics
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• v.22 no.4
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• pp.469-481
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• 2006

A new method called fuzzy factor method for the stationary stochastic response analysis of fuzzy truss with global fuzzy structural parameters is presented in this paper. Considering the fuzziness of the structural physical parameters and geometric dimensions simultaneously, the fuzzy correlation function matrix of structural displacement response in time domain is derived by using the fuzzy factor method and the optimization method, the fuzzy mean square values of the structural displacement and stress response in the frequency domain are then developed with the fuzzy factor method. The influences of the fuzziness of structural parameters on the fuzziness of mean square values of the displacement and stress response are inspected via an example and some important conclusions are obtained. Finally, the example is simulated by Monte-Carlo method and the results of the two methods are close, which verified the feasibility of the method given in this paper.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.411-414
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• 2011

구조물에서의 소음은 일반적으로 볼트, 스냅, 힌지, 용접 등과 같은 체결부에서 발생한다. 이러한 소음을 정확히 예측하기 위해서는 구조물이 갖는 실제적인 동적특성(고유진동수, 주파수응답함수) 해석기술이 필수적으로 선행되어야 한다. 그러나 현재의 동적특성 해석기술은 체결부 특성을 무시하거나 많은 시간을 수반되는 상세모델을 적용하여 해석한다. 본 연구에서는 간단한 요소를 사용하여 체결부 상세모델을 대처할 수 있는 등가모델 개발을 수행하였고 실제모델과의 비교를 통해 타당성을 검증하였다. 또한, Monte-Carlo Simulation(MCS)을 사용하여 구조물의 확률기반 해석을 수행하였다.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2433-2435
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• 2000

Inertial Navigation System(INS) provides short-term accurate navigation solution but its error grows with time due to integration characteristics. Meanwhile, Global Positioning System(GPS) provides long-term stable solution but it has poor error characteristics in high dynamic region. So for its synergistic relationship, an integrated INS/GPS systems has been widely used as an advanced navigation system. Generally, two kinds of integration method are used. One is loosely coupled mode which uses GPS-derived position and velocity as measurements in an integrated Kalman filter. The other is tightly coupled one which uses pseudorange and pseudorange rate as Kalman filter measurements. In this paper the system error models and observation models for two kinds of integrated systems are derived, respectively, and their performance are compared through Monte-Carlo simulations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.63
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• pp.33-43
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• 2001

To estimate the reliability of a large and complex network with a small variance, we propose two dynamic Monte Carlo sampling methods: the sequential minimal cut set (SMCS) and the sequential minimal path set (SMPS) methods. These methods do not require all minimal cut sets or path sets to be given in advance and do not simulate all arcs at each trial, which can decrease the valiance of network reliability. Based on the proposed methods, we develop the importance sampling estimators, the total hazard (or safety) estimator and the hazard (or safety) importance sampling estimator, and compare the performance of these simulation estimators. It is found that these estimators can significantly reduce the variance of the raw simulation estimator and the usual importance sampling estimator. Especially, the SMCS algorithm is very effective in case that the failure probabilities of arcs are low. On the contrary, the SMPS algorithm is effective in case that the success Probabilities of arcs are low.

• Journal of ILASS-Korea
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• v.3 no.4
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• pp.65-76
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• 1998

An experimental and numerical study of a spray flow is performed to investigate the spray characteristics using an air-assisted atomizer. A Partical Dynamic Analyzer(PDA) is used to measure SMD, dmp velocity, and drop number density whose the initial conditions have considerable effect on the numerical results. The measured experimental data have been used to asses the accuracy of model predictions. Numerical investigation is made with the Eulerian - Lagrangian formulism. Turbulent dispersion effects using a Monte-Carlo method, turbulent modulation effect and entrainment of air are also numerically simulated. Results show that the numerical predictions of SSF(Stochastic Separated Flow) analysis yielded reasonable agreement with the experimental data. However, the model calculations for small drops produced the inconsistent numerical results due to the effect of surrounding air entrainment.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.166-173
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• 2002

Seismic bridge failure due to the combined effects of earthquake and local scour are examined in probabilistic perspectives. The seismic responses of multi-span continuous bridge with deep foundations are evaluated with a simplified mechanical model. The probabilistic local scour depths around the deep foundations are estimated by using the Monte Carlo simulation. From the simulation results, it is found that seismic responses of a bridge slightly increase due to the local scour effect. The effect of local scour on the global motion of the continuous bridge is found to be significant under weak seismic intensity. In addition, the duration to regain its original foundation stiffness is critical in estimating the probability of foundation failure under earthquake. Therefore, the duration in recovering the foundation stiffness should be determined reasonably and the safely of the whole bridge system should be evaluated by considering the scour effect.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.581-585
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• 2010

This study introduced a Bayesian based frequency analysis in which the statistical trend seasonal analysis for hydrologic extreme series is incorporated. The proposed model employed Gumbel and GEV extreme distribution to characterize extreme events and a fully coupled bayesian frequency model was finally utilized to estimate design rainfalls in Seoul. Posterior distributions of the model parameters in both trend and seasonal analysis were updated through Markov Chain Monte Carlo Simulation mainly utilizing Gibbs sampler. This study proposed a way to make use of nonstationary frequency model for dynamic risk analysis, and showed an increase of hydrologic risk with time varying probability density functions. In addition, full annual cycle of the design rainfall through seasonal model could be applied to annual control such as dam operation, flood control, irrigation water management, and so on. The proposed study showed advantage in assessing statistical significance of parameters associated with trend analysis through statistical inference utilizing derived posterior distributions.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.93-96
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• 2006

This study represents results of performance-based fragility analysis of reinforced concrete (RC) bridge. Monte carlo simulation is performed to study nonlinear dynamic responses of RC bridge. Two-parameter log-normal distribution function is used to represent the fragility curves. These two-parameters, referred to as fragility parameters, are estimated by the traditional maximum likelihood procedure, which. is treated each event of RC bridge pier damage as a realization of Bernoulli experiment. In order to formulate the fragility curves, five different damage states are described by two practical factors: the displacement and curvature ductility, which are mostly influencing on the seismic behavior of RC bridge piers. Five damage states are quantitatively assessed in terms of these seismic ductilities on the basis of numerous experimental results of RC bridge piers. Thereby, the performance-based fragility curves of RC bridge pier are provided in this paper.