• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.366-366
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• 2012

확률강우량은 하천설계, 수자원설계 및 계획을 위한 기초자료로 활용되며 최근 이상기후 및 기후변화로 인한 극치강우의 빈도 및 양적 증가로 인한 확률강우량 산정의 불확실성 분석에 대한 관심이 크게 증가하고 있다. 수문빈도 해석에 있어서 대부분 지역이 50년 이하의 수문자료가 이용되고 있으며 수문설계에서 요구되는 50년 이상의 확률강수량 추정시에는 상당한 불확실성을 내포하고 있다. 이러한 점에서 본 연구에서는 자료연수에 따른 Sampling Error와 분포형의 매개변수의 불확실성을 고려한 해석모형을 구축하고자 한다. 빈도해석에서 매개변수를 추정하기 위해서는 일반적으로 모멘트법, 최우도법, 확률가중모멘트법이 이용되고 있으나 사용되는 분포형에 따라서 통계학적으로 불확실성 구간을 정량화하는 과정이 난해할 뿐만 아니라 극치 수문자료가 Thick-Tailed분포의 특성을 가짐에도 불구하고 신뢰구간 산정시 정규분포로 가정하는 등 기존 해석 방법에는 많은 문제점을 내포하고 있다. 본 연구에서는 이러한 매개변수의 불확실성 평가에 있어서 우수한 해석능력을 발휘하는 Bayesian기법을 도입하여 분포형의 매개변수를 추정하고 매개변수 추정과 관련된 불확실성을 평가하고자 한다. 이와 별개로 자료연한에 따른 Sampling Error를 추정하기 위해서 Bootstrapping 기반의 해석모형을 구축하고자 하며 최종적으로 빈도해석시에 나타나는 불확실성을 종합적으로 검토하였다. 빈도해석을 위한 확률분포형으로 GEV(generalized extreme value)분포를 이용하였으며 Gibbs 샘플러를 활용한 Bayesian Markov Chain Monte Carlo 모의를 기본 해석모형으로 활용하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.981-981
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• 2012

최근 지구환경 변화에 따른 기후변화의 영향으로 자연재해의 형태는 점차 대형화, 다양화되고 있으며 극치사상의 발생 빈도가 계속해서 증가하고 있는 추세이다. 특히 도시하천의 경우 인구와 재산이 밀집해 있어 기후변화에 따른 홍수위험 및 취약성이 클 것으로 사료된다. 본 연구에서는 기후 변화에 따른 홍수위험 및 취약성 분석을 위하여 위험도 기반 불확실성을 다루는 수단으로 UQR-MCS (Upper Quartile Range-Monte Carlo Simulation)을 적용하였으며, 다양한 형태의 확률 분포로부터 특정변량(variable)의 확률분포 Quartile을 모의하였다. 또한 기후변화에 따른 도시하천의 홍수위험 및 취약성 평가를 위하여 도시하천에 적합한 홍수위험 및 취약성평가 지수(FVI: flood vulnerability index)를 산정하였으며, 홍수취약성지수는 기후변화(Climate change)와 도시화(Urbanization), 제방월류위험(Overtopping risk) 및 홍수범람 면적(Flood area) 등의 지표를 사용하였다. 각각의 지표는 엔트로피(Entropy) 기법을 적용하여 가중치를 부여하였으며, 표준화과정을 통한 일반화된 지표 값을 산정하였다. 우이천 유역의 기후변화에 따른 홍수위험 및 취약성 지표값은 KMA RCM A1B 시나리오자료를 바탕으로 추정한 미래 확률강수량과 각 인자별 재현기간에 따른 수문변량의 변화를 통하여 산정하였다. 본 연구의 결과는 향후 도시하천의 기후변화에 따른 홍수위험도분석 및 취약성 평가, 극치 수문사상에 대한 신뢰성 있는 분석과 더불어 예상치 못할 이상홍수에 대비한 하천방재 연구에 도움이 되리라 사료된다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.4
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• pp.274-282
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• 2019

Vision-based navigation of unmaned aerial vehicle is a significant technology that can reinforce the vulnerability of the widely used GPS/INS integrated navigation system. However, the existing image matching algorithms are not suitable for matching the aerial image with the database. For the reason, this paper proposes particle filters using Gaussian mixture models to deal with matching between aerial image and database for vision-based navigation. The particle filters estimate the position of the aircraft by comparing the correspondences of aerial image and database under the assumption of Gaussian mixture model. Finally, Monte Carlo simulation is presented to demonstrate performance of the proposed method.

• Journal of Korea Water Resources Association
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• v.42 no.12
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• pp.1039-1052
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• 2009

Radar measurement with high temporal and spatial resolutions can be a valuable source of data, especially in the areas where rain gauge installment is not practical. However, this kind of data brings with it many errors. The objective of this paper is to propose a method to evaluate statistically the quantitative and qualitative accuracy at different radar ranges, temporal intervals and raingage densities and use a bias adjustment technique to improve the quality of radar rainfall for the purpose of hydrological application. The method is tested with the data of 2 storm events collected at Jindo (S band) and Kwanak (C band) radar stations. The obtained results show that the accuracy of radar rainfall estimation increases when time interval rises. Radar data at the shorter range seems to be more accurate than the further one, especially for C-band radar. Using the Monte Carlo simulation experiment, we find out that the sampling error of the bias between radar and gauge rainfall reduces nonlinearly with increasing raingage density. The accuracy can be improved considerably if the real-time bias adjustment is applied, making adjusted radar rainfall to be adequately good to apply for hydrological application.

• Journal of Korea Water Resources Association
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• v.45 no.5
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• pp.505-516
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• 2012

The study applies a hydrologic simulation model, HEC-1 developed by Hydrologic Engineering Center to Daecheong dam watershed for modeling hourly inflows of Daecheong dam. Although the HEC-1 model provides an automatic optimization technique for some of the parameters, the built-in optimization model is not sufficient in estimating reliable parameters. In particular, the optimization model often fails to estimate the parameters when a large number of parameters exist. In this regard, a main objective of this study is to develop Bayesian Markov Chain Monte Carlo simulation based HEC-1 model (BHEC-1). The Clark IUH method for transformation of precipitation excess to runoff and the soil conservation service runoff curve method for abstractions were used in Bayesian Monte Carlo simulation. Simulations of runoff at the Daecheong station in the HEC-1 model under Bayesian optimization scheme allow the posterior probability distributions of the hydrograph thus providing uncertainties in rainfall-runoff process. The proposed model showed a powerful performance in terms of estimating model parameters and deriving full uncertainties so that the model can be applied to various hydrologic problems such as frequency curve derivation, dam risk analysis and climate change study.

• Tunnel and Underground Space
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• v.16 no.4 s.63
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• pp.281-287
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• 2006

Intake of groundwater by tunneling in a mountainous area mostly results from groundwater flow through fractured parts of total rock mass. For reasonable analysis of this phenomenon the representative joint groups 1, 2, and 3 have been selected by previous investigations, geological/geophysical field tests and boring works. Three dimensional fractures were generated by the FracMan and MAFIC which is a three dimensional finite element model has been used to analyse a groundwater flow through fractured media. Monte Carlo simulation was applied to reduce the uncertainty of this study. The numerical results showed that the average and deviation of amounts of groundwater intaked into tunnel per unit length were $5.40{\times}10^{-1}$ and $3.04{\times}10^{-1}m^3/min/km$. It is concluded that tunnel would be stable on impact of groundwater environment by tunneling because of the lower value than $2.00{\sim}3.00m^3/min/km$ as previous and present standard on the application of tunnel construction.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.421-436
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• 2016

Public-Private-Partnerships tend to be committed high project development cost and recover the cost through future revenue during the operation period. In general, long-term concession can bring on more revenue to private investors, but short-term concession less revenue due to the short recovering opportunities. The concession period is usually determined by government in advance or by the private sectors's proposal although it is a very crucial factor for the PPPs. Accurate traffic forecasting should be most important in planing and evaluating the operation period in that the forecasted traffic determines the project revenue with user fees in PPPs. In this regards, governments and the private investors are required to consider the traffic forecast risk when determining concession period. This study proposed a model for the optimal concession period in the PPPs transportation projects. Monte Carlo simulation was performed to find out the optimal concession period while traffic forecast uncertainty is considered as a project risk under the expected return of the private sector. The simulation results showed that the optimal concession periods are 17 years and 21 years at 5.5% and 7% discount level, respectively. This study result can be applied for the private investors and/or any other concerned decision makers for PPPs projects to set up a more resonable concession period.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.1
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• pp.11-22
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• 2018

The safety of tunnels is quantified by quantitative risk assessment when planning the disaster prevention facilities of railway tunnels, and it is decided whether they are appropriate. The purpose of this study is to estimate the probability of the train stopping in the tunnels at train fire, which has a significant effect on the results of quantitative risk assessment for tunnel fires. For this purpose, a model was developed to calculate the coasting distance of the train considering the coefficient of train running resistance. The probability of stopping in case of train fire in the tunnel is predicted by the Monte Carlo simulation method with the coasting distance and the emergency braking distance as parameters of the tunnel lengths and slopes, train initial driving speeds. The kinetic equations for predicting the coasting distance were analyzed by reflecting the coefficient train running resistance of KTX II. In the case of KTX II trains, the coasting distance is reduced as the slope increases in a tunnel with an upward slope, but it is possible to continue driving without stopping in a slope downward. The probability of the train stopping in the case of train fire in tunnel decreases as the train speed increases and the slope of the tunnel decreases. If human error is not taken into account, the probability that a high-speed train traveling at a speed of 250 km/h or above will stop in a tunnel due to a fire is 0% when the slope of the tunnel is 0.5% or less, and the probability of stopping increases rapidly as the tunnel slope increases and the tunnel length increases.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.3 no.3
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• pp.159-165
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• 2005

The characterization of radiological contamination inside pipes generated during the decommission of a nuclear facility is necessary before pipes can be recycled or disposed. But, existing direct measurements of radioactive contamination level using the survey-meter can not estimate the characteristic of contamination on a local area such as the pipe inside. Moreover, the measurement of surface contamination level using the indirect methods has many problems of an application because of the difficulty of collecting sample and contamination possibility of a worker when collecting sample. In this work, plastic scintillator was simulated by using Monte Carlo simulation method for detection of beta radiation emitted from internal surfaces of small diameter pipe. Simulation results predicted the optimum thickness and geometry of plastic scintillator at which energy absorption for beta radiation was maximized. In addition, the problem of scintillator processing and transferring the detector into the pipe inside was considered when fabricating the plastic detector on the basis of simulation results. The characteristic of detector fabricated was also estimated. As a result, it was confirmed that detector capability was suitable for the measurement of contamination level. Also, the development of a detector for estimating the radiological characteristic of contamination on a local area such as the pipe inside was proven to be feasible.

• Korean Journal of Optics and Photonics
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• v.21 no.1
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• pp.26-32
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• 2010

Line lamps, which utilize leaky optical fibers based on periodic bending of plastic optical fibers, are proposed. The LED-optical fiber coupler, the key component of the line lamp, is designed and analyzed. The analysis by the Monte Carlo photon simulation method has shown that the optical coupling efficiency is affected rather sensitively by $\theta_w$, the slanting angle of the reflecting cup sidewall and $\rho_{ref}$, the reflectivity of the reflecting cup. The optical coupling efficiency of the coupler reaches the maximum when $\theta_w$ is about $60^{\circ}$, which is significantly larger than $\theta_w=45^{\circ}$, the typical sidewall slanting angle of the reflecting cup adopted in most LED lamps. When the reflectivity of the reflecting cup is above 0.8, the optical coupling efficiency is larger than 80%, which is the typical efficiency to be achieved in LD-optical fiber coupler.