• Title/Summary/Keyword: Monte Carlo 모의기법

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A Study on the Simulation and the Measurement of 6 MeV electron Beam (6 MeV 전자선의 측정과 모의계산에 대한 연구)

  • Lee Sung Ah;Lee Jeong Ok;Moon Sun Rock;Won Jong Jin;Kang Jeong Ku;Kim Seung Kon
    • Radiation Oncology Journal
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    • v.13 no.3
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    • pp.285-289
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    • 1995
  • Purpose : We compared the calcualted percent depth dose curves of 6 MeV electron beam to that of measured to evaluate the usefulness of Monte-carlo simulation method in radiation physics. Materials and Methods : The radiation dose values of 6 MeV electron beam using EGS4 code with one million histories in water were compared values that were measured from the depth dose curve of electron beam irradiated by medical accelerator ML6M. The central axis dose values were calculated according to the changing field size. such as $5{\times}5,\;10{\times}10,\;15{\times}15,\;20{\times}20cm^2$. Results : The value calculated showed a very similar shape to depth dose curve. The calculated and measured value of $D_max$ at $10{\times}10cm^2$ cone is 15mm and 14mm respectively. The calculated value of the surface radiation dose rate is $65.52\%$ and measured one is $76.94\%$. The surface radiation dose rate has varied from $64.43\%$ to $66.99\%$. The calculated values of $D_max$ are in the range between 15mm and 18mm. The calculated value was fitted well with measured value around the $D_max$ area, excluding build up range and below the $90\%$ depth dose area. Conclusion : This result suggested that the calculation of dose value can be replace the direct measurement of the dose for radiation therapy. Also, EGS4 may be a very convenient program to assess the effect of radiation dose using by personal computers.

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A Study on Regionalization of Parameters for Sacramento Continuous Rainfall-Runoff Model Using Watershed Characteristics (유역특성인자를 활용한 Sacramento 장기유출모형의 매개변수 지역화 기법 연구)

  • Kim, Tae-Jeong;Jeong, Ga-In;Kim, Ki-Young;Kwon, Hyun-Han
    • Journal of Korea Water Resources Association
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    • v.48 no.10
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    • pp.793-806
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    • 2015
  • The simulation of natural streamflow at ungauged basins is one of the fundamental challenges in hydrology community. The key to runoff simulation in ungauged basins is generally involved with a reliable parameter estimation in a rainfall-runoff model. However, the parameter estimation of the rainfall-runoff model is a complex issue due to an insufficient hydrologic data. This study aims to regionalize the parameters of a continuous rainfall-runoff model in conjunction with a Bayesian statistical technique to consider uncertainty more precisely associated with the parameters. First, this study employed Bayesian Markov Chain Monte Carlo scheme for the estimation of the Sacramento rainfall-runoff model. The Sacramento model is calibrated against observed daily runoff data, and finally, the posterior density function of the parameters is derived. Second, we applied a multiple linear regression model to the set of the parameters with watershed characteristics, to obtain a functional relationship between pairs of variables. The proposed model was also validated with gauged watersheds in accordance with the efficiency criteria such as the Nash-Sutcliffe efficiency, index of agreement and the coefficient of correlation.

Ensemble Daily Streamflow Forecast Using Two-step Daily Precipitation Interpolation (일강우 내삽을 이용한 일유량 시뮬레이션 및 앙상블 유량 발생)

  • Hwang, Yeon-Sang;Heo, Jun-Haeng;Jung, Young-Hun
    • Journal of Korea Water Resources Association
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    • v.44 no.3
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    • pp.209-220
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    • 2011
  • Input uncertainty is one of the major sources of uncertainty in hydrologic modeling. In this paper, first, three alternate rainfall inputs generated by different interpolation schemes were used to see the impact on a distributed watershed model. Later, the residuals of precipitation interpolations were tested as a source of ensemble streamflow generation in two river basins in the U.S. Using the Monte Carlo parameter search, the relationship between input and parameter uncertainty was also categorized to see sensitivity of the parameters to input differences. This analysis is useful not only to find the parameters that need more attention but also to transfer parameters calibrated for station measurement to the simulation using different inputs such as downscaled data from weather generator outputs. Input ensembles that preserves local statistical characteristics are used to generate streamflow ensembles hindcast, and showed that the ensemble sets are capturing the observed steamflow properly. This procedure is especially important to consider input uncertainties in the simulation of streamflow forecast.

Variability Analysis of Design Flood Considering Uncertainty of Rainfall-Runoff Model and Climate Change (기후변화 영향과 강우-유출 모형의 불확실성을 고려한 설계홍수량 변동성 분석)

  • Kwon, Hyun-Han;Kim, Jang-Gyeong;Lee, Jong-Seok
    • Proceedings of the Korea Water Resources Association Conference
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    • 2012.05a
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    • pp.365-365
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    • 2012
  • 이수 및 치수를 위한 수공구조물 설계 및 하천기본계획 수립의 요점은 설계홍수량의 산정에 있으며, 통계적으로 유의성을 가지는 설계홍수량을 산정하기 위해서는 일반적으로 30년 이상 관측된 홍수자료가 요구된다. 우리나라의 경우 대부분의 유역이 미계측 유역이거나 관측년수가 비교적 작은 경우가 많으므로, 상대적으로 자료 연한이 긴 강우자료를 빈도분석한 후 이를 강우-유출 모형에 입력하여 확률홍수량을 추정하는 간접적인 방법이 주로 이용되며 사용된 강우의 빈도가 홍수의 빈도와 동일하다는 가정을 기본으로 한다. 그러나 동일한 강우량이 발생하더라도 강우의 강도, 지속시간, 유역의 선행함수조건 등과 같은 유역 특성에 따라 유출의 특성은 현저히 다르게 나타나며 결국 이러한 특성은 입력자료, 강우-유출 모형, 기후변동성 등과 같은 불확실성 요소로 인식될 수 있다. 따라서 본 연구에서는 이러한 불확실성을 고려할 수 있는 강우-유출 모의기법을 개발하여 이를 통해 홍수빈도곡선을 유도할 수 있는 방법론을 제시하고자 한다. 불확실성 분석을 위해 기존 HEC-1 강우-유출 모형에서 Bayesian MCMC 기법을 적용하여 매개변수들의 사후분포를 추정하여 매개변수들의 최적화 및 불확실성 분석을 수행하였다. 마지막으로 기후변화 영향을 통합한 홍수빈도곡선을 유도하기 위해서 극치강수를 모의하는 것이 필요하며, 본 연구에서는 극치값 재현에 있어서 우수한 성능을 발휘하는 Kernel-Pareto Piecewise분포 기반의 강우모의발생 기법을 적용하여 HEC-1모형과 연동되도록 모형을 개발하였다. 본 연구에서 제안하는 방법론은 기존 홍수빈도곡선 유도 방법에서 불확실성을 분석하기 위해 모든 변수들을 독립사상으로 간주하고 Monte Carlo Simulation을 수행함으로서 매개변수들간의 상호연관성, 상관성, 조건부 확률들을 고려할 수 없었던 점을 Bayesian 모형을 통해 매개변수들간의 조건부 확률을 고려한 매개변수의 사후분포 도출을 가능하게 하여 보다 현실적인 강우-유출 관계 도출이 가능하고 불확실성 구간이 자연적으로 도출됨으로서 향후, 신뢰성 있는 수자원 계획수립에 유용한 자료로 활용이 가능할 것으로 판단된다.

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A Development of Regional Frequency Model Based on Hierarchical Bayesian Model (계층적 Bayesian 모형 기반 지역빈도해석 모형 개발)

  • Kwon, Hyun-Han;Kim, Jin-Young;Kim, Oon-Ki;Lee, Jeong-Ju
    • Journal of Korea Water Resources Association
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    • v.46 no.1
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    • pp.13-24
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    • 2013
  • The main objective of this study was to develop a new regional frequency analysis model based on hierarchical Bayesian model that allows us to better estimate and quantify model parameters as well as their associated uncertainties. A Monte-carlo experiment procedure has been set up to verify the proposed regional frequency analysis. It was found that the proposed hierarchical Bayesian model based regional frequency analysis outperformed the existing L-moment based regional frequency analysis in terms of reducing biases associated with the model parameters. Especially, the bias is remarkably decreased with increasing return period. The proposed model was applied to six weather stations in Jeollabuk-do, and compared with the existing L-moment approach. This study also provided shrinkage process of the model parameters that is a typical behavior in hierarchical Bayes models. The results of case study show that the proposed model has the potential to obtain reliable estimates of the parameters and quantitatively provide their uncertainties.

A Listening Angle Estimation Scheme based on Received Signal Power Differences in Indoor Environment (실내에서 음향신호의 RSPD를 이용한 청음각 추정 기법)

  • Lee, Eui-Hyoung;Yoo, Seung-Soo;Yoon, Eun-Chul;Kim, Sun-Yong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.12C
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    • pp.1035-1043
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    • 2010
  • This paper presents a listening angle estimation scheme based on received signal power difference (RSPD) using acoustic signals, and analyzes the performance of the proposed scheme. The RSPD as the measurement to estimate the listening angle is considered for the first time in this paper. We mathematically analyze the error characteristics of the proposed scheme and present the characteristics of the proposed scheme through the Monte-Carlo simulation. We also conduct actual experiments in an anechoic room to evaluate the performance of the proposed scheme to compare with the conventional scheme.

On a robust analysis of variance based on winsorization (윈저화를 이용한 로버스트 분산분석)

  • 성내경
    • The Korean Journal of Applied Statistics
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    • v.8 no.1
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    • pp.119-131
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    • 1995
  • Based on Monte-Carlo simulation results we propose a robust analysis of variance procedure by utilizing trimmed mean and Winsorized variance. We deal with mainly the one-way classification case. We evaluate the empirical distribution of a pseudo-F statistic based on symmetrically Winsorized sum of squares when the population is normally distributed.

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On the behavior od Winsorized $x^2$ (윈저화 $x^2$의 양태에 대하여)

  • 성내경
    • The Korean Journal of Applied Statistics
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    • v.7 no.2
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    • pp.1-7
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    • 1994
  • Using a Monte-Carlo simulation technique we evaluate the empiricla distribution of a pseudo-chi-square statistic based on symmetrically Winsorized sum of squares when the population is normally distributed, and search for a chi-square distribution with appropriate degrees of freedom which can be referred to an approximate distribution for Winsorized chi-square.

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Development of Simulation Model for Diffusion of Oil Spill in the Ocean (II) - Application of Simulation model to the Field (해양유출기름의 확산 시뮬레이션 모델 개발(II) - 유류확산모델의 현장 적용)

  • 김기철;이중우;강신영;도덕희
    • Journal of Korean Port Research
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    • v.13 no.2
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    • pp.427-436
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    • 1999
  • Simulation model for diffusion of oil spill is developed. The model can perform real time simulation in the case of oil spill accident in the ocean. The model consists of three dimensional ocean circulation model and model for diffusion of oil spill. Real time flow fields which are used in the calculation of advection of oil spill are obtained in the three dimensional ocean circulation model. The model for diffusion of oil spill includes the evaporation dissolution emulsification and downward diffusion. For the verification of the model it is applied to the oil spill from the accident of Sea Prince. The results shows good agreement.

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A Generalized Advanced Region Correlation (G-ARC) Scheme for BOC(pn,n) Modulated Code Tracking in GNSS (BOC(pn,n) 변조된 확산신호의 부호동기추적을 위한 일반화된 이른영역상관기법)

  • Yoo, Seung-Soo;Lee, Young-Yoon;Kim, Yeong-Moon;Yoon, Seok-Ho;Kim, Sun-Yong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.3C
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    • pp.329-340
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    • 2009
  • This paper proposes a novel code tracking scheme to track the fine code synchronization for BOC(pn,n) modulated spreading signals. The correlation function of BOC(pn,n) modulated spreading signals has been several peaks. In this paper, we observe that the correlation function in the advanced offset region remains almost unchanged, due to the multipath signals being received later than a line-of-sight signal. Based on this observation, we propose a novel code tracking scheme which is called the advanced region correlation (ARC) method for BOC(n,n) modulated spreading signals. And, we compare with the code tracking accuracy between the conventional and proposed methods in the static multipath and land mobile satellite system channels through the Monte-Carlo simulation. Then, base on the proposed scheme, we propose the generalized-ARC (ARC) scheme for BOC(pn, n) modulated spreading signals.