• Title/Summary/Keyword: monte carlo evaluation

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An Efficient Simulation of Discrete Time Queueing Systems with Markov-modulated Arrival Processes (MMAP 이산시간 큐잉 시스템의 속산 시뮬레이션)

  • Kook Kwang-Ho;Kang Sungyeol
    • Journal of the Korea Society for Simulation
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    • v.13 no.3
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    • pp.1-10
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    • 2004
  • The cell loss probability required in the ATM network is in the range of 10$^{-9}$ ∼10$^{-12}$ . If Monte Carlo simulation is used to analyze the performance of the ATM node, an enormous amount of computer time is required. To obtain large speed-up factors, importance sampling may be used. Since the Markov-modulated processes have been used to model various high-speed network traffic sources, we consider discrete time single server queueing systems with Markov-modulated arrival processes which can be used to model an ATM node. We apply importance sampling based on the Large Deviation Theory for the performance evaluation of, MMBP/D/1/K, ∑MMBP/D/1/K, and two stage tandem queueing networks with Markov-modulated arrival processes and deterministic service times. The simulation results show that the buffer overflow probabilities obtained by the importance sampling are very close to those obtained by the Monte Carlo simulation and the computer time can be reduced drastically.

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Uncertainty Evaluation of Dynamic Pressure Calibrator by Monte Carlo Simulation (몬테카를로 모사를 이용한 동압력 교정기 불확도 평가)

  • Kim, Moon-Ki
    • Journal of the Korea Institute of Military Science and Technology
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    • v.13 no.4
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    • pp.665-672
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    • 2010
  • This paper describes Monte Carlo Simulation(MCS) to assess the uncertainty of dynamic pressure calibrator and the expanded uncertainty results that were compared by GUM approximation and MCS. MCS uncertainties were computed using defining a domain of possible inputs, generating inputs randomly using probability distribution, performing a deterministic computation repeatedly and aggregating the results. It was revealed that the expanded uncertainty between GUM and MCS was different from each other. the expanded uncertainties were 0.5366%, 0.4856%, respectively. MCS is a suitable method for determining the uncertainty of simple and complex measurement systems. It should be more widely used and studied in measurement uncertainty calculations.

FURTHER EVALUATION OF A STOCHASTIC MODEL APPLIED TO MONOENERGETIC SPACE-TIME NUCLEAR REACTOR KINETICS

  • Ha, Pham Nhu Viet;Kim, Jong-Kyung
    • Nuclear Engineering and Technology
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    • v.43 no.6
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    • pp.523-530
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    • 2011
  • In a previous study, the stochastic space-dependent kinetics model (SSKM) based on the forward stochastic model in stochastic kinetics theory and the Ito stochastic differential equations was proposed for treating monoenergetic space-time nuclear reactor kinetics in one dimension. The SSKM was tested against analog Monte Carlo calculations, however, for exemplary cases of homogeneous slab reactors with only one delayed-neutron precursor group. In this paper, the SSKM is improved and evaluated with more realistic and complicated cases regarding several delayed-neutron precursor groups and heterogeneous slab reactors in which the extraneous source or reactivity can be introduced locally. Furthermore, the source level and the initial conditions will also be adjusted to investigate the trends in the variances of the neutron population and fission product levels across the reactor. The results indicate that the improved SSKM is in good agreement with the Monte Carlo method and show how the variances in population dynamics can be controlled.

Region-wise evaluation of gamma-ray exposure dose in decontamination operation after a nuclear accident

  • Jeong, Hae Sun;Hwang, Won Tae;Han, Moon Hee;Kim, Eun Han;Lee, Jo Eun;Lee, Cheol Woo
    • Nuclear Engineering and Technology
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    • v.53 no.8
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    • pp.2652-2660
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    • 2021
  • The gamma-ray exposure doses in decontamination operation after a nuclear accident were evaluated with a consideration of various geometrical conditions and specific gamma-ray energies. The calculation domain is organized with three residence types and each form is divided into two kinds of geometrical arrangements. The position-wise air KERMA values were calculated with an assumption of evenly distributed gamma-ray source based on Monte Carlo radiation transport analysis using the MCNP code. The radioactivity is initially set to be unity to be multiplied by the deposition value measured in the actual accident condition. The workforce data set depending on the target object was determined by modifying the Fukushima report. The external exposure doses for decontamination workers were derived from the calculated KERMA values and the workforce analysis. These results can be used to efficiently determine the workforce required by the characteristics of the area and the structure to be decontaminated within the dose limits.

A Study on the Risk Assessment of Small Reservoirs using Reliability Analysis Methods (신뢰도 분석기법을 이용한 소규모 저수지의 위험도 분석)

  • Kim, Mun-Mo;Park, Chang-Eon
    • Journal of Korea Water Resources Association
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    • v.33 no.1
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    • pp.15-30
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    • 2000
  • This study is to develop the applied method of reliability analysis to present risk - initial water level relationship in the small reservoir. To determine the reliability, the grasping of uncertainty sources is prerequisited and performance function is formulated. Reliability analysis method is a statistical method and the basic procedure of risk evaluation for overtopping of reservoir is as follows. 1. Define the risk criterion and performance function for the overtopping. 2. Determine the uncertainties of all the variables in the performance function. 3. Perform the risk analysis with suitable risk calculation method. Reliability analysis method such as Monte Carlo simulation(MCS) method and mean value first order second moment(MVFOSM) method are used to calculate the risk for reservoir. Finally, risk - initial water level relationship is established according to return period and it is useful for reservoir operation and safety assessment.ssment.

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Bayesian Estimation of Multinomial and Poisson Parameters Under Starshaped Restriction

  • Oh, Myong-Sik
    • Communications for Statistical Applications and Methods
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    • v.4 no.1
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    • pp.185-191
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    • 1997
  • Bayesian estimation of multinomial and Poisson parameters under starshped restriction is considered. Most Bayesian estimations in order restricted statistical inference require the high-dimensional integration which is very difficult to evaluate. Monte Carlo integration and Gibbs sampling are among alternative methods. The Bayesian estimation considered in this paper requires only evaluation of incomplete beta functions which are extensively tabulated.

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The Effects of the Statistical Uncertainties in Monte Carlo Photon Dose Calculation for the Radiation Therapy (방사선 치료를 위한 몬테칼로 광자선 선량계산 시 통계적 불확실성 영향 평가)

  • Cheong, Kwang-Ho;Suh, Tae-Suk;Cho, Byung-Chul
    • Journal of Radiation Protection and Research
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    • v.29 no.2
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    • pp.105-115
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    • 2004
  • The Monte Carlo simulation requires very much time to obtain a result of acceptable accuracy. Therefore we should know the optimum number of history not to sacrifice time as well as the accuracy. In this study, we have investigated the effects of statistical uncertainties of the photon dose calculation. BEAMnrc and DOSXYZnrc systems were used for the Monte Carlo dose calculation and the case of mediastinum was simulated. The several dose calculation result from various number of histories had been obtained and analyzed using the criteria of isodose curve comparison, dose volume histogram comparison(DVH) and root mean-square differences(RMSD). Statistical uncertainties were observed most evidently in isodose curve comparison and RMSD while DVHs were less sensitive. The acceptable uncertainties $(\bar{{\Delta}D})$ of the Monte Carlo photon dose calculation for the radiation therapy were estimated within total 9% error or 1% error for over than $D_{max}/2$ voxels or voxels at maximum dose.

Evaluation of Ventilation Deficiecy in Elementary, Middle, and High Schools using Monte Carlo Simulation (Monte-Carlo 모의실험을 이용한 초·중·고등학교의 환기부족 평가)

  • Choe, Youngtae;Park, Jinhyeon;Kim, Eunchae;Ryu, Hyoensu;Kim, Dong Jun;Min, Kihong;Jung, Dayoung;Woo, Byung Lyul;Cho, Mansu;Yang, Wonho
    • Journal of Environmental Health Sciences
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    • v.46 no.6
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    • pp.627-635
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    • 2020
  • Objectives: Indoor air quality has become more important aspeople spend most of their times indoors. Since students spend most of their times at home or at school, they are more likely to be exposed to indoor air pollutants. Ventilation in school classrooms can affect health and learning performance. In this study, ventilation deficiency was evaluated in school classrooms using Monte Carlo simulation. Methods: This study used sensor-based monitoring for six months to measure carbon dioxide (CO2) concentrations in classrooms in elementary, middle, and high schools. The volume of the classroom and the number of students were investigated, and the students' body surface area was used to calculate the CO2 emission rate. The distribution of ventilation rates was estimated by measured CO2 concentration and a mass-balance model using Monte Carlo simulation. Results: In the elementary, middle, and high schools, the average CO2 concentrations exceeded 1000 ppm, indicating that the ventilation rates were insufficient. The ventilation rates were deficient from July to August and in December, but showed relatively high ventilation rates in October. Forty-three percent of elementary schools, 56% of middle schools, and 62% of high schools showed insufficient ventilation rates. Conclusions: The ventilation rates calculated in elementary, middle and high schools were found to be quite insufficient. Therefore, proper management is needed to overcome the lack of ventilation and improve air quality.

Development of river discharge estimation scheme using Monte Carlo simulation and 1D numerical analysis model (Monte Carlo 모의 및 수치해석 모형을 활용한 하천 유량 추정기법의 개발)

  • Kang, Hansol;An, Hyunuk;Kim, Yeonsu;Hur, Youngteck;Noh, Joonwoo
    • Journal of Korea Water Resources Association
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    • v.55 no.4
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    • pp.279-289
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    • 2022
  • Since the frequency of heavy rainfall is increasing due to climate change, water levels in the river exceed past historical records. The rating-curve is to convert water level into flow dicscharge from the regression analysis of the water level and corresponding flow discharges. However, the rating-curve involves many uncertainties because of the limited data especially when observed water level exceed past historical water levels. In order to compensate for insufficient data and increase the accuracy of flow discharge data, this study estimates the flow discharge in the river computed mathematically using Monte Carlo simulation based on a 1D hydrodynamic numerical model. Based on the existing rating curve, a random combination of coefficients constituting the rating-curve creates a number of virtual rating curve. From the computed results of the hydrodynamic model, it is possible to estimate flow discharge which reproduces best fit to the observed water level. Based on the statistical evaluation of these samples, a method for mathematically estimating the water level and flow discharge of all cross sections is porposed. The proposed methodology is applied to the junction of Yochoen Stream in the Seomjin River. As a result, it is confirmed that the water level reproducibility was greatly improved. Also, the water level and flow discharge can be calculated mathematically when the proposed method is applied.

Probabilistic Method for The Harmonic Analysis of Railroad Feeding System (철도급전시스템의 고조파 평가를 위한 확률론적 방법)

  • Lee, Seung-Hyuk;Song, Hak-Seon;Lee, Jun-Kyong;Kim, Jin-O
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.55 no.9
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    • pp.384-391
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    • 2006
  • The harmonic currents generated along with the operating speed of electrical railroad traction are very difficult to analyze because of its nonlinear characteristics. This paper therefore presents probabilistic approach for the evaluation of harmonic currents about the operating speed of the arbitrary single traction. To use probabilistic method for railroad system, PDF(Probability Density Function) using measuring data based on the realistic h 따 monic currents per operating speed is calculated. Measuring data of harmonic current per operating speed is obtained using the result data of PSCAD/EMTDC dynamic simulation based on an IAT(Intra Airport Transit) in Incheon International Airport. The means(expected values) and variances of harmonic currents of single traction also are obtained by the PDF of the operating traction speed and harmonic currents. The uncertainty of harmonic currents can be calculated through the mean and variance of PDF. The probability of harmonic currents generated with the operating of arbitrary many tractions is calculated by the convolution of functions. The harmonics of different number of tractions are systematically investigated to assess the TDD(Total Demand Distortion) for the railroad system. The calculation of TDD was carried out using Monte-Carlo Simulations(MSCs) and the results of TDD evaluation of the power quality in the IAT power feeding system.