• Title/Summary/Keyword: Monte Carlo model

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The Precision of Lead Frame Etching Characteristics Using Monte-Carlo Simulations

  • Jeong, Heung-Cheol;Choi, Gyung-Min;Kim, Duck-Jool
    • International Journal of Precision Engineering and Manufacturing
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    • v.8 no.1
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    • pp.73-78
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    • 2007
  • The objective of this work was to simulate lead frame etching characteristics to optimize the etching process, Characteristics such as the etching factor and uniformity were investigated for different actual operating conditions, including pressure, distance from the nozzle tip, pipe pitch, and feed speed. The correlation between the etching and spray characteristics was analyzed to develop the etching model. Spray characteristics obtained from an experiment using a phase Doppler anemometer system were then simulated using a Monte-Carlo technique, The etching process model was coded in the Java language, The spray and etching characteristics were correlated with each other and simulated results agreed well with the measured data for a lead frame etching process, The optimal operating parameters under various conditions were successfully determined.

On the Bayesian Statistical Inference (베이지안 통계 추론)

  • Lee, Ho-Suk
    • Proceedings of the Korean Information Science Society Conference
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    • 2007.06c
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    • pp.263-266
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    • 2007
  • This paper discusses the Bayesian statistical inference. This paper discusses the Bayesian inference, MCMC (Markov Chain Monte Carlo) integration, MCMC method, Metropolis-Hastings algorithm, Gibbs sampling, Maximum likelihood estimation, Expectation Maximization algorithm, missing data processing, and BMA (Bayesian Model Averaging). The Bayesian statistical inference is used to process a large amount of data in the areas of biology, medicine, bioengineering, science and engineering, and general data analysis and processing, and provides the important method to draw the optimal inference result. Lastly, this paper discusses the method of principal component analysis. The PCA method is also used for data analysis and inference.

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The first application of modified neutron source multiplication method in subcriticality monitoring based on Monte Carlo

  • Wang, Wencong;Liu, Caixue;Huang, Liyuan
    • Nuclear Engineering and Technology
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    • v.52 no.3
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    • pp.477-484
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    • 2020
  • The control rod drive mechanism needs to be debugged after reactor fresh fuel loading. It is of great importance to monitor the subcriticality of this process accurately. A modified method was applied to the subcriticality monitoring process, in which only a single control rod cluster was fully withdrawn from the core. In order to correct the error in the results obtained by Neutron Source Multiplication Method, which is based on one point reactor model, Monte Carlo neutron transport code was employed to calculate the fission neutron distribution, the iterated fission probability and the neutron flux in the neutron detector. This article analyzed the effect of a coarse mesh and a fine mesh to tally fission neutron distributions, the iterated fission probability distributions and to calculate correction factors. The subcriticality before and after modification is compared with the subcriticality calculated by MCNP code. The modified results turn out to be closer to calculation. It's feasible to implement the modified NSM method in large local reactivity addition process using Monte Carlo code based on 3D model.

Probabilistic Analysis of Reinforced Concrete Beam and Slab Deflections Using Monte Carlo Simulation

  • Choi, Bong-Seob;Kwon, Young-Wung
    • KCI Concrete Journal
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    • v.12 no.2
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    • pp.11-21
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    • 2000
  • It is not easy to correctly predict deflections of reinforced concrete beams and one-way slabs due to the variability of parameters involved in the calculation of deflections. Monte Carlo simulation is used to assess the variability of deflections with known statistical data and probability distributions of variables. A deterministic deflection value is obtained using the layered beam model based on the finite element approach in which a finite element is divided into a number of layers over the depth. The model takes into account nonlinear effects such as cracking, creep and shrinkage. Statistical parameters were obtained from the literature. For the assessment of variability of deflections, 12 cases of one-way slabs and T-beams are designed on the basis of ultimate moment capacity. Several results of a probabilistic study are presented to indicate general trends indicated by results and demonstrate the effect of certain design parameters on the variability of deflections. From simulation results, the variability of deflections relies primarily on the ratio of applied moment to cracking moment and the corre-sponding reinforcement ratio.

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Use of Markov Chain Monte Carlo in Estimating the Economy Model

  • Lee, Seung Moon
    • Journal of Integrative Natural Science
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    • v.1 no.2
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    • pp.127-132
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    • 2008
  • This project follows the heterogeneous agent market segmented model of Landon-Lane and Occhino (2007) with using Korean data, M1 and GDP deflator from 1882:I to 2007:II. This paper estimates parameters with Monte Carlo Markov Chain. The fraction of traders, ${\lambda}$, in Korea is 15.64%. The quarterly preferences discount factor's, ${\beta}$, posterior mean is 0.9922. The posterior mean of the inverse of the elasticity of the labor supply to the real wage, ${\varphi}$, is 0.0316. The elasticity of the labor supply to the real wage has a very large value. By Hansen (1985) and Christiano and Eichenbaum (1992) and Cooley and Hansen (1989), models having large elasticity of the aggregate labor supply better match macroeconomic data.

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Three-dimensional monte carlo modeling and simulation of ion implantation process: an efficient virtual trajectory split approach (3차원 몬테 카를로 이온 주입 공정 모델링 및 시뮬레이션: 효율적인 가상 궤적 발생 알고리듬)

  • 손명식;황호정
    • Journal of the Korean Institute of Telematics and Electronics D
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    • v.35D no.3
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    • pp.28-38
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    • 1998
  • In our paper is reported a new 3D(dimensional) trajectory split approach with greatly improved efficiency for the Monte Carlo simulation of the 3D profiles of implanted ionand point defect concentrations in single-crystal silicon. This approach has been successfully implemented in our TRICSI Monte Carlo code. Combined with the previously developed model for damage accumalation in our TRICSI code, this model allows phasically based dynamic simulation of 3D profiles over an subsequent process simulation such as diffusion modeling and simulation. A typical time saving of over 10 timeshas been achieved for 3D simulation. Our method ensures much better region aground the implanted area. For 1-D simulation, the optimized condition for trajectory split has set to 3,000 pseudoparticles with 2 split branches.

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Direct tracking of noncircular sources for multiple arrays via improved unscented particle filter method

  • Yang Qian;Xinlei Shi;Haowei Zeng;Mushtaq Ahmad
    • ETRI Journal
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    • v.45 no.3
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    • pp.394-403
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    • 2023
  • Direct tracking problem of moving noncircular sources for multiple arrays is investigated in this study. Here, we propose an improved unscented particle filter (I-UPF) direct tracking method, which combines system proportional symmetry unscented particle filter and Markov Chain Monte Carlo (MCMC) algorithm. Noncircular sources can extend the dimension of sources matrix, and the direct tracking accuracy is improved. This method uses multiple arrays to receive sources. Firstly, set up a direct tracking model through consecutive time and Doppler information. Subsequently, based on the improved unscented particle filter algorithm, the proposed tracking model is to improve the direct tracking accuracy and reduce computational complexity. Simulation results show that the proposed improved unscented particle filter algorithm for noncircular sources has enhanced tracking accuracy than Markov Chain Monte Carlo unscented particle filter algorithm, Markov Chain Monte Carlo extended Kalman particle filter, and two-step tracking method.

Estimation of Flash Flood Guidance considering Uncertainty of Rainfall-Runoff Model (강우-유출 모형의 불확실성을 고려한 돌발홍수기준)

  • Lee, Keon-Haeng;Kim, Hung-Soo;Kim, Soo-Jun;Kim, Byung-Sik
    • Journal of Wetlands Research
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    • v.12 no.3
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    • pp.155-163
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    • 2010
  • The flash flood is characterized as flood leading to damage by heavy rainfall occurred in steep slope and impervious area with short duration. Flash flood occurs when rainfall exceeds Flash Flood Guidance(FFG). So, the accurate estimation of FFG will be helpful in flash flood forecasting and warning system. Say, if we can reduce the uncertainty of rainfall-runoff relationship, FFG can be estimated more accurately. However, since the rainfall-runoff models have their own parameter characteristics, the uncertainty of FFG will depend upon the selection of rainfall-runoff model. This study used four rainfall-runoff models of HEC-HMS model, Storage Function model, SSARR model and TANK model for the estimation of models' uncertainties by using Monte Carlo simulation. Then, we derived the confidence limits of rainfall-runoff relationship by four models on 95%-confidence level.

Response of an Elastic Pendulum under Random Excitations (불규칙 가진을 받는 탄성진자의 응답 해석)

  • Lee, Sin-Young
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.18 no.2
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    • pp.187-193
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    • 2009
  • Dynamic response of an elastic pendulum system under random excitations was studied by using the Lagrangian equations of motion which uses the kinetic and potential energy of a target system. The responses of random excitations were calculated by using Monte Carl simulation which uses the series of random numbers. The procedure of Monte Carlo simulation is generation of random numbers, system model, system output, and statistical management of output. When the levels of random excitations were changed, the expected responses of the pendulum system showed various responses.

Hydraulic Model for Real Time Forecasting of Inundation Risk (실시간 범람위험도 예측을 위한 수리학적 모형의 개발)

  • Han, Geon-Yeon;Son, In-Ho;Lee, Jae-Yeong
    • Journal of Korea Water Resources Association
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    • v.33 no.3
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    • pp.331-340
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    • 2000
  • This study aims to develop a methodology of real time forecasting of mundation risk based on DAMBRK model and Kalman filter. The model is based on implicit, nonlinear finite difference approximatIons of the one-dimensional dynamic wave equations. The stochastic estimator uses on extended Kalman filter to provide optimal updating estimates. These are accomplished by combining the predictions of the determurustic model with real time observauons modified by the Kalman filter gain ractor. Inundation risks are also estimated by applying Monte Carlo simulation to consider the variability in cross section geometry and Manning's roughness coefficient. The model calibrated by applying to the floods ot South Han River on September, 1990 and August, 1995. The Kalman tilter model indicates that significant improvement compared to deteriministic analysis in flood routing predictions in the river. Overtopping risk of levee is also presented by comparing levee height with simulated flood level. level.

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