• Title/Summary/Keyword: Monte Carlo modeling

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Bayesian Estimation of State-Space Model Using the Hybrid Monte Carlo within Gibbs Sampler

  • Park, Ilsu
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.203-210
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    • 2003
  • In a standard Metropolis-type Monte Carlo simulation, the proposal distribution cannot be easily adapted to "local dynamics" of the target distribution. To overcome some of these difficulties, Duane et al. (1987) introduced the method of hybrid Monte Carlo(HMC) which combines the basic idea of molecular dynamics and the Metropolis acceptance-rejection rule to produce Monte Carlo samples from a given target distribution. In this paper, using the HMC within Gibbs sampler, an asymptotical estimate of the smoothing mean and a general solution to state space modeling in Bayesian framework is obtaineds obtained.

MONTE CARLO DEPLETION UNDER LEAKAGE-CORRECTED CRITICAL SPECTRUM VIA ALBEDO SEARCH

  • Yun, Sung-Hwan;Cho, Nam-Zin
    • Nuclear Engineering and Technology
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    • v.42 no.3
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    • pp.271-278
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    • 2010
  • While the deterministic lattice physics/depletion codes use leakage-corrected critical spectrum (although approximate due to the B1 buckling search employed), Monte Carlo depletion codes currently in use do not have such a feature in spite of their heterogeneity and continuous-energy modeling capability. This paper describes an approach to Monte Carlo depletion with leakage-corrected critical spectrum derived from first principles. This is based on the concept of albedo eigenvalue treated as weight of the reflected neutron in Monte Carlo simulation.

Reliability Analysis for Structure Design of Automatic Ocean Salt Collector Using Sampling Method of Monte Carlo Simulation

  • Song, Chang Yong
    • Journal of Ocean Engineering and Technology
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    • v.34 no.5
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    • pp.316-324
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    • 2020
  • This paper presents comparative studies of reliability analysis and meta-modeling using the sampling method of Monte Carlo simulation for the structure design of an automatic ocean salt collector (AOSC). The thickness sizing variables of structure members are considered as random variables. Probabilistic performance functions are selected from strength performances evaluated via the finite element analysis of an AOSC. The sampling methods used in the comparative studies are simple random sampling and Sobol sequences with varied numbers of sampling. Approximation methods such as the Kriging model is applied to the meta-model generation. Reliability performances such as the probability failure and distribution are compared based on the variation of the sampling method of Monte Carlo simulation. The meta-modeling accuracy is evaluated for the Kriging model generated from the Monte Carlo simulation and Sobol sequence results. It is discovered that the Sobol sequence method is applicable to not only to the reliability analysis for the structural design of marine equipment such as the AOSC, but also to Kriging meta-modeling owing to its high numerical efficiency.

Photon Beam Commissioning for Monte Carlo Dose Calculation

  • Cho, Byung-Chul;Park, Hee-Chul;Hoonsik Bae
    • Proceedings of the Korean Society of Medical Physics Conference
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    • 2002.09a
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    • pp.106-108
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    • 2002
  • Recent advances in radiation transport algorithms, computer hardware performance, and parallel computing make the clinical use of Monte Carlo based dose calculations possible. Monte Carlo treatment planning requires accurate beam information as input to generate accurate dose distributions. The procedures to obtain this accurate beam information are called "commissioning", which includes accelerator head modeling. In this study, we would like to investigate how much accurately Monte Carlo based dose calculations can predict the measured beam data in various conditions. The Siemens 6MV photon beam and the BEAM Monte Carlo code were used. The comparisons including the percentage depth doses and off-axis profiles of open fields and wedges, output factors will be presented.

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Crack Analysis of Piezoelectric Material Considering Bounded Uncertain Material Properties

  • Kim, Tae-Uk;Shin, Jeong-Woo
    • International Journal of Aeronautical and Space Sciences
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    • v.4 no.2
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    • pp.9-16
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    • 2003
  • Piezoelectric materials are widely used to construct smart or adaptive structures. Although extensive efforts have been devoted to the analysis of piezoelectric materials in recent years, most researches have been conducted by assuming that the material properties are fixed and have no uncertainties. Intrinsically, material properties have a certain amount of scatter and such uncertainties can affect the performance of component. In this paper, the convex modeling is used to consider such uncertainties in calculating the crack extension force of piezoelectric material and the results are compared with the one obtained via the Monte Carlo simulation. Numerical results show that crack extension forces increase when uncertainties considered, which indicates that such uncertainties should not be ignored for reliable lifetime prediction. Also, the results obtained by the convex modeling and the Monte Carlo simulation show good agreement, which demonstrates the effectiveness of the convex modeling.

A Kinetic Monte Carlo Simulation of Individual Site Type of Ethylene and α-Olefins Polymerization

  • Zarand, S.M. Ghafelebashi;Shahsavar, S.;Jozaghkar, M.R.
    • Journal of the Korean Chemical Society
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    • v.62 no.3
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    • pp.191-202
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    • 2018
  • The aim of this work is to study Monte Carlo simulation of ethylene (co)polymerization over Ziegler-Natta catalyst as investigated by Chen et al. The results revealed that the Monte Carlo simulation was similar to sum square error (SSE) model to prediction of stage II and III of polymerization. In the case of activation stage (stage I) both model had slightly deviation from experimental results. The modeling results demonstrated that in homopolymerization, SSE was superior to predict polymerization rate in current stage while for copolymerization, Monte Carlo had preferable prediction. The Monte Carlo simulation approved the SSE results to determine role of each site in total polymerization rate and revealed that homopolymerization rate changed from site to site and order of center was different compared to copolymerization. The polymer yield was reduced by addition of hydrogen amount however there was no specific effect on uptake curve which was predicted by Monte Carlo simulation with good accuracy. In the case of copolymerization it was evolved that monomer chain length and monomer concentration influenced the rate of polymerization as rate of polymerization reduced from 1-hexene to 1-octene and increased when monomer concentration proliferate.

Monte Carlo Simulation of Densification during Liquid-Phase Sintering

  • Lee, Jae Wook
    • Journal of the Korean Ceramic Society
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    • v.53 no.3
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    • pp.288-294
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    • 2016
  • The densification process during liquid-phase sintering was simulated by Monte Carlo simulation. The Potts model, which had been applied to coarsening during liquid-phase sintering, was modified to include vapor particles. The results of two- and threedimensional simulations showed a temporal decrease in porosity, in other words, densification, and an increase in the average size of pores. The results also showed growth of solid grains and the effect of wetting angle on microstructure.

A Study of Neutronics Effects of the Spacer Grids in a Typical PWR via Monte Carlo Calculation

  • Tran, Xuan Bach;Cho, Nam Zin
    • Nuclear Engineering and Technology
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    • v.48 no.1
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    • pp.33-42
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    • 2016
  • Spacer grids play an important role in maintaining the proper form of the fuel assembly structure and ensuring the safety of reactor core design. This study applies the Monte Carlo method to the analysis of the neutronics effects of spacer grids in a typical pressurized water reactor (PWR). The core problem used to analyze the neutronics effects of spacer grids is a modified version of Korea Advanced Institute of Science and Technology benchmark problem 1B, based on an Advanced Power Reactor 1400 (APR1400) core model. The spacer grids are modeled and added to this test problem in various ways. Then, by running MCNP5 for all cases of spacer grid modeling, some important numerical results, such as the effective multiplication factor, the spatial distributions of neutron flux, and its energy spectrum are obtained. The numerical results of each case of spacer grid modeling are analyzed and compared to assess which type has more advantages in accuracy of numerical results and effectiveness in terms of geometry building. The conclusion is that the most realistic modeling for Monte Carlo calculation is the "volume-preserving" streamlined heterogeneous spacer grids, but the "banded" dissolution spacer grids modeling is a more practical yet accurate model for routine (deterministic) analysis.

Relative Power Density Distribution Calculations of the Kori Unit 1 Pressurized Water Reactor with Full-Scope Explicit Modeling of Monte Carlo Simulation

  • Kim, Jong-Oh;Kim, Jong-Kyung
    • Nuclear Engineering and Technology
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    • v.29 no.5
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    • pp.375-384
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    • 1997
  • Relative power density distributions of the Kori Unit 1 pressurized water reactor are calculated by Monte Carlo modeling with the MCNP code. The Kori Unit 1 core is modeled on a three-dimensional representation of the one-eighth of the reactor in-vessel component with reflective boundaries at 0 and 45 degrees. The axial core model is based on half core symmetry and is divided into four axial segments. Fission reaction density in each rod is calculated by following 100 cycles with 5,000 test neutrons in each cycle after starling with a localized neutron source and ten noncontributing settle cycles. Relative assembly power distributions are calculated from fission reaction densities of rods in assembly. After 100 cycle calculations, the system converges to a k value of 1.00039 $\geq$ 0.00084. Relative assembly power distribution is nearly the same with that of the Kori Unit 1 FSAR. Applicability of the full-scope Monte Carlo simulation in the power distribution calculation is examined by the relative root moan square error of 2.159%.

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