• Nuclear Engineering and Technology
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• v.50 no.7
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• pp.1043-1050
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• 2018

For an efficient Monte Carlo (MC) burnup analysis, an accurate high-order depletion scheme to consider the nonlinear flux variation in a coarse burnup-step interval is crucial accompanied with an accurate depletion equation solver. In a Seoul National University MC code, McCARD, the high-order depletion schemes of the quadratic depletion method (QDM) and the linear extrapolation/quadratic interpolation (LEQI) method and a depletion equation solver by the Chebyshev rational approximation method (CRAM) have been newly implemented in addition to the existing constant extrapolation/backward extrapolation (CEBE) method using the matrix exponential method (MEM) solver with substeps. In this paper, the quadratic extrapolation/quadratic interpolation (QEQI) method is proposed as a new high-order depletion scheme. In order to examine the effectiveness of the newly-implemented depletion modules in McCARD, four problems in the VERA depletion benchmarks are solved by CEBE/MEM, CEBE/CRAM, LEQI/MEM, QEQI/MEM, and QDM for gadolinium isotopes. From the comparisons, it is shown that the QEQI/MEM predicts ${k_{inf}}^{\prime}s$ most accurately among the test cases. In addition, statistical uncertainty propagation analyses for a VERA pin cell problem are conducted by the sensitivity and uncertainty and the stochastic sampling methods.

• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2748-2755
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• 2024

This paper presents two new methods for variance reduction for shielding calculation in Monte Carlo radiation transport. One method is CADIS-NEE, which combines Consistent Adjoint Driven Importance Sampling (CADIS) and next-event estimator (NEE) methods to increase the calculation efficiency of tallies at points. The other is CADIS-deterministic transport (DXTRAN), which combines CADIS and DXTRAN to obtain higher performance than using CADIS and DXTRAN separately. The combination processes are derived and implemented in the hybrid Monte-Carlo-Deterministic particle-transport code NECP-MCX. Various problems are tested to demonstrate the effectiveness of the two methods. According to the results, the two combination methods have higher efficiency than using CADIS, NEE or DXTRAN separately. In a long-distance photon-transport problem, CADIS-NEE converges faster than NEE and the figure of merit (FOM) of CADIS-NEE is 75.6 times of NEE. In a labyrinthine problem, CADIS-DXTRAN's FOM surpasses that of DXTRAN and CADIS by a factor of 45.3 and 17.7, respectively. Therefore, it is advisable to employ these two novel methods selectively in appropriate scenarios to reduce variance.

• 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.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.43-51
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• 1995

For the stress-strengh function, hierarchical Bayes estimations considered under squared error loss and entropy loss. In particular, the desired marginal postrior densities ate obtained via Gibbs sampler, an iterative Monte Carlo method, and Normal approximation (by Delta method). A simulation is presented.

• Nuclear Engineering and Technology
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• v.51 no.8
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• pp.2018-2025
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• 2019

This study systematically compared two hybrid deterministic/Monte Carlo transport codes, ADVANTG/MCNP and MAVRIC, in solving a difficult shielding problem for a real-world spent fuel storage cask. Both hybrid codes were developed based on the consistent adjoint driven importance sampling (CADIS) methodology but with different implementations. The dose rate distributions on the cask surface were of primary interest and their predicted results were compared with each other and with a straightforward MCNP calculation as a baseline case. Forward-Weighted CADIS was applied for optimization toward uniform statistical uncertainties for all tallies on the cask surface. Both ADVANTG/MCNP and MAVRIC achieved substantial improvements in overall computational efficiencies, especially for gamma-ray transport. Compared with the continuous-energy ADVANTG/MCNP calculations, the coarse-group MAVRIC calculations underestimated the neutron dose rates on the cask's side surface by an approximate factor of two and slightly overestimated the dose rates on the cask's top and side surfaces for fuel gamma and hardware gamma sources because of the impact of multigroup approximation. The fine-group MAVRIC calculations improved to a certain extent and the addition of continuous-energy treatment to the Monte Carlo code in the latest MAVRIC sequence greatly reduced these discrepancies. For the two continuous-energy calculations of ADVANTG/MCNP and MAVRIC, a remaining difference of approximately 30% between the neutron dose rates on the cask's side surface resulted from inconsistent use of thermal scattering treatment of hydrogen in concrete.

• Journal of Preventive Medicine and Public Health
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• v.30 no.3 s.58
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• pp.530-539
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• 1997

This study was conducted to assess the health risk on the volatile organic compounds such as toluene, xylene, and styrene in painting workplace. It was monitored through personal air sampling during working time in selected 5 workplaces and analysed using gas chromatography. For the settlement of exposure situation, there were regarded working conditions such as working hours, yearly working days, and working years. Also, Monte-Carlo simulation was used for the induction of hazard index using toxicity value from IRIS(Integrated risk information system) database. The results of risk assessment were summarized as follows. 1. The air concentration of toluene was $7.096{\pm}15,644ppm,\;2.586{\pm}4.275ppm\;for\;xylene,\;1.914{\pm}5.320ppm$ for styrene in blast painting workplaces. The level of toluene was different significantly compared with the level of xylene and styrene. 2. Computated chronic daily intake values of 95th percentile on toluene, xylene and styrene treated by Monte-Carlo simulation were 9.616, 3.567, 2.782 mg/kg/day, respectively. 3. Computated hazard index values of 75th percentile on toluene, xylene and styrene treated by Monte-Carlo simulation were 3.5, 1.0 and 1.6, respectively. Adverse health effects on the toluene, xylene and styrene would be expected by working exposure in selected 5 workplaces since the hazard indices of three compounds were exceeded 1 in the surroundings of 75th percentile though having the low emerged frequency.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.169-180
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• 1999

A Markov Chain Monte Carlo method with development of computation is used to be the software system reliability probability model. For Bayesian estimator considering computational problem and theoretical justification we studies relation Markov Chain with Gibbs sampling. Special case of GOS with Superposition for Goel-Okumoto and Weibull models using Gibbs sampling and Metropolis algorithm considered. In this paper discuss Bayesian computation and model selection using posterior predictive likelihood criterion. We consider in this paper data using method by Cox-Lewis. A numerical example with a simulated data set is given.

• Communications for Statistical Applications and Methods
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• v.20 no.6
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• pp.427-438
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• 2013

Based on progressive Type II censored sampling which is an important method to obtain failure data in a lifetime study, we suggest a very general form of Bayesian prediction bounds from two parameters exponentiated Weibull distribution using the proper general prior density. For this, Markov chain Monte Carlo approach is considered and we also provide a simulation study.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.2
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• pp.123-130
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• 2004

The automobile suspension system is composed of parts that affect performances of a vehicle such as ride quality, handling characteristics, straight performance and steering effort, etc. Moreover, by using the finite element analysis the cost for the initial design step can be decreased. In the design of a suspension system, usually system vibration and structural rigidity must be considered simultaneously to satisfy dynamic and static requirements simultaneously. In this paper, we consider the weight reduction and the increase of the first eigen-frequency of a suspension part, the upper control arm, especially using topology optimization and size optimization. Firstly, we obtain the initial design to maximize the first eigen-frequency using topology optimization. Then, we apply the multi-objective parameter optimization method to satisfy both the weight reduction and the increase of the first eigen-frequency. The design variables are varying during the optimization process for the multi-objective. Therefore, we can obtain the deterministic values of the design variables not only to satisfy the terms of variation limits but also to optimize the two design objectives at the same time. Finally, we have executed reliability based optimal design on the upper control arm using the Monte-Carlo method with importance sampling method for the optimal design result with 98％ reliability.

• Computational Structural Engineering
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• v.4 no.2
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• pp.111-117
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• 1991

The analysis method calculating the mean and standard deviation for the eigenvalue of complicated structures in which the limit state equation is implicitly expressed is formulated and applied to the buckling analysis by combining probabilistic finite element method with direct differential method which is a kind of sensitivity analysis technique. Also, the probability of buckling failure is calculated by combining classical reliability techniques such a MVFOSM and AFOSM. As random variables external load, elastic modulus, sectional moment of inertia and member length are chosen and Parkinson's iteration algorithm in AFOSM is used. The accuracy of the results by this study is verified by comparing the results with the crude Monte Carlo simulation and Importance Sampling Method. Through the case study of some structures the important aspects of buckling reliability analysis are discussed.