• Nuclear Engineering and Technology
• /
• v.55 no.7
• /
• pp.2712-2722
• /
• 2023

For an accurate and efficient time-dependent Monte Carlo (TDMC) neutron transport analysis, several advanced methods are newly developed and implemented in the Seoul National University Monte Carlo code, McCARD. For an efficient control of the neutron population, a dynamic weight window method is devised to adjust the weight bounds of the implicit capture in the time bin-by-bin TDMC simulations. A moving geometry module is developed to model a continuous insertion or withdrawal of a control rod. Especially, the history-based batch method for the TDMC calculations is developed to predict the unbiased variance of a bin-wise mean estimate. The developed methods are verified for three-dimensional problems in the C5G7-TD benchmark, showing good agreements with results from a deterministic neutron transport analysis code, nTRACER, within the statistical uncertainty bounds. In addition, the TDMC analysis capability implemented in McCARD is demonstrated to search the optimum detector positions for the pulsed-neutron-source experiments in the Kyoto University Critical Assembly and AGN201K.

• Bulletin of the Korean Chemical Society
• /
• v.35 no.4
• /
• pp.1209-1211
• /
• 2014

• Journal of Ocean Engineering and Technology
• /
• v.34 no.5
• /
• pp.316-324
• /
• 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.

• Nuclear Engineering and Technology
• /
• v.48 no.5
• /
• pp.1120-1125
• /
• 2016

The neutron decay constant, ${\alpha}$, and effective delayed neutron fraction, ${\beta}_{eff}$, are important parameters for the control of the dynamic behavior of nuclear reactors. For the heavy water zero power reactor (HWZPR), this document describes the measurements of the neutron decay constant by noise analysis methods, including variance to mean (VTM) ratio and endogenous pulse source (EPS) methods. The measured ${\alpha}$ is successively used to determine the experimental value of the effective delayed neutron fraction as well. According to the experimental results, ${\beta}_{eff}$ of the HWZPR reactor under study is equal to 7.84e-3. This value is finally used to validate the calculation of the effective delayed neutron fraction by the Monte Carlo methods that are discussed in the document. Using the Monte Carlo N-Particle (MCNP)-4C code, a ${\beta}_{eff}$ value of 7.58e-3 was obtained for the reactor under study. Thus, the relative difference between the ${\beta}_{eff}$ values determined experimentally and by Monte Carlo methods was estimated to be < 4%.

• Nuclear Engineering and Technology
• /
• v.56 no.9
• /
• pp.3775-3784
• /
• 2024

In this study, a skewness estimation method (SEM) and kurtosis estimation method (KEM) are introduced to determine the number of inactive cycles in Monte Carlo eigenvalue calculations. The SEM and KEM can determine the number of inactive cycles on the basis that fully converged fission source distributions may follow normal distributions without asymmetry or outliers. Two convergence criteria values and a minimum cycle length for the SEM and KEM were determined from skewness and kurtosis analyses of the AGN-201K benchmark and 1D slab problems. The SEM and KEM were then applied to two OECD/NEA slow convergence benchmark problems to evaluate the performance and reliability of the developed methods. Results confirmed that the SEM and KEM provide appropriate and effective convergence cycles when compared to other methods and fission source density fraction trends. Also, the determined criterion value of 0.5 for both ε₁ and ε₂ was concluded to be reasonable. The SEM and KEM can be utilized as a new approach for determining the number of inactive cycles and judging whether Monte Carlo tally values are fully converged. In the near future, the methods will be applied to various practical problems to further examine their performance and reliability, and optimization will be performed for the convergence criteria and other parameters as well as for improvement of the methodology for practical usage.

• Communications for Statistical Applications and Methods
• /
• v.5 no.1
• /
• pp.55-67
• /
• 1998

Recent work by Shin and Sarkar (1996) examines model misspecification problems for nonstationary time series. Shin and Sarkar introduce a general regression model with integrated errors and one system of integrated regressors and discuss the limiting distributions of the OLS estimators and the usual OLS statistics such as $\hat{\sigma^2}$t, DW and $R^2$. We analyze three different model misspecification problems through a Monte Carlo study and investigate each model misspecification problem. Our Monte Carlo experiments show that DW and $R^2$ can be in general used as diagnostic tools to detect spurious regression, misspecification of nonstationary autoregressive and polynomial regression models.

• Journal of the Korean Statistical Society
• /
• v.36 no.3
• /
• pp.435-445
• /
• 2007

This paper addresses for the first time the use of complete data information criteria in unsupervised learning of the Naive-Bayes model. A Monte Carlo study sets a large experimental design to assess these criteria, unusual in the Bayesian network literature. The simulation results show that complete data information criteria underperforms the Bayesian information criterion (BIC) for these Bayesian networks.

• Journal of the Korea Society for Simulation
• /
• v.9 no.3
• /
• pp.43-51
• /
• 2000

In regression model, we estimate the unknown parameters by using various methods. There are the least squares method which is the most general, the least absolute deviation method, the regression quantile method and the asymmetric least squares method. In this paper, we will compare each others with two cases: firstly the theoretical comparison in the asymptotic sense and then the practical comparison using Monte Carlo simulation for a small sample size.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2000.11a
• /
• pp.6-10
• /
• 2000

In regression model we estimate the unknown parameters using various methods. There are the least squares method which is the most general, the least absolute deviation, the regression quantile and the asymmetric least squares method. In this paper, we will compare each others with two case: to begin with the theoretical comparison in the asymptotic sense, and then the practical comparison using Monte Carlo simulation for a small sample size.

• Journal of Radiation Protection and Research
• /
• v.47 no.1
• /
• pp.50-57
• /
• 2022

Background: There are several proton therapy facilities in operation or planned in Taiwan, and these facilities are anticipated to not only treat cancer but also provide beam services to the industry or academia. The simplified approach based on the Monte Carlo-based data sets (source terms and attenuation lengths) with the point-source line-of-sight approximation is friendly in the design stage of the proton therapy facilities because it is intuitive and easy to use. The purpose of this study is to expand the Monte Carlo-based data sets to allow the simplified approach to cover the application of proton beams more widely. Materials and Methods: In this work, the MCNP6 Monte Carlo code was used in three simulations to achieve the purpose, including the neutron yield calculation, Monte Carlo-based data sets generation, and dose assessment in simple cases to demonstrate the effectiveness of the generated data sets. Results and Discussion: The consistent comparison of the simplified approach and Monte Carlo simulation results show the effectiveness and advantage of applying the data set to a quick shielding design and conservative dose assessment for proton therapy facilities. Conclusion: This study has expanded the existing Monte Carlo-based data set to allow the simplified approach method to be used for dose assessment or shielding design for beam services in proton therapy facilities. It should be noted that the default model of the MCNP6 is no longer the Bertini model but the CEM (cascade-exciton model), therefore, the results of the simplified approach will be more conservative when it was used to do the double confirmation of the final shielding design.