• Water for future
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• v.18 no.4
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• pp.335-345
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• 1985

The purpose of stochastic models for synthetic generation of river flows based on the short-term observed data is to provide abundant input data to the water resources systems of which the system performance and operation policy are to be determined beforehand. Among many of such models the Monte Carlo Method of synthetic generation, which is usually known to be appropriate for annual data generation, is employed to check if it can be applied for the generation of monthly flows. For the purpose of comparisons the statistical parameters of the generated monthly flows by Monte Carlo model based on the appropriate probability distribution for each month were compared with those of the generated flows by Thoms-Fiering multiseason model and with those of the observed monthly flows. On the other hand, the statistical parameters of the annual river flows obtained by adding the generated monthly flows year by year based on the Monte Carlo and Thomas-Fiering models were compared with those of the annual flows generated directly by annual Monte Carlo model with reference to those for the observed annual river flows. Based on the above comparative studies, the discussions are made and conclusions derived.

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

• 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.

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

• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.55-67
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• 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
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• v.36 no.3
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• pp.435-445
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• 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
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• v.9 no.3
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• pp.43-51
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• 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
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• 2000.11a
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• pp.6-10
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• 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
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• v.47 no.1
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• pp.50-57
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• 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.

• Journal of radiological science and technology
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• v.23 no.2
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• pp.75-79
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• 2000

This study was performed for the clinical applications applying the Monte Carlo methods. In this study we calculated the absorbed dose distributions for the 6 MeV electron beam in water phantom and compared the results with measured values. The energy data of electron beam used in Monte Carlo calculation is the energy distribution for 6 MeV electron beam which is assumed as a Gaussian form. We calculated percent depth doses and beam profiles for three field sizes of $10{\times}10,\;15{\times}15$, and $20{\times}20\;cm^2$ in water phantom using Monte Carlo methods and measured those data using a semiconductor detector and other devices. We found that the calculated percent depth doses and beam profiles agree with the measured values approximately. However, the calculated beam profiles at the edge of the fields were estimated to be lower than the measured values. The reason for that result is that we did not consider the angular distributions of the electrons in phantom surface and contamination of X-rays in our calculations. In conclusion, in order to apply the Monte Carlo methods to the clinical calculations we are to study the source models for electron beam of the linear accelerator beforehand.