• Nuclear Engineering and Technology
• /
• v.54 no.5
• /
• pp.1902-1908
• /
• 2022

In many of the complex systems modeled in the field of nuclear engineering, it is often useful to use linear regression-based analyses to analyze relationships between model parameters and responses of interests. In cases where the response of interest is calculated by a simulation which uses Monte Carlo methods, there will be some uncertainty in the responses. Further, the reduction of this uncertainty increases the time necessary to run each calculation. This paper presents some discussion on how the Monte Carlo error in the response of interest influences the error in computed linear regression coefficients. A mathematical justification is given that shows that when performing linear regression in these scenarios, the error in regression coefficients can be largely independent of the Monte Carlo error in each individual calculation. This condition is only true if the total number of calculations are scaled to have a constant total time, or amount of work, for all calculations. An application with a simple pin cell model is used to demonstrate these observations in a practical problem.

• The Korean Journal of Applied Statistics
• /
• v.24 no.2
• /
• pp.401-409
• /
• 2011

From a social network of n nodes connected by l lines, one may produce centrality measures such as closeness, betweenness and so on. In the past, the magnitude of n was around 1,000 or 10,000 at most. Nowadays, some networks have 10,000, 100,000 or even more than that. Thus, the scalability issue needs the attention of researchers. In this short paper, we explore random networks of the size around n = 100,000 by Monte-Carlo method and propose Monte-Carlo algorithms of computing closeness and betweenness centrality measures to study the small world properties of social networks.

• Nuclear Engineering and Technology
• /
• v.46 no.4
• /
• pp.481-488
• /
• 2014

An analysis of the uncertainty quantification related to LBLOCA using the Monte-Carlo calculation has been performed and compared with the tolerance level determined by the Wilks' formula. The uncertainty range and distribution of each input parameter associated with the LOCA phenomena were determined based on previous PIRT results and documentation during the BEMUSE project. Calulations were conducted on 3,500 cases within a 2-week CPU time on a 14-PC cluster system. The Monte-Carlo exercise shows that the 95% upper limit PCT value can be obtained well, with a 95% confidence level using the Wilks' formula, although we have to endure a 5% risk of PCT under-prediction. The results also show that the statistical fluctuation of the limit value using Wilks' first-order is as large as the uncertainty value itself. It is therefore desirable to increase the order of the Wilks' formula to be higher than the second-order to estimate the reliable safety margin of the design features. It is also shown that, with its ever increasing computational capability, the Monte-Carlo method is accessible for a nuclear power plant safety analysis within a realistic time frame.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.6 no.3
• /
• pp.63-74
• /
• 1986

A methodology for the probabilistic determination of active storage capacity of an impounding reservoir is proposed with due considerations to the durations and return periods of the low flow series at the reservoir site. For more reliable probabilistic analysis the best-fit stochastic generation model of Monte Carlo type was first selected for the generation of monthly flow series, the models tested being the Month Carlo Model based on the month-by-month flow series (Monte Carlo-A Type), Monte Carlo Model based on the standardized sequential monthly flow series (Monte Carlo-B Type), and the Thomas-Fiering Model. Monte Carlo-B Model was final1y selected and synthetic monthly flows of 200 years at Hong Cheon dam site were generated. With so generated 200 years' monthly flows partial duration series of low flows were developed for various durations. Each low flow series was further processed by a nonsequential mass analysis for specified draft rates. This mass analysis furnished the storage-draft-recurrence interval relationship which gives the reservoir storage requirement for a specified water demand from the reservoir during a drought of given return period. Illustrations are given on the application of these results in analyzing the water supply capacity of a particlar reservoir, existing or proposed.

• Journal of the Korean Geotechnical Society
• /
• v.23 no.11
• /
• pp.109-117
• /
• 2007

Uncertainty is pervasive in rock slope stability analysis due to various reasons and subsequently it may cause serious rock slope failures. Therefore, the importance of uncertainty has been recognized and subsequently the probability theory has been used to quantify the uncertainty since 1980's. However, some uncertainties, due to incomplete information, cannot be handled satisfactorily in the probability theory and the fuzzy set theory is more appropriate for those uncertainties. In this study the random variable is considered as fuzzy number and the fuzzy set theory is employed in rock slope stability analysis. However, the previous fuzzy analysis employed the approximate method, which is first order second moment method and point estimate method. Since previous studies used only the representative values from membership function to evaluate the stability of rock slope, the approximated analysis results have been obtained in previous studies. Therefore, the Monte Carlo simulation technique is utilized to evaluate the probability of failure for rock slope in the current study. This overcomes the shortcomings of previous studies, which are employed vertex method. With Monte Carlo simulation technique, more complete analysis results can be secured in the proposed method. The proposed method has been applied to the practical example. According to the analysis results, the probabilities of failure obtained from the fuzzy Monte Carlo simulation coincide with the probabilities of failure from the probabilistic analysis.

• Water for future
• /
• v.26 no.2
• /
• pp.89-97
• /
• 1993

For the system benefit optimization by considering risk or reliability from a multiple reservoir system using the Monte Carlo technique, many stochastically generated inflow series have to be used for the system analysis. In this study, the stochastically generated inflow series for the multiple reservoir system operation are preprocessed according to the considered system objectives and operating time periods. Through this procedure, several representative inflow series which have discrete probability levels and operation horizons are selected among the thousands of generated inflows. Then a deterministic optimization technique is applied to the power energy estimation from the Han River Reservoirs System which considers five reservoirs in the study. It took much lower computational requirements then using the original Monte Carlo Technique, even though estimated result was almost similar.

• Journal of Welding and Joining
• /
• v.18 no.3
• /
• pp.122-130
• /
• 2000

Due to the inherent dimensional uncertainty, the tolerances accumulate in the assembly of plasma cutting torch. Tolerance accumulation has serious effect on the performance of the plasma torch. This study proposes a statistical tolerance propagation model, which is based on matrix transform. This model can predict the final tolerance distributions of the completed plasma torch assembly with the prescribed statistical tolerance distribution of each part to be assembled. Verification of the proposed model was performed by making use of Monte Carlo simulation. Monte Carlo simulation generates a large number of discrete plasma torch assembly instances and randomly selects a point within the tolerance region with the prescribed statistical distribution. Monte Carlo simulation results show good agreement with that of the proposed model. This results are promising in that we can predict the final tolerance distributions in advance before assembly process of plasma torch thus provide great benefit at the assembly design stage of plasma torch.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.17 no.1
• /
• pp.71-76
• /
• 2008

Nonlinear dynamic system under random excitation was analyzed by using stochastic method. A linearization method was used in order to linearize non-linear structural characteristics but the parametric excitation was used as it was given. An equivalent energy method which equalizes the expectation value of energy of the original nonlinear system and that of quasi-linearized system was proposed. Ito's differential rule was applied to obtain steady state moments. Quasi-linearization coefficients can be obtained the iterative calculation of linearization scheme and steady state moments. Monte Carlo simulation was used to verify the results of the proposed method. Nonlinear vibration of a slender beam was analyzed in this research. The analysis results were compared with Monte Carlo simulation result and showed good agreement. As the spectral density of the given excitation increased, the analysis results showed the better agreement with Monte Carlo simulation.

• Journal of the Semiconductor & Display Technology
• /
• v.8 no.4
• /
• pp.37-42
• /
• 2009

The performance of an OLED(organic luminescent emitting device) fabrication system strongly depends on the design of the evaporation cell-source. Trends in display sizes have hauled the enlargement of mother glass substrates. The enlargement of substrates requires the improvement and the enlargement of the effusion cell-source for OLED evaporation process. The deposited layers should be as uniform as possible, and therefore it is important to know the effusion profile of the molecules emitted from the cell-source. Conventional 2D DSMC algorithm cannot be used for simulating the new concept cell-source design, such as a linear source. This work concerns the development of 3D DSMC (direct simulation Monte Carlo) analysis for simulating the behavior of the evaporation cell-sources. In this paper, the 3D DSMC algorithm was developed and the film thickness profiles were obtained by the numerical analysis.

• Tunnel and Underground Space
• /
• v.14 no.2
• /
• pp.97-107
• /
• 2004

Various kinds of rock mass properties, which can be obtained from laboratory tests as well as field tests, can be reasonably applied to the design of earth structures. An extrapolation technique can be used for this application and it generally guarantee its quality from a sufficient amount of test results because it is based on the RMR value in most cases. When the confident RMR can not be obtained because of the insufficient testing results, the Monte Carlo Simulation technique can be introduced fer deducing the proper RMR and this assessed RMR can be reused fur the major input parameters. Authors' proposed method can be verified from the comparison between the results of numerical analysis and the evidences of field site.