• Journal of the Korea Concrete Institute
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• v.26 no.3
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• pp.343-350
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• 2014

A probabilistic construction stage analysis using the Monte Carlo Simulation was performed to address the effects of uncertainty regarding the material properties, environmental factors, and applied forces. In the previous research, creep and shrinkage were assumed to be completely independent random variables. However, because of the common influencing factors in the material models for the creep and shrinkage estimation, strong correlation between creep and shrinkage can be presumed. In this paper, an Monte Carlo Simulation using CEB-FIB creep and shrinkage equations were performed to actually evaluate the correlation coefficient between two phenomena, and then another Monte Carlo Simulation to evaluate the statistical properties of axial strain affected by partially correlated random variables including the material properties, environmental factors, and applied forces. The results of Monte Carlo Simulation were compared with measured strains of a column on a first story in a 58-story building. Comparison indicated that the variation due to the uncertainty related with the material properties were most severe. And measured strains was within the range of mean+standard deviation.

• Electrical & Electronic Materials
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• v.8 no.6
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• pp.685-692
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• 1995

The electron transport coefficients in argon gas is studied over the range of E/N values from 85 to 566 Td by the Monte Carlo method considering the latest cross section data. The result of the Monte Carlo method analysis shows that the value of the electron transport coefficients such as the electron drift velocity, the ratio of the longitudinal and transverse diffusion coefficients to the mobility. It is also found that the electron transport coefficients calculated by the two-term approximation analysis agree well with those by Monte Carlo calculation. The electron energy distributions function were analysed in argon at E/N=283, and 566 Td for a case of the equilibrium region in the mean electron energy. A momentum transfer cross section for the argon atom which was consistent with both of the present electron transport coefficients was derived over the range of mean electron energy from 10.3 to 14.5 eV, also suggested as a set of electron cross section for argon atom. The validity of the results obtained has been confirmed by a Monte Carlo simulation method.

• Bulletin of the Korean Chemical Society
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• v.33 no.8
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• pp.2553-2559
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• 2012

The adsorption properties of benzene, toluene, p-xylene in MCM-41 with heterogeneous and cylindrical pore were studied using grand canonical ensemble Monte Carlo simulation. The simulated isotherms were compared with experimental ones, and the different adsorption behaviors in MCM-41 with pore diameters of 2.2 and 3.2 nm were investigated. The simulated adsorption amounts above the capillary-condensation pressure agreed with the experimental ones. The simulation results showed that most molecular planes were nearly parallel to the pore axis. This orientation was not affected by the molecular position in the pore. The molecular planes were nearly parallel to the pore surface for the adsorbate molecules close to the pore wall, and the molecules in the MCM-41 with the pore diameter of 3.2 nm were ordered along the pore axis.

• Journal of computational fluids engineering
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• v.4 no.3
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• pp.63-70
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• 1999

A Direct simulation Monte-Carlo (DSMC) code is developed, which employs the Monte-Carlo statistical sampling technique to investigate hypersonic rarefied gas flows accompanying chemical reactions. The DSMC method is a numerical simulation technique for analyzing the Boltzmann equation by modeling a real gas flow using a representative set of molecules. Due to the limitations in computational requirements. the present method is applied to a flow around a simple two-dimensional object in exit velocity of 7.6 km/sec at an altitude of 90 km. For the calculation of chemical reactions an air model with five species (O₂, N₂, O, N, NO) and 19 chemical reactions is employed. The simulated result showed various rarefaction effects in the hypersonic flow with chemical reactions.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.957-962
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• 2008

We propose a model for the line expansion problem in the AMOLED (Active Matrix Organic Light Emitting Diodes) industry, which now faces market uncertainty: for example, changing customer needs, technological development path, etc. We focus on the optimal investment time and size of the AMOLED production lines. In particular, employed here is the ROV (Real Options Valuation) model to show how to capture the value of line expansion and to determine the optimal investment time. The ROV framework provides a systematic procedure to quantify an expected outcome of a flexible decision which is not possible in the frame of the traditional NPV (Net Present Value) approach. Furthermore, we also use Monte Carlo simulation to measure the uncertainty associated with the line expansion decision; Monte Carlo simulation estimates the volatility of a decision alternative. Lastly, we present a scenario planning to be conducted for what-if analysis of the ROV model.

• International Journal of Automotive Technology
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• v.6 no.6
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• pp.625-633
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• 2005

Vehicle drift was reduced using statistical six sigma tools. The study was performed through four steps: M (measure), A (analyze), I (improve), and C (control). Step M measured the main factors which were derived from a fishbone diagram. The measurement system capabilities were analyzed and improved before measurement. Step A analyzed critical problems by examining the process capability and control chart derived from the measured values. Step I analyzed the influence of the main factors on vehicle drift using DOE (design of experiment) to derive the CTQ (critical to quality). The tire conicity and toe angle difference proved to be CTQ. This information enabled the manufacturing process related with the CTQ to be improved. The respective toe angle tolerance for the adjustment process was obtained using the Monte Carlo simulation. Step C verified and controlled the improved results through hypothesis testing and Monte Carlo simulation.

• Journal of radiological science and technology
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• v.34 no.3
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• pp.215-219
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• 2011

Monte Carlo simulation was performed to investigate optimal system of proton computed tomography and to avoid the errors by using data from X ray computed tomography in proton therapy. The informations from two DSSDs to measure position and LYSO scintillation detector to measure the residual energy of proton particle in GEANT4 were used for reconstruction computed tomography.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.3
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• pp.125-129
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• 2015

Energy distribution function for electrons in SF6-Ar mixtures gas used by MCS-BEq algorithm has been analysed over the E/N range 30~300[Td] by a two term Boltzmann equation and a Monte Carlo Simulation using a set of electron cross sections determined by other authors experimentally the electron swarm parameters for 0.2[%] and 0.5[%] $SF_6-Ar$ mixtures were measured by time-of-flight(TOF) method, The results show that the deduced longitudinal diffusion coefficients and transverse diffusion coefficients agree reasonably well with theoretical for a rang of E/N values. The results obtained from Boltzmann equation method and Monte Carlo simulation have been compared with present and previously obtained data and respective set of electron collision cross sections of the molecules.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.12 s.189
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• pp.72-79
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• 2006

Vibration of a non-linear system under random parametric excitations was evaluated by probabilistic methods. The non-linear characteristic terms of a system structure were quasi-linearized and excitation terms were remained as they were An analytical method where the square mean of error was minimized was used An alternative method was an energy method where the damping energy and restoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.71-94
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• 2009

In this paper a procedure for Monte Carlo simulation of univariate stationary stochastic processes with the aid of neural networks is presented. Neural networks operate model-free and, thus, circumvent the need of specifying a priori statistical properties of the process, as needed traditionally. This is particularly advantageous when only limited data are available. A neural network can capture the "pattern" of a short observed time series. Afterwards, it can directly generate stochastic process realizations which capture the properties of the underlying data. In the present study a simple feed-forward network with focused time-memory is utilized. The proposed procedure is demonstrated by examples of Monte Carlo simulation, by synthesis of future values of an initially short single process record.