• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2009.05a
• /
• pp.350-353
• /
• 2009

In the fatigue analysis and the components design, uncertainties are caused by the variances of geometry data and applied loads, and the scatter of material properties. In this paper, fatigue crack growth life of turbine is evaluated by fracture mechanics and the reliability analysis is accessed by the fist order second moment method and Monte Carlo simulation.

• Journal of Radiation Protection and Research
• /
• v.11 no.1
• /
• pp.29-36
• /
• 1986

GESS-a computer code for simulation of energy spectra for gamma-ray in NaI(T1) scintillator has been developed. The Monte Carlo method was employed to simulate physical behaviours of particle transport in a medium. In the processes of simulation, all the interaction processes such as Rayleigh and Compton scattering, photoelectric effect and pair production were considered. The resulting electron slowing down spectrum was also considered with the CSDA model. For the purpose of verification of the code, a measurement gamma spectrum for incident gamma energy of 1.33 MeV was performed. The measured values appeared to be slightly higher than the theoretically calculated values.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.54 no.3
• /
• pp.87-93
• /
• 2017

A maximum likelihood (ML) approach is presented for estimating the mean of radar cross section (RCS) of a Swerling III target and its numerical solution methods are discussed. The solution methods are based on an approximate expression for implementing the expectation maximization (EM) algorithm. The methods are evaluated and compared through Monte Carlo simulations in terms of estimation accuracy and computational efficiency to obtain a most efficient method for both Swerling I and Swerling III targets. The methods are also compared with a previously reported method based on heuristics.

• Journal of the Korean Geotechnical Society
• /
• v.23 no.3
• /
• pp.111-121
• /
• 2007

The paper presents a reliability-based method that can capture the impact of uncertainty of seismic loadings. The proposed method incorporates probabilistic concepts into the classical limit equilibrium and the Newmark-type deformation techniques. The risk of damage is then computed by Monte Carlo simulation. Random process and RMS hazard method are introduced to produce seismic motions and also to use them in the seismic slope analyses. The geotechnical variability and sampling errors are also considered. The results of reliability analyses indicate that in a highly seismically active region, characterization of earthquake hazard is the more critical factor, and characterization of soil properties has a relatively small effect on the computed risk of slope failure and excessive slope deformations. The results can be applicable to both circular and non-circular slip surface failure modes.

• Journal of Korea Water Resources Association
• /
• v.30 no.6
• /
• pp.691-698
• /
• 1997

The risk assessment model for dam and levee is applied to a river where two adjacent dams are located in the upstream of the watershed. "A" dam is proven to be safe with 200-year precipitation and unsafe with PMP condition, whereas "B" dam to be safe with 200-year precipitation and PMP condition. The computed risk considering the uncertainties of the runoff coefficient. initial water depth and relevant data of the dam and spillway turn out to be equivalent results in Monte-Carlo and AFOSM method. In levee risk model, this study addresses the uncertainty of water surface elevation by Manning's equation. Monte-Carlo simulation with the variations of Manning's roughness coefficient is calculated by assuming that it follows atriangular distribution. The model can be used for preparing flood risk maps, flood warning systems, and establishing nation's flood disaster protection plan.

• Journal of the Korean Society of Radiology
• /
• v.12 no.3
• /
• pp.289-295
• /
• 2018

Most diagnostic devices in the medical field use X-ray sources, which emit energy spectra. In radiological diagnosis, the quantitative and qualitative analyses of X-rays are essential for maintaining the image quality and minimizing the radiation dose to patients. This work aims to obtain the X-ray energy spectra used in diagnostic imaging by Monte Carlo simulation. Various X-ray spectra are simulated using a Monte Carlo simulation tool. These spectra are then compared to the reference data obtained with a tungsten anode spectral model using the interpolating polynomial (TASMIP) code. The X-ray tube voltages used are 50, 60, 80, 100, and 110 kV, respectively. CdTe and a-Se detector are used as the detectors for obtaining the X-ray spectra. Simulation results demonstrate that the various X-ray spectra are well matched with the reference data. Based on the simulation results, an appropriate X-ray spectrum, in accordance with the tube voltage, can be selected when generating an image for diagnostic imaging. The dose to be delivered to the patient can be predicted prior to examination in the diagnostic field.

• Journal of Korea Water Resources Association
• /
• v.38 no.12 s.161
• /
• pp.1051-1060
• /
• 2005

The present study analyzes hydrologic utilization of optimal radar-derived rainfall by using semi-distributed TOPMODEL and evaluates the impacts of radar rainfall and model parametric uncertainty on a hydrologic model. Monte Carlo technique is used to produce the flow ensembles. The simulated flows from the corrected radar rainfalls with real-time bias adjustment scheme are well agreed to observed flows during 22-26 July 2003. It is shown that radar-derived rainfall is useful for simulating streamflow on a basin scale. These results are diagnose with which radar-rainfall Input and parametric uncertainty influence the character of the flow simulation uncertainty. The main conclusions for this uncertainty analysis are that the radar input uncertainty is less influent than the parametric one, and combined uncertainty with radar and Parametric input can be included the highest uncertainty on a streamflow simulation.

• Journal of Korean Society of Environmental Engineers
• /
• v.30 no.11
• /
• pp.1123-1131
• /
• 2008

In this study, measurement uncertainty of instrumental neutron activation analysis was evaluated for ambient As concentration in PM2.5. Expanded uncertainties of the measurements were calculated by applying both ISO-GUM approximation and Monte Carlo Simulation(MCS). The estimate of As concentration on a specific day by the Monte Carlo Simulation differed from that of ISO-GUM approximation by less than 4%. Relative expanded uncertainties of As concentrations from a total number of 60 PM2.5 samples were also estimated to be more or less than 10% with 95% confidence level using the Monte Carlo Simulation. Sensitivity test of the measurement uncertainties showed that $\gamma$-ray counting error(62.3%), efficiency(18.5%), air volume(12.3%), neutron flux(2.3%), and absolute gamma-intensity(1.8%) are major factors of uncertainty variations.

• Journal of the Korean Vacuum Society
• /
• v.21 no.2
• /
• pp.86-92
• /
• 2012

We have studied the effect of speed of deposited atom on morphology evolution during Glancing Angle Deposition (GLAD). Using Kinetic Monte Carlo simulation that incorporate molecular dynamics simulations, we have shown that the rough surface morphology became smoother as the speed of deposited atom is increased. The growth exponent ${\beta}$ change from 0.97 to 0.67 as the speed increase from ${\upsilon}_0$ to $10{\upsilon}_0$ in the case of GLAD. We also examined the effect of speed of deposited atom for the case of chemical vapor deposition (CVD) simulation. Compared to GLAD, the variation in scaling exponent ${\beta}$ is small but the speed of deposited atom also have considerable effect on growth morpholgy in the case of CVD.

• Journal of Korea Game Society
• /
• v.14 no.3
• /
• pp.47-54
• /
• 2014

The game of Go is one of the oldest games and originated at least more than 2,500 years ago. In game programming the most successful approach is to use game tree searches using evaluation functions. However it is really difficult to construct feasible evaluation function in computer Go. Monte-Carlo Tree Search(MCTS) has created strong computer Go programs such as MoGo and CrazyStone which defeated human Go professionals played on the $9{\times}9$ board. MCTS is based on the winning rate estimated by Monte-Carlo simulation. Prior to implementing MCTS into computer Go, we tried to measure each winning rate of three positions, center, corner and side, in Tic-Tac-Toe playing as the best first move. The experimental result revealed that the center is the best, a corner the next and a side the last as the best first move.