• Journal of the Korean Society for Precision Engineering
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• v.29 no.4
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• pp.479-486
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• 2012

Two of fundamental approaches that can be used to understand ion-solid interaction are Monte Carlo (MC) and Molecular Dynamic (MD) simulations. For the simplicity of simulation Monte Carlo simulation method is widely preferred. In this paper, basic consideration and algorithm of Monte Carlo simulation will be presented as well as simulation results. Sputtering caused by incident ion beam will be discussed with distribution of sputtered particles and their energy distributions. Redeposition of sputtered particles that are experienced refraction at the substrate-vacuum interface additionally presented. In addition, reflection of incident ions with reflection coefficient will be presented together with spatial and energy distributions. This Monte Carlo simulation will be useful in simulating and describing ion beam related processes such as Ion beam induced deposition/etching process, local nano-scale distribution of focused ion beam implanted ions, and ion microscope imaging process etc.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.1-20
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• 2009

The present contribution addresses uncertainty quantification and uncertainty propagation in structural mechanics using stochastic analysis. Presently available procedures to describe uncertainties in load and resistance within a suitable mathematical framework are shortly addressed. Monte Carlo methods are proposed for studying the variability in the structural properties and for their propagation to the response. The general applicability and versatility of Monte Carlo Simulation is demonstrated in the context with computational models that have been developed for deterministic structural analysis. After discussing Direct Monte Carlo Simulation for the assessment of the response variability, some recently developed advanced Monte Carlo methods applied for reliability assessment are described, such as Importance Sampling for linear uncertain structures subjected to Gaussian loading, Line Sampling in linear dynamics and Subset simulation. The numerical example demonstrates the applicability of Line Sampling to general linear uncertain FE systems under Gaussian distributed excitation.

• Journal of Industrial Technology
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• v.22 no.B
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• pp.3-12
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• 2002

Monte-Carlo simulation technique has advantages over deterministic simulation in various engineering analysis since Monte-Carlo simulation can take into consideration of scattering of various design variables, which is inherent characteristics of physical world. In this work, Monte-Carlo simulation of steady-state cornering behavior of a truck with design variables like hard points and busing stiffness. The purpose of the simulation is to improve understeer gradient of the truck, which exhibits a small amount of instability when the lateral acceleration is about 0.4g. Through correlation analysis, design variables that have high impacts on the cornering behavior were selected, and significant performance improvement has been achieved by appropriately changing the high impact design variables.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.106-108
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• 2002

Recent advances in radiation transport algorithms, computer hardware performance, and parallel computing make the clinical use of Monte Carlo based dose calculations possible. Monte Carlo treatment planning requires accurate beam information as input to generate accurate dose distributions. The procedures to obtain this accurate beam information are called "commissioning", which includes accelerator head modeling. In this study, we would like to investigate how much accurately Monte Carlo based dose calculations can predict the measured beam data in various conditions. The Siemens 6MV photon beam and the BEAM Monte Carlo code were used. The comparisons including the percentage depth doses and off-axis profiles of open fields and wedges, output factors will be presented.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.2
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• pp.127-136
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• 2008

Monte Carlo simulation methods are especially useful in studying a variety of problems difficult to calculate by experimental or analytical approaches. Nowadays, they are extensively applied to simulate nuclear medicine instrumentations such as single photon emission computed tomography (SPECT) and positron emission tomography (PET) for assisting system design and optimizing imaging and processing protocols. The goal of this paper is to address the practical issues, a potential user of Monte Carlo simulations for nuclear medicine can encounter, to help them to choose a code. This review introduces the different types of Monte Carlo codes currently available for nuclear medicine, comments main features and properties for a code to be proper for a given purpose, and discusses current research trends in Monte Carlo codes.

• JSTS:Journal of Semiconductor Technology and Science
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• v.9 no.1
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• pp.67-74
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• 2009

Monte Carlo simulation is widely used for predicting ion implantation profiles in amorphous targets. Here, we compared Monte Carlo simulation results with a vast database of ion implantation secondary ion mass spectrometry (SIMS), and showed that the Monte Carlo data sometimes deviated from the experimental data. We modified the electron stopping power model, calibrated its parameters, and reproduced most of the database. We also demonstrated that Monte Carlo simulation can accurately predict profiles in a low energy range of around 1keV once it is calibrated in the higher energy region.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.3 no.2
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• pp.58-64
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• 2008

In this paper, we proposed the methodology of interference analysis based on monte-carlo method for effective use of Industrial, Scientific, Medical (ISM) band. The interference scenario is divided according to the distance and density. The simulation of interference analysis evaluates the interference probability according to distribution density of Interfering Transmitters (It) in the Secure Interference Area (SIA). The SIA is gained from the Interference Efficiency Range that satisfied to Interference Permissible Range of Victim Receiver (Vr). Simulation result that apply the proposed interference scenario to the WLAN and bluetooth, Interference Permissible Range was 60~400m. And the WLAN was acceptable within interference permissible range to six bluetooth that exist in the SIA. In the same condition, when applied Listen Before Talk (LBT) based on Cognitive Radio (CR) to the bluetooth using Frequency Hopping (FH), interference probability was decreased sharply. The Spectrum Engineering Advanced Monte Carlo Analysis Tool (SEAMCAT) that has been developed based on the monte-carlo method by European Radio-communications Office (ERO) were used to the interference simulation.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.113-115
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• 2002

The Monte Carlo simulation method is a numerical solution to a problem that models objects interacting with other objects or their environment based upon simple object-object or object-environment relationships. In spite of its great accuracy, It was turned away because of long calculation time to simulate a model. But, it is used to simulate a linear accelerator frequently with the advance of computer technology. To simulate linear accelerator in Monte Carlo simulations, there are many parameters needed to input to Monte Carlo code. These data can be supported by a linear accelerator manufacturer. Although the model of a linear accelerator is the same, a different characteristic property can be found. Thus, we performed a commissioning process of 6MV photon beam in Varian 2300C/D model with BEAM/EGS4 Monte Carlo code. The head geometry data were put into BEAM/EGS4 data. The mean energy and energy spread of the electron beam incident on the target were varied to match Monte Carlo simulations to measurements. TLDs (thermoluminescent dosimeter) and radiochromic films were employed to measure the absorbed dose in a water phantom. Beam profile was obtained in 40cm${\times}$40cm field size and Depth dose was in 10cm${\times}$10cm. At first, we compared the depth dose between measurements and Monte Carlo simulations varying the mean energy of an incident electron beam. Then, we compared the beam profile with adjusting the beam radius of the incident electron beam in Monte Carlo simulation. The results were found that the optimal mean energy was 6MV and beam radius of 0.1mm was well matched to measurements.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.225-232
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• 1998

Results of Monte Carlo simulations on amorphous silicon based x-ray imaging arrays are described. In order to investigate the characteristics of amorphous silicon x-ray imaging devices and to provide the optimum design parameter, Monte Carlo simulations were performed. Monte Carlo simulation codes for our purpose were developed and various combinations of x-ray peak voltages, aluminum filter thicknesses, CsI(TI) thicknesses, and amorphous silicon photodiode pixel sizes were tested in connection with detection efficiency and spatial resolution of the amorphous silicon based x-ray imager. With usual Csl(TI) thickness of 300${\mu}{\textrm}{m}$-500${\mu}{\textrm}{m}$, detection efficiency was in the range of 70%-95% and energy absorption efficiency was in the range of 40%-70% for 60kVp-120kVp x-ray. From the simulations it was found that amorphous silicon pixel size and Csl(TI) thickness were the most important parameters which determine the resolution of the imager. By use of our simulation results we could provide proper combinations of Csl(TI) thicknesses and pixels sizes for optimum sensitivity and resolution.