• Geophysics and Geophysical Exploration
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• v.15 no.4
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• pp.227-234
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• 2012

In this study, we make simulation of density log using a Monte Carlo N-Particle (MCNP) algorithm to make an analysis on density logging under different borehole environments, since density logging is affected by various borehole conditions like borehole size, density of borehole fluid, thickness and type of casing, and so on. MCNP algorithm has been widely used for simulation of problems of nuclear particle transportation. In the simulation, we consider the specific configuration of a tool (Robertson Geologging Co. Ltd) that Korea institute of geoscience and mineral resources (KIGAM) has used. In order to measure accurate bulk density of a formation, it is essential to make a calibration and correction chart for the tool under considerations. Through numerical simulation, this study makes calibration plot of the density tool in material with several known bulk densities and with boreholes of several different diameters. In order to make correction charts for the density logging, we simulate and analyze measurements of density logging under different borehole conditions by considering borehole size, density of borehole fluid, and presence of casing.

• ETRI Journal
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• v.44 no.5
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• pp.837-848
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• 2022

Analog circuit design is comparatively more complex than its digital counterpart due to its nonlinearity and low level of abstraction. This study proposes a novel low-level hybrid of the sine-cosine algorithm (SCA) and modified grey-wolf optimization (mGWO) algorithm for machine learning-based design automation of CMOS analog circuits using an all-CMOS voltage reference circuit in 40-nm standard process. The optimization algorithm's efficiency is further tested using classical functions, showing that it outperforms other competing algorithms. The objective of the optimization is to minimize the variation and power usage, while satisfying all the design limitations. Through the interchange of scripts for information exchange between two environments, the SCA-mGWO algorithm is implemented and simultaneously simulated. The results show the robustness of analog circuit design generated using the SCA-mGWO algorithm, over various corners, resulting in a percentage variation of 0.85%. Monte Carlo analysis is also performed on the presented analog circuit for output voltage and percentage variation resulting in significantly low mean and standard deviation.

• Computational Structural Engineering
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• v.4 no.2
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• pp.111-117
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• 1991

The analysis method calculating the mean and standard deviation for the eigenvalue of complicated structures in which the limit state equation is implicitly expressed is formulated and applied to the buckling analysis by combining probabilistic finite element method with direct differential method which is a kind of sensitivity analysis technique. Also, the probability of buckling failure is calculated by combining classical reliability techniques such a MVFOSM and AFOSM. As random variables external load, elastic modulus, sectional moment of inertia and member length are chosen and Parkinson's iteration algorithm in AFOSM is used. The accuracy of the results by this study is verified by comparing the results with the crude Monte Carlo simulation and Importance Sampling Method. Through the case study of some structures the important aspects of buckling reliability analysis are discussed.

• Water for future
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• v.26 no.2
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• pp.79-87
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• 1993

A new method to estimate the mean areal precipitation using kriging is developed. Unlike the conventional approach, points for double and quadruple numerical integrations in the kriging equation are selected randomly, given the boundary of area of interest. This feature eliminates the conventional approach's necessity of dividing the area into subareas and calculating the center of each subarea, which in turn makes the developed method more powerful in the case of complex boundaries. The algorithm to select random points within an arbitrary boundary, based on the theory of complex variables, is described. The results of Monte Carlo simulation showed that the error associated with estimation using randomly selected points is inversely proportional to the square root of the number of sampling points.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.10
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• pp.52-58
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• 2007

This paper presents the wind-power model for generation adequacy assessment. Both wind-power and system load depend on time of a year and show their periodic nature with similar periods. Therefore, the two quantities have some probabilistic relations, and if one of them is given, the other can be decided with some probability. In this paper, the two quantities are quantized by k-means clustering algorithm and related probabilities among the cluster centers are calculated using sequential wind-power and system load data. The proposed model is highly expected to be applied for generation adequacy assessment by Monte-Carlo simulation with state sampling method.

• The Journal of Korea Robotics Society
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• v.15 no.2
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• pp.147-159
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• 2020

Over the last years, a number of different path following methods for the autonomous parking system have been proposed for tracking planned paths. However, it is difficult to find a study comparing path following methods for a short path length with large curvature such as a parking path. In this paper, we conduct a comparative study of the path following methods for perpendicular parking. By using Monte-Carlo simulation, we determine the optimal parameters of each controller and analyze the performance of the path following. In addition, we consider the path following error occurred at the switching point where forward and reverse paths are switched. To address this error, we conduct the comparative study of the path following methods with the one thousand switching points generated by the Monte-Carlo method. The performance of each controller is analyzed using the V-rep simulator. With the simulation results, this paper provides a deep discussion about the effectiveness and limitations of each algorithm.

• Journal of the Korean Society for Railway
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• v.10 no.2 s.39
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• pp.137-145
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• 2007

In traditional financial theory, the discount cash flow model(DCF or NPV) operates as the basic framework for most analyses. In doing valuation analysis, the conventional view is that the net present value(NPV) of a project is the measure of the present value of expected net cash flows. Thus, investing in a positive(negative) NPV project will increase(decrease) firm value. Recently, this framework has come under some fire for failing to consider the options of the managerial flexibilities. Real option valuation(ROV) considers the managerial flexibility to make ongoing decisions regarding the implementation of investment projects and the deployment of real assets. The appeal of the framework is natural given the high degree of uncertainty that firms face in their technology investment decisions. This paper suggests an algorithm for estimating volatility of logarithmic cash flow returns of real assets based on the Black-Sholes option pricing model, the binomial option pricing model, and the Monte Carlo simulation. This paper uses those models to obtain point estimates of real option value with the G7- HSR350X(high-speed train).

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07b
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• pp.1102-1105
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• 2003

Energy distribution function for electrons in $SF_6$-Ar mixtures gas used by MCS-BEq algorithm has been analysed over the E/N range $30{\sim}300[Td]$ by a two term Boltzmann equation and by 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 electron drift velocities, Electrons Drift Velocities for a rang of E/N values. As a consequence, it was known that the spatial growth rates and the dielectric behaviors in $SF_6$-Ar mixtures are strongly dependent on the addition rate of $SF_6$ gas but the transport coefficients of electrons are insensitive to the addition rate of $SF_6$ gas. 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.

• Proceedings of the KIEE Conference
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• 2003.07e
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• pp.75-78
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• 2003

Energy distribution function for electrons in $SF_6$-Ar mixtures gas used by MCS-BEq algorithm has been analysed over the E/N range $30\sim300$[Td] by a two term Boltzmann equation and by 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 electron drift velocities, the electron ionization or attachment coefficients, longitudinal and transverse diffusion coefficients and mean energy agree reasonably well with theoretical for a rang of E/N values. The transport coefficients for electrons in (0.2[%])$SF_6$-Ar and (0.5[%]$SF_6$ - Ar mixtures were measured by time-of-flight method, and the electron energy distribution function and the parameters of the velocity and the diffusion were determined by the variation of the collision cross-sections with energy. 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 Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.87-93
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• 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.