• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• 제21권8호
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• pp.34-43
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• 2007

This paper presents a methodology on the AHP(Analytic Hierarchy Process) to calculate unified power quality index which provide an overall assessment of the distribution system performance. To obtain the unified power quality index. we propose the use of the AHP model and consider contingency using Monte Carlo simulation. The proposed method is especially useful and effective for planning. We have applied the proposed method to an actual relatively large system.

• Journal of the Optical Society of Korea
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• 제15권4호
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• pp.373-379
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• 2011

Current therapeutic methods for suppressing muscle spasticity are intensive functional training, surgery, or pharmacological interventions. However, these methods have not been fully supported by confirmed efficacy due to the aggravation of the muscle spasticity in some patients. In this study, a combined system was developed to treat with a low-level laser and to monitor the region of the treatment using an optical spectroscopic probe that measures oxygen saturation and deoxygenation during low-level laser therapy (LLLT). The evaluation of the wavelength dependence for LLLT was performed using a Monte Carlo simulation and the results showed that the greatest amount of heat generation was seen in the deep tissue at ${\lambda}$ = 830 nm. In the oxy- and deoxygenation measurements during and after the treatment, oxygen-Hb concentration was significantly increased in the laser-irradiated group when compared to the control group. These findings suggest that LLLT using ${\lambda}$ = 830 nm may be of benefit in accelerating recovery of muscle spasticity. The combined system that we have developed can monitor the physiological condition of muscle spasticity during the laser treatment in real time and may also be applied to various myotonia conditions such as muscle fatigue, back-pain treatment/monitoring, and ulcer due to paralysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제14권5호
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• pp.1043-1053
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• 1994

This study suggests a practical but rational approach for the development of reliability-based LRFD criteria for transmission towers under wind and ice loadings in Korea. Based on available statistical data on wind speed and icing on transmission lines in Korea, the design wind and ice loads are obtained by Monte Carlo Simulations. In the study, the AFOSM reliability method and an Importance Sampling Technique are used for the element and system reliability evaluation of actual transmission towers. Based on the selected target reliabilities, a set of load and resistance factors for the LRFD criteria are calibrated using the AFOSM and the code optimization technique.

• Proceedings of the Korean Society of Medical Physics Conference
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• 한국의학물리학회 2002년도 Proceedings
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• pp.208-210
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• 2002

In a treatment planning for actual patients with a complex internal structure, we often expect that proton beams, which pass through both a bolus and the heterogeneity in body, will form complex dose distributions. Therefore, the accuracy of the calculated dose distributions has to be verified for such a complex object. Then dose distributions formed by proton beams passing through both the bolus and phantoms simulating a clinical heterogeneity in patients were measured using a silicon semiconductor detector. The calculated results by the range-modulated pencil beam algorithm (RMPBA) produced large errors compared with the measured dose distributions since dose calculation using the RMPBA could not predict accurately the edge-scattering effect both in the bolus and in clinical heterogeneous phantoms. On the other hand, in spite of this troublesome heterogeneity, calculated results by the simplified Monte Carlo (SMC) method reproduced the experimental ones well. It is obvious that the dose-calculations by the SMC method will be more useful for application to the treatment planning for proton therapy.

• Journal of the Korean Society for Precision Engineering
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• 제24권2호
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• pp.110-117
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• 2007

In this paper, probabilistic distribution of chassis component fatigue life is determined statistically by applying the design of experiments and the Pearson system. To construct p - ${\varepsilon}$ - N curve, the case that fatigue data are random variables is attempted. Probabilistic density function (p.d.f) for fatigue life is obtained by the design of experiment and using this p.d.f fatigue reliability, any aimed fatigue life can be calculated. Lower control arm and rear torsion bar of chassis components are selected as examples for analysis. Component load histories which are obtained by multi-body dynamic simulation for Belsian load history are used. Finite element analysis is performed by using commercial software MSC Nastran and fatigue analysis is performed by using FE Fatigue. When strain-life curve itself is random variable, the probability density function of fatigue life has very little difference from log-normal distribution. And the cases of fatigue data are random variables, probability density functions are approximated to Beta distribution. Each p.d.f is verified by Monte-Carlo simulation.

• Wind and Structures
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• 제27권3호
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• pp.199-211
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• 2018

This paper deals with wind fragility and risk analysis of high rise buildings subjected to stochastic wind load. Conventionally, such problems are dealt in full Monte Carlo Simulation framework, which requires extensive computational time. Thus, to make the procedure computationally efficient, application of metamodelling technique in fragility analysis is explored in the present study. Since, accuracy by the conventional Least Squares Method (LSM) based metamodelling is often challenged, an efficient Moving Least Squares Method based adaptive metamodelling technique is proposed for wind fragility analysis. In doing so, artificial time history of wind load is generated by three wind field models: i.e., a simple one based on alongwind component of wind speed; a more detailed one considering coherence and wind directionality effect, and a third one considering nonstationary effect of mean wind. The results show that the proposed approach is more accurate than the conventional LSM based metamodelling approach when compared to full simulation approach as reference. At the same time, the proposed approach drastically reduces computational time in comparison to the full simulation approach. The results by the three wind field models are compared. The importance of non-linear structural analysis in fragility evaluation has been also demonstrated.

• Journal of the Korean Geotechnical Society
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• 제29권3호
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• pp.41-50
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• 2013

There always exists uncertainty which is mainly due to uncertainty of the evaluation of a geotechnical structure at a site. The uncertainty in the geotechnical analysis can be considered in the probabilistic analysis using the Monte Carlo Simulation. It needs various soil profiles which could be possible at the target site. In this study, a new method is proposed to generate soil profiles which are probable at the site. The proposed method analyzes a structure of a site and generates one dimensional soil profiles for a probabilistic analysis. Through the field application, the applicability of the prosed method was shown.

• Advances in Computational Design
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• 제2권3호
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• pp.165-194
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• 2017

The present work proposes the thermo mechanically induced statistics of nonlinear transverse central deflection of elastically supported functionally graded (FG) plate subjected to static loadings with random system properties. The FG plate is supported on two parameters Pasternak foundation with Winkler cubic nonlinearity. The random system properties such as material properties of FG material, external loading and foundation parameters are assumed as uncorrelated random variables. The material properties are assumed as non-uniform temperature distribution with temperature dependent (TD) material properties. The basic formulation for static is based on higher order shear deformation theory (HSDT) with von-Karman nonlinear strain kinematics through Newton-Raphson method. A second order perturbation technique (SOPT) and direct Monte Carlo simulation (MCS) are used to compute the nonlinear governing equation. The effects of load parameters, plate thickness ratios, aspect ratios, volume fraction, exponent, foundation parameters, and boundary conditions with random system properties are examined through parametric studies. The results of present approaches are compared with those results available in the literature and by employing direct Monte Carlo simulation (MCS).

• Earthquakes and Structures
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• 제13권3호
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• pp.323-335
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• 2017

A simplified framework for the probabilistic estimation of economic losses induced by the structural vulnerability in single-story and single-bay precast industrial buildings is presented. The simplifications introduced in the framework are oriented to the definition of an expeditious procedure adoptable by government agencies and insurance companies for preliminary risk assessment. The economic losses are evaluated considering seismic hazard, structural response, damage resulting from the structural vulnerability and only structural-vulnerability-induced e]conomic losses, i.e., structural repair or reconstruction costs (stock and flow costs) and content losses induced by structural collapse. The uncertainties associated with each step are accounted for via Monte Carlo simulations. The estimation results in a probabilistic description of the seismic risk of portal-like industrial buildings, expressed in terms of economic losses for each occurrence (i.e., seismic event) that owners (i.e., insured) and stakeholders can use to make risk management decisions. The outcome may also be useful for the definition of the insurance premiums and the evaluation of the risks and costs for the owner corresponding to the insurance industrial costs. A prototype of a precast concrete industrial building located in Mirandola, Italy, hit by the 2012 Emilia earthquake, is used as an example of the application of the procedure.

• Journal of the Korean Operations Research and Management Science Society
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• 제37권3호
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• pp.135-150
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• 2012

This paper presents a portfolio model for a long-term power generation mix problem. The proposed portfolio model evaluates generation mix by considering the tradeoffs between the expected cost for power generation and its variability. Unlike conventional portfolio models measuring variance, we introduce Conditional Value-at-Risk (CVaR) in designing the variability with aims to considering events that are enormously expensive but are rare such as nuclear power plant accidents. Further, we consider uncertainties associated with future electricity demand, fuel prices and their correlations, and capital costs for power plant investments. To obtain an objective generation by each energy source, we employ the sample average approximation method that approximates the stochastic objective function by taking the average of large sample values so that provides asymptotic convergence of optimal solutions. In addition, the method includes Monte Carlo simulation techniques in generating random samples from multivariate distributions. Applications of the proposed model and method are demonstrated through a case study of an electricity industry with nuclear, coal, oil (OCGT), and LNG (CCGT) in South Korea.