• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.4
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• pp.751-758
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• 2000

In this paper, we discuss frequency allocation and sharing for high speed radio access network in domestic 5GHz the band. In order to evaluate the possibility of frequency sharing between meteorological radar and high speed radio access network, we analyses radio interference of meteorological radar by means of minimum coupling loss method and Monte Carlo simulation. And simulations show that it is necessary to use DFS(Dynamic Frequency Selection) scheme for frequency sharing between meteorological radar and high speed radio access network.

• Journal of the Korean Society of Safety
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• v.20 no.2 s.70
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• pp.119-126
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• 2005

Load bearing structural members in a wide variety of applications accumulate damage over their service life. From a standpoint of both safety and performance, it is desirable to monitor the occurrence, location, and extent of such damage. Structures require complicated element models with a number of degrees of freedom in structural analysis. During experiment much effort and cost is needed for measuring structural parameters. The sparseness and errors of measured data have to be considered during the parameter estimation Of Structures. In this paper we introduces damage identification algorithm by a system identification(S.I) using static and dynamic response. To study the behaviour of the estimators in noisy environment Using Monte Carlo simulation and a data measured perturbation scheme is adopted to investigate the influence of measurement errors on identification results. The assessment result by static and dynamic response were compared, and the efficiency and applicabilities of the proposed algorithm are demonstrated through simulated static and dynamic responses of a truss bridge. The assessment results by each method were compared and we could observe that the 5.1 method is superior to the other conventional methods.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.5
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• pp.185-190
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• 2006

The security analysis relates to the ability of the electric systems to survive sudden disturbances such as electric short circuits or unanticipated loss of system elements. It is composed of both steady state and dynamic security analyses, which are not two separate issues but should be considered together. In steady state security analysis including voltage security analysis, the analysis checks that the system is operated within security limits by OPF (optimal power flow) after the transition of a new operating point. On the other hand, dynamic security analysis deals that the transition will lead to an acceptable operating condition. Transient stability, which is the ability of power systems to maintain synchronism when subjected to a large disturbance, is a principal component in dynamic security analysis. Usually any loss of synchronism will cause additional outages. They make the present steady state analysis of the post-contingency condition inadequate for unstable cases. This is the reason of the need for dynamics of systems. Probabilistic criterion can be used to recognize the probabilistic nature of system components and shows the possibility of system security. A comprehensive conceptual framework for probabilistic static and dynamic assessment is presented in this paper. The simulation results of the Western System Coordinating Council (WSCC) system compare an analytical method with Monte-Carlo simulation (MCS). Also, a case study of the extended IEEE Reliability Test System (RTS) shows the efficiency of this approach.

• Steel and Composite Structures
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• v.39 no.3
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• pp.243-259
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• 2021

In the present paper, a Monte Carlo-based framework is developed to investigate the accuracy and reliability of analytical fragility curves of steel moment-resisting frames and simple SDOF systems. It is also studied how the effectiveness of incremental dynamic analysis (IDA) and multiple stripes analysis (MSA) approaches, as two common nonlinear dynamic analysis methods, are influenced by the number of records and analysis stripes in fragility curves producing. Results showed that the simple SDOF systems do not provide accurate and reliable fragility curves compared with realistic steel moment-resisting structures. It is demonstrated that, the effectiveness of nonlinear dynamic analysis approaches is dependent on the fundamental period of structures, where in short-period structures, IDA is found to be more effective approach compared with MSA. This difference between the effectiveness of two analysis approaches decreases as the fundamental period of structures become longer. Using of 2 or 3 analysis stripes in MSA approach leads to significant inaccuracy and unreliability in the estimated fragility curves. Additionally, 15 number of ground motion records is recommended as a threshold of significant unreliability in estimated fragility curves, constructed by MSA.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.1
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• pp.24-27
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• 2018

The performance measure of airborne radars is the range at which the cumulative probability of detection has some specified value, because the per-scan detection probability is an oscillatory function of the target range in airborne radars operating with the dynamic clutter environment. As a result, no one range, at which the per-scan detection probability has a given value, can give a meaningful description of the range performance. In this paper, we provide the equation to calculate the cumulative detection probability and show that the result of Monte Carlo simulation is same as the calculated value in a simple scenario. This verified Monte Carlo model will be used to evaluate the performance of airborne radars in various operating scenarios, at which the numerical calculation is difficult.

• Structural Engineering and Mechanics
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• v.63 no.1
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• pp.47-53
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• 2017

The fundamental goal of this study is to minimize the uncertainty of the median fragility curve and to assess the structural vulnerability under earthquake excitation. Bayesian Inference with Markov Chain Monte Carlo (MCMC) simulation has been presented for efficient collapse response assessment of the independent intake water tower. The intake tower is significantly used as a diversion type of the hydropower station for maintaining power plant, reservoir and spillway tunnel. Therefore, the seismic fragility assessment of the intake tower is a pivotal component for estimating total system risk of the reservoir. In this investigation, an asymmetrical independent slender reinforced concrete structure is considered. The Bayesian Inference method provides the flexibility to integrate the prior information of collapse response data with the numerical analysis results. The preliminary information of risk data can be obtained from various sources like experiments, existing studies, and simplified linear dynamic analysis or nonlinear static analysis. The conventional lognormal model is used for plotting the fragility curve using the data from time history simulation and nonlinear static pushover analysis respectively. The Bayesian Inference approach is applied for integrating the data from both analyses with the help of MCMC simulation. The method achieves meaningful improvement of uncertainty associated with the fragility curve, and provides significant statistical and computational efficiency.

• Steel and Composite Structures
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• v.8 no.2
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• pp.129-144
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• 2008

This paper demonstrates an application of the perturbation based stochastic finite element method (SFEM) for predicting the performance of structural systems made of composite sections with random material properties. The composite member consists of materials in contact each of which can surround a finite number of inclusions. The perturbation based stochastic finite element analysis can provide probabilistic behavior of a structure, only the first two moments of random variables need to be known, and should therefore be suitable as an alternative to Monte Carlo simulation (MCS) for realizing structural analysis. A summary of stiffness matrix formulation of composite systems and perturbation based stochastic finite element dynamic analysis formulation of structural systems made of composite sections is given. Two numerical examples are presented to illustrate the method. During stochastic analysis, displacements and sectional forces of composite systems are obtained from perturbation and Monte Carlo methods by changing elastic modulus as random variable. The results imply that perturbation based SFEM method gives close results to MCS method and it can be used instead of MCS method, especially, if computational cost is taken into consideration.

• Journal of radiological science and technology
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• v.44 no.2
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• pp.109-115
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• 2021

In this study, a physical evaluation of internal radiation exposure in children was conducted using nuclear medicine test(Renal DTPA Dynamic Study) to simulate the distribution and effects of the radiation throughout the tracer kinetics over time. Monte Carlo simulations were performed to determine the internal medical radiation exposure during the tests and to provide basic data for medical radiation exposure management. Specifically, dose variability based on changes in the tracer kinetic was simulated over time. The internal exposure to the target organ (kidney) and other surrounding organs was then quantitatively evaluated and presented. When kidney function was normal, the dose to the target organ(kidney) was approximately 0.433 mGy/mCi, and the dose to the surrounding organs was approximately 0.138-0.266 mGy/mCi. When kidney function was abnormal, the dose to the surrounding organs was 0.228-0.419 mGy/mCi. This study achieved detailed radiation dose measurements in highly sensitive pediatric patients and enabled the prediction of radiation doses according to kidney function values. The proposed method can provide useful insights for medical radiation exposure management, which is particularly important and necessary for pediatric patients.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1991.10a
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• pp.69-72
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• 1991

The purpose of this study is to develop the reliability-based dynamic load model for bridges. Analytial procedure to calculate the dynamic load is developed. Truck traffic is simulated using Monte Carlo method. Static and dynamic loads(deflections) are plotted on the normal probability paper to estimate the mean maximum dynamic load in bridge lifetime. The results may be served as a basis for new LRFD bridge design code.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.167-173
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• 2005

This paper presents an autocorrelation test that is applicable to dynamic panel data models with serially correlated errors. The residual-based GMM t-test is a significance test that is applied after estimating a dynamic model by using the instrumental variable(IV) method and is directly applicable to any other consistently estimated residuals. Monte Carlo simulations show that the t-test has considerably more power than the $m_2$ test or the Sargan test under both forms of serial correlation (i.e., AR(1) and MA(1)).