• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.4
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• pp.44-50
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• 2010

Structural vibration is a significant problem in many multi-part or multi-component assemblies. In aircraft industry, structures are composed of various fasteners, such as bolts, snap, hinge, weld or other fastener or connector (collectively "fasteners"). Due to these, prediction and design involving dynamic characteristics is quite complicated. However, the current state of the art does not provide an analytical tool to effectively predict structure's dynamic characteristics, because consideration of structural uncertainties (i.e. material properties, geometric tolerance, dimensional tolerance, environment and so on) is difficult and very small fasteners in the structure cause a huge amount of analysis time to predict dynamic characteristics using the FEM (finite element method). In this study, to resolve the current state of the art, a new approach is proposed using the FEM and probabilistic analysis. Firstly, equivalent elements are developed using simple element (e.g. bar, beam, mass) to replace fasteners' finite element model. Developed equivalent elements enable to explain static behavior and dynamic behavior of the structure. Secondly, probabilistic analysis is applied to evaluate the PDF (probability density function) of dynamic characteristics due to tolerance, material properties and so on. MCS (Monte-Carlo simulation) is employed for this. Proposed methodology offers efficiency of dynamic analysis and reality of the field as well. Simple plates joined by fasteners are taken as an example to illustrate the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.544-547
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• 1997

In this paper, we propose a dynamic localization method using a rotating sonar and a map. The proposed method is implemented by using extended Kalman filter. The state equation is based on the encoder propagation model and the encoder error model, and the measurement equation is a map-based measurement equation using a rotating sonar sensor. By utilizing sonar beam characteristics, map-based measurements are updated while AMR is moving continuously. By modeling and estimating systematic errors of a differential encoder, the position is successfully estimated even the interval of the map-based measurement. Monte-Carlo simulation shows that the proposed global position estimator has the performance of a few millimeter order in position error and of a few tenth degrees in heading error and of compensating systematic errors of the differential encoder well.

• Proceedings of the IEEK Conference
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• 2000.06b
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• pp.111-114
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• 2000

Single Electron Transistor Logic (SETL) can be characterized by HSPICE simulation using a SPICE macro model. First, One unit SET is characterized by Monte-carlo simulation and then we fit SPICE macro-modeling equations to its characteristics. Second, using this unit SET, we simulate the transient characteristics of two-input NAND gate in both the static and dynamic logic schemes. The dynamic logic scheme shows more stable operation in terms of logic-swing and on/off current ratio. Also, there is a merit that we can use the SET only as current on-off switch without considering the voltage gain.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.399-406
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• 1998

An investigation into the stochastic bifurcation and response statistits of an autoparameteric system under broad-band random excitation is made. The specific system examined is a spring-pendulum system with internal resonance, which is known to be a good model for a variety of engineering systems, including ship motions with nonlinear coupling between pitching and rolling motions. The Fokker-Planck equations is used to generate a general first-order differential equation in the dynamic moment of response coordinates. By means of the Gaussian and non-Gaussian closure methods the dynamic moment equations for the random responses of the system are reduced to a system of autonomous ordinary differential equations. In view of equilibrium solutions of this system and their stability we examine the stochastic bifurcation and response statistics. The analytical results are compared with results obtained by Monte Carlo simulation.

• Proceedings of the KIEE Conference
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• 2005.11b
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• pp.35-38
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• 2005

This paper suggests the method that forecast Dynamic Line Rating (DLR). Thermal Overload Risk (TOR) of next time is forecasted based on current weather condition and DLR value by Monte Carlo Simulation (MCS). To model weather element of transmission line for MCS, we will propose the use of weather forecast system and statistical models that time series law is applied. Also, through case study, forecasted TOR probability confirmed can utilize by standard that decide DLR of next time. In short, proposed method may be used usefully to keep safety of transmission line and reliability of supply of electric Power by forecasting transmission capacity of next time.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.813-817
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• 2002

This paper presents the reliability analysis technique on the dynamic characteristics of the torsion beam consisting the suspension system of passenger car. We utilize response surface method (RSM) and Monte Carlo simulation to obtain the response surface model that describes the limit state function for the natural frequencies of the torsion beam. Using the response surface model and the design optimization technique, we have obtained the optimized section considering the reliability of the torsion beam structure.

• Journal of Industrial Technology
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• v.23 no.A
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• pp.15-20
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• 2003

Stochastic simulation technique has advantages over deterministic simulation in various engineering analysis, since stochastic simulation can take into consideration of scattering of various design variables, which is inherent characteristics of physical world. In this work, Monte-Carlo simulation mothod in ADAMS/Insight for steady-state cornering and J-turn behavior of a truck with design variables like hard points and busing stiffnesses have performed to achieve better dynamic performance. The main purpose is to improve understeer gradient at steady-state cornering and minimize peak lateral acceleration and peak yaw rate at J-turn. 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.

• Earthquakes and Structures
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• v.5 no.3
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• pp.359-378
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• 2013

The problem of identification of multi-component and (or) spatially varying earthquake support motions based on measured responses in instrumented structures is considered. The governing equations of motion are cast in the state space form and a time domain solution to the input identification problem is developed based on the Kalman and particle filtering methods. The method allows for noise in measured responses, imperfections in mathematical model for the structure, and possible nonlinear behavior of the structure. The unknown support motions are treated as hypothetical additional system states and a prior model for these motions are taken to be given in terms of white noise processes. For linear systems, the solution is developed within the Kalman filtering framework while, for nonlinear systems, the Monte Carlo simulation based particle filtering tools are employed. In the latter case, the question of controlling sampling variance based on the idea of Rao-Blackwellization is also explored. Illustrative examples include identification of multi-component and spatially varying support motions in linear/nonlinear structures.

• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.29-42
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• 2018

We combine the integer-valued GARCH(1, 1) model with a generalized regime-switching model to propose a dynamic count time series model. Our model adopts Markov-chains with time-varying dependent transition probabilities to model dynamic count time series called the generalized regime-switching integer-valued GARCH(1, 1) (GRS-INGARCH(1, 1)) models. We derive a recursive formula of the conditional probability of the regime in the Markov-chain given the past information, in terms of transition probabilities of the Markov-chain and the Poisson parameters of the INGARCH(1, 1) process. In addition, we also study the forecasting of the Poisson parameter as well as the cumulative impulse response function of the model, which is a measure for the persistence of volatility. A Monte-Carlo simulation is conducted to see the performances of volatility forecasting and behaviors of cumulative impulse response coefficients as well as conditional maximum likelihood estimation; consequently, a real data application is given.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.838-843
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• 2005

The nonlinear characteristics of a suspension is directly related to the ride quality of a passenger car. In this study, a dynamic experiment for a spring and a damper of a passenger car is performed to analyze the nonlinear characteristics using MTS 1-axial testing machine and a mathematical nonlinear dynamic suspension model based on experimental data is devised to estimate the ride quality using Billings' method. The devised nonlinear model is applied to the ride quality analysis using K factor and the effect of suspension parameters is examined. As a result, the friction between the cylinder and the piston of a damper is the most effective parameter for the ride quality of a passenger car.