• Ocean and Polar Research
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• v.37 no.1
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• pp.1-9
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• 2015

An approach based on the combined use of a 2D shallow water model and analytical 1D long wave run-up theory is proposed which facilitates the forecasting of tsunami run-up heights in a more rapid way, compared with the statistical or empirical run-up ratio method or resorting to complicated coastal inundation models. Its application is advantageous for long-term tsunami predictions based on the modeling of many prognostic tsunami scenarios. The modeling of the Chilean tsunami on February 27, 2010 has been performed, and the estimations of run-up heights are found to be in good agreement with available observations.

• Tribology and Lubricants
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• v.14 no.1
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• pp.85-93
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• 1998

The Bair & Winer's limiting shear stress rheological model is incorporated into the Reynolds equation to successfully predict the traction and film thickness for an isothermal line contact using the primary rheological properties. The modified WLF viscosity model and Barus viscosity model are also adapted for the realistic prediction of EHD tractional behavior. The influences of the limiting shear stress and slide-roll ratio on the pressure spike, film thickness, distribution of shear stress and nonlinear variation of traction are examined. A good agreement between the disc machine experiments and numerical traction prediction has been established. The film thickness due to non-Newtonian effects does not deviate significantly from the fdm thicknesss with Newtonian lubricant.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.543-546
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• 1996

We propose a new visual tracking system for grasping which can find grasping points of an unknown polygonal object. We construct the system with the image prediction technique and Extended Kalman Filter algorithm. The Extended Kalman Filter(EKF) based on the SVD can improve the accuracy and processing time for the estimation of the nonlinear state variables. By using it, we can solve the numerical unstability problem that can occur in the visual tracking system based on Kalman filter. The image prediction algorithm can reduce the effect of noise and the image processing time. In the processing of a visual tracking, we can construct the parameterized family and can found the grasping points of unknown object through the geometric properties of the parameterized family.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.04a
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• pp.281-286
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• 1999

Nonlinear temperature distribution induced by the hydration heat generates thermal stress in mass concrete. At early ages, such thermal stress may induce thermal cracks in the structure which can affect on the durability and safety of the structure. Up to now, a lot of works have focused on the prediction of temperature distribution and thermal stress in the structure. In most of such works, however, the inside of structure was considered as adiabatic state to predict temperature distribution and the thermal stress. And due to the lacks of appropriate analysis models after crack, there was little research on the crack occurrence. This paper deals with the prediction of the temperature distribution in the structure using the rate of hydration heat generation and also estimates the behavior of structure before and after cracking due to hydration heat using crack band model.

• The KSFM Journal of Fluid Machinery
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• v.11 no.4
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• pp.14-21
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• 2008

The prediction for gaseous leak flows through a narrow crack is important for a leak-before-break (LBB) analysis. Therefore, the methodology to obtain the flow characteristics of gaseous leak flow in a narrow crack for the wide range by using the product of friction factor and Reynolds number correlations (fRe) for a micro-channel is developed and presented. The correlation applied here was proposed by the previous study. The fourth-order Runge-Kutta method was employed to integrate the nonlinear ordinary differential equation for the pressure and the regular-Falsi method was also employed to find the inlet Mach number. A narrow crack whose opening displacement ranges from 10 to $100{\mu}m$ with a crack length in the range from 2 to 200mm was chosen for sample prediction. The present results are compared with both numerical simulation results and available experimental measurements. The results are in excellent agreement with them. The leak flow rate can be approximately predicted by using proposed methodology.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1088-1090
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• 1999

The radio noise produced by corona discharge in high voltage transmission tines is one of the most important line design considerations. Therefore it is necessary to pre-evaluate radio noise for transmission line designers using Prediction formulas or field test results. In this Paper, more accurate and useful formulas for Predicting radio noise during fair and foul weathers in AC transmission lines were proposed through comparison with the existing formulas. Also it was verified by comparing with the long-term measured data from operating lines that the Proposed formulas are very accurate. The Proposed prediction formulas are developed by the applications of nonlinear least square optimization method to radio noise database collected from lines throughout the world.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.933-935
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• 1999

In this paper, we present model predictive control scheme based on neural network to control discrete-time chaotic systems. We use a feedforward neural network as nonlinear prediction model. The training algorithm used is an adaptive backpropagation algorithm that tunes the connection weights. And control signal is obtained by using gradient descent (GD), some kind of LMS method. We identify that the system identification results through model prediction control have a great effect on control performance. Finally, simulation results show that the proposed control algorithm performs much better than the conventional controller.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.1041-1044
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• 1988

This paper considers the design problem of adaptive filters based an the state-space models for linear discrete-time stationary stochastic signal processes. The adaptive state estimator consists of both the predictor and the sequential prediction error estimator. The discrete Chandrasakhar filter developed by author is employed as the predictor and the nonlinear least-squares estimator is used as the sequential prediction error estimator. Two models are presented for calculating the parameter sensitivity functions in the adaptive filter. One is the exact model called the linear innovations model and the other is the simplified model obtained by neglecting the sensitivities of the Chandrasekhar X and Y functions with respect to the unknown parameters in the exact model.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.99-104
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• 2001

Effect of mean stress on the fatigue life of natural rubber for engine mount was investigated. Fatigue damage parameter based on the maximum Green-Lagrange strain was employed to account for the effect of mean stress. A procedure to predict the fatigue life of rubber components based on the maximum Green-Lagrange strain method was proposed. Nonlinear finite element analysis and fatigue test of jang-gu shape specimen were conducted to predict the fatigue life of engine mount. Predicted fatigue lives have a good agreement with tested lives within a factor of 3.

• Structural Engineering and Mechanics
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• v.65 no.4
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• pp.447-452
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• 2018

The controlling and prediction of spring back is one of the most important factors in sheet metal forming processes which require high dimensional precision. The relationship between effective parameters and spring back phenomenon is highly nonlinear and complicated. Moreover, the objective function is implicit with regard to the design variables. In this paper, first the influence of some effective factors on spring back in U-die bending process was studied through some experiments and then regarding the robustness of artificial neural network (ANN) approach in predicting objectives in mentioned kind of problems, ANN was used to estimate a prediction model of spring back. Eventually, the spring back angle was optimized using the Imperialist Competitive Algorithm (ICA). The results showed that the employment of ANN provides us with less complicated and time-consuming analytical calculations as well as good results with reasonable accuracy.