• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.47-52
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• 2002

There are many factors in machine tool error. These are thermal deformation, geometric error, machine's part assembly error, error caused by tool bending. Among them thermal error is 70% of total error of machine tool . Prediction of thermal error is very difficult. because of nonlinear tendency of machine tool deformation. In this study, we tried thermal error prediction by using multi regression analysis.

• International Journal of Ocean Engineering and Technology Speciallssue:Selected Papers
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• v.3 no.1
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• pp.29-34
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• 2000

This paper proposes a long-term prediction of offshore structures in ocean waves. All short-term statistics is generated by the simulation for all the combinations of significant wave heights and spectral peak periods. The simulation has been tested first on linear system, whose analytic solution is known, to verify if the simulation works accurately. Then the scheme was applied to the nonlinear system. This paper demonstrated that the proposed scheme could be an efficient tool in estimating the response of offshore structures.

• Journal of the Korean Geotechnical Society
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• v.16 no.4
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• pp.5-16
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• 2000

THe purpose of this paper is to suggest the analytical method which can predict lateral nonlinear behavior in non-homogeneous soil using the coefficient of soil resistance and ultimate soil resistance. Those parameters are obtained through back analysis on the base of the results of a series of model tests.Analytical method of Chang is more or less difficult to predict nonlinear behavior in non-homogeneous sol. So, in this study, for the prediction of nonlinear behavior the compositive analytical method which apply the p - y curve to Chang model is suggested. Also, the program is developed to predict nonlinear behavior using the compositive analytical method and it can be used to calculated the deflection, bending moment and soil reaction with DFM in non-homogeneous soil. To establish applicability of the suggested analytical method, the results of model tests and field tests and Pentagon2D finite element program are compared with those of the compositive analytical method. In the analysis values of the coefficient of soil reaction and ultimate soil resistance are also applied to the case of non-homogeneous soil. Lateral defection calculated using the compositive analytical method has been found to be in good agreement with values measured in field and model load tests.

• Journal of Information Technology Applications and Management
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• v.11 no.1
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• pp.117-135
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• 2004

Since human decision making behavior is likely to follow nonlinear strategy, it is conjectured that the human decision making behavior can be modeled better by nonlinear models than by linear models. All that linear models can do is to approximate rather than model the decision behavior. This study attempts to test this conjecture by analyzing human decision making behavior and combining the results of the analysis with predictive performance of both linear models and nonlinear models. In this way, this study can examine the relationship between the predictive performance of models and the existence of valid nonlinear strategy in decision making behavior. This study finds that the existence of nonlinear strategy in decision making behavior is highly correlated with the validity of the decision (or the human experts). The second finding concerns the significant correlations between the model performance and the existence of valid nonlinear strategy which is detected by Lens Model. The third finding is that as stronger the valid nonlinear strategy becomes, the better nonlinear models predict significantly than linear models. The results of this study bring an important concept, validity of nonlinear strategy, to modeling human experts. The inclusion of the concept indicates that the prior analysis of human judgement may lead to the selection of proper modeling algorithm. In addition, lens Model Analysis is proved to be useful in examining the valid nonlinearity in human decision behavior.

• Journal of the Korean Institute of Telematics and Electronics
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• v.10 no.6
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• pp.45-55
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• 1973

This paper discusses the nonlinear time-invarient circuit composed of a tunnel diode. Prior to determine the solution of the nonlinear network which has negative resistance elements, the static characteristics of the nonlinear resistance elements need to be represented by function. Polynomial curve fitting is discussed to represent the static characteristies by least squares approximation. In order to solve the nonlinear network, the state equations for the networks are set up and solved by prediction corrector method. Finally, the limit cycle is plotted to discuss the stability of the nonlinear network and the oscillation condition.

• Journal of computational fluids engineering
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• v.8 no.2
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• pp.57-63
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• 2003

Two nonlinear κ-ε models with the wall function method are applied to the fully developed turbulent flow in a square duct. Typical predicted quantities such as axial and secondary velocities, turbulent kinetic energy and Reynolds stresses are compared in details both qualitatively and quantitatively with each other. A nonlinear κ-ε model with the wall function method capable of predicting accurately duct flows involving turbulence-driven secondary motion is presented in the present paper. The nonlinear κ-ε model of Shih et al.[1] adopted in a commercial code is found to be unable to predict accurately duct flows with the prediction level of secondary flows one order less than that of the experiment.

• Journal of computational fluids engineering
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• v.8 no.2
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• pp.8-15
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• 2003

Three nonlinear κ-ε models with the wall function method are applied to the fully developed turbulent flow in a triangular subchannel of a bare rod bundle. Typical predicted quantities such as axial and secondary velocities, turbulent kinetic energy and wall shear stress are compared in details both qualitatively and quantitatively with both each other and experimental data. The nonlinear κ-ε models by Speziale[1] and Myong and Kasagi[2] are found to be capable of predicting accurately noncircular duct flows involving turbulence-driven secondary motion. The nonlinear κ-ε model by Shih et aL.[3] adopted in a commercial code is found to be unable to predict accurately noncircular flows with the prediction level of secondary flows one order less than that of the experiment.

• Journal of computational fluids engineering
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• v.8 no.1
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• pp.23-29
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• 2003

Two nonlinear κ-ε models with the wall function method are applied to the fully developed turbulent flow in a square duct. Typical predicted quantities such as axial and secondary velocities, turbulent kinetic energy and Reynolds stresses are compared in details both qualitatively and quantitatively with each other. A nonlinear κ-ε model with the wall function method capable of predicting accurately duct flows involving turbulence-driven secondary motion is presented in the present paper. The nonlinear κ-ε model of Shih et al.[1] adopted in a commercial code is found to be unable to predict accurately duct flows with the prediction level of secondary flows one order less than that of the experiment.

• Journal of Mechanical Science and Technology
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• v.19 no.7
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• pp.1517-1525
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• 2005

Liquid sloshing displays the highly nonlinear free surface fluctuation when either the external excitation is of large amplitude or its frequency approaches natural sloshing frequencies. Naturally, the accurate tracking of time-varying free surface configuration becomes a key task for the reliable prediction of the sloshing time-history response. However, the numerical instability and dissipation may occur in the nonlinear sloshing analysis, particularly in the long-time beating simulation, when two simulation parameters, the relative time-increment parameter a and the fluid mesh pattern, are not elaborately chosen. This paper intends to examine the effects of these two parameters on the potential-based nonlinear finite element method introduced for the large amplitude sloshing flow.

• Computers and Concrete
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• v.22 no.6
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• pp.539-550
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• 2018

Concrete is highly non-linear material which is originating from the transition zone in the form of micro-cracks, governs material response under various loadings. In this paper, the constitutive models published by many researchers have been used to generate novel stiffness parameters and constitutive curves for concrete. Following such linear material formulations, where the energy is conservative during the curvature, and a nonlinear contribution to the concrete has been made and investigated. In which, nonlinear concrete elastic modulus modeling has been developed that is capable-of representing concrete elasticity for grades ranging from 10 to 140 MPa. Thus, covering the grades range of concrete up to the ultra-high strength concrete, and replacing many concrete models that are valid for narrow ranges of concrete strength grades. This has been followed by the introduction of the nonlinear Hooke's law for the concrete material through the replacement of the Young constant modulus with the nonlinear modulus. In addition, the concept of concrete elasticity index (${\varphi}$) has been proposed and this factor has been introduced to account for the degradation of concrete stiffness in compression under increased loading as well as the multi-stages micro-cracking behavior of concrete under uniaxial compression. Finally, a sub-routine artificial neural network model has been developed to capture the concrete behavior that has been introduced to facilitate the prediction of concrete properties under increased loading.