• Communications of the Korean Mathematical Society
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• v.17 no.2
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• pp.309-319
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• 2002

We consider the nonlinear autoregressive model with nonlinear ARCH errors, and find sufficient conditions for the existence of a strictly stationary process. New results are obtained, and known results are shown to emerge as special oases.

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.783-791
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• 2004

In this paper we review recent developments in nonlinear time series modeling on both conditional mean and conditional variance. Traditional linear model in conditional mean is referred to as ARMA(autoregressive moving average) process investigated by Box and Jenkins(1976). Nonlinear mean models such as threshold, exponential and random coefficient models are reviewed and their characteristics are explained. In terms of conditional variances, ARCH(autoregressive conditional heteroscedasticity) class is considered as typical linear models. As nonlinear variants of ARCH, diverse nonlinear models appearing in recent literature including threshold ARCH, beta-ARCH and Box-Cox ARCH models are remarked. Also, a class of unified nonlinear models are considered and parameter estimation for that class is briefly discussed.

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.311-321
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• 2002

Transfer function model(TFM) capturings conditional heteroscedastic pattern is introduced to analyze stochastic regression relationship between the two time series. Nonlinear ARCH concept is incorporated into the TFM via threshold ARCH and beta- ARCH models. Steps for statistical analysis of the proposed model are explained along the lines of the Box & Jenkins(1976, ch. 10). For illustration, dynamic analysis between KOSPI and NASDAQ is conducted from which it is seen that threshold ARCH performs the best.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.565-572
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• 2001

This article explores the problem of ergodicity for the nonlinear autoregressive processes with ARCH structure in a very general setting. A sufficient condition for the geometric ergodicity of the model is developed along the lines of Feigin and Tweedie(1985), thereby extending classical results for specific nonlinear time series. The condition suggested is in turn applied to some specific nonlinear time series illustrating that our results extend those in the literature.

• Structural Engineering and Mechanics
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• v.35 no.5
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• pp.555-570
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• 2010

Shallow fixed arches have a nonlinear primary equilibrium path with limit points and an unstable postbuckling equilibrium path, and they may also have bifurcation points at which equilibrium bifurcates from the nonlinear primary path to an unstable secondary equilibrium path. When a shallow fixed arch is subjected to a central step load, the load imparts kinetic energy to the arch and causes the arch to oscillate. When the load is sufficiently large, the oscillation of the arch may reach its unstable equilibrium path and the arch experiences an escaping-motion type of dynamic buckling. Nonlinear dynamic buckling of a two degree-of-freedom arch model is used to establish energy criteria for dynamic buckling of the conservative systems that have unstable primary and/or secondary equilibrium paths and then the energy criteria are applied to the dynamic buckling analysis of shallow fixed arches. The energy approach allows the dynamic buckling load to be determined without needing to solve the equations of motion.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.185-192
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• 2002

In this study, we choose the sinusoidal shaped arch with pin-ends subjected to sinusoidal distributed excitation to investigate the fundamental mechanism of the dynamic instability. We derive the nonlinear equations of motion to investigate the instability phenomenon of arch structures and Identify the buckling characteristics of sinusoidal shaped arch structures through the nonlinear eigenvalue analysis with discreted equations of motion by Galerkin's method. We examine that phenomenons which direct snapping and indirect snapping with backbone curves to understand occurrence paths of the dynamic buckling.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.293-303
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• 2003

Under the case that we know the period and the reason of external events, we reviewed the method of model identification, parameter estimation and model diagnosis with the former papers that have been studied about the linear time series model with intervention, and compared with nonlinear time series model such as ARCH, GARCH model that it has been used widely in economic models, and also we compared with the combination prediction method that Tong(1990) introduced.

• Structural Engineering and Mechanics
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• v.14 no.3
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• pp.331-343
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• 2002

Because of the increasing span of arch bridges, ultimate capacity analysis recently becomes more focused both on design and construction. This paper investigates the static and ultimate behavior of a long-span steel arch bridge up to failure and evaluates the overall safety of the bridge. The example bridge is a long-span steel arch bridge with a 550 m-long central span under construction in Shanghai, China. This will be the longest central span of any arch bridge in the world. Ultimate behavior of the example bridge is investigated using three methods. Comparisons of the accuracy and reliability of the three methods are given. The effects of material nonlinearity of individual bridge element and distribution pattern of live load and initial lateral deflection of main arch ribs as well as yield stresses of material and changes of temperature on the ultimate load-carrying capacity of the bridge have been studied. The results show that the distribution pattern of live load and yield stresses of material have important effects on bridge behavior. The critical load analyses based on the linear buckling method and geometrically nonlinear buckling method considerably overestimate the load-carrying capacity of the bridge. The ultimate load-carrying capacity analysis and overall safety evaluation of a long-span steel arch bridge should be based on the geometrically and materially nonlinear buckling method. Finally, the in-plane failure mechanism of long-span steel arch bridges is explained by tracing the spread of plastic zones.

• Journal of Korean Society of Steel Construction
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• v.17 no.2 s.75
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• pp.161-171
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• 2005

When the in-plane flexural rigidity is small in relation to the applied load, the arch ribs may buckle to the in-plane direction. Designers should therefore determine the in-plane buckling strength. To determine the buckling strength of arch ribs, designers have to consider the material nonlinear response. But in the case of arch ribs having large slenderness ratio, arch ribs may buckle in the elastic range, and when the arch ribs have low slenderness ratio, elastic buckling strength is useful in the preliminary design. In this paper, elastic buckling strength of arch ribs, which are frequently used in practical design, is studied using nonlinear finite element method. In general, the relation between flexural rigidity and elastic buckling strength is linear. As seen from the results, however, when the arch ribs have low slenderness ratio, the relation between flexural rigidity and elastic buckling strength is nonlinear.

• Journal of the Korean Society of Hazard Mitigation
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• v.5 no.3 s.18
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• pp.57-65
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• 2005

When arch ribs are subjected unsymmetrical load, buckling strength Is lower than strength of arch ribs subjected symmetrical load. However, A few study about the buckling strength of arch ribs subjected unsymmetrical load is performed compare with study about arch ribs subjected symmetrical load. Several researchers(Deutch : 1940, Chang : 1973, Harrison : 1982) studied about arch ribs subjected unsymmetrical load and they found that unsymmetrical loading reduces the critical buckling load. But, their results are limited parabolic arch ribs. This paper focuses on circular arch ribs subjected to unsymmetrical loading. The result shows that the ratio of live and dead load length to cause smallest critical buckling load of arch ribs is $0.6{\sim}0.7$ under geometric nonlinear condition and $0.5{\sim}0.6$ under both material and geometrical nonlinear conditions.