• Journal of the Korea Concrete Institute
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• v.17 no.4 s.88
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• pp.551-558
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• 2005

The setting and hardening of concrete is accompanied with nonlinear temperature distribution caused by development of hydration heat of cement. Especially at early ages, this nonlinear distribution has a large influence on the crack evolution. As a result, in order to predict the exact temperature history in concrete structures it is required to examine thermal properties of concrete. In this study, the convection heat transfer coefficient which presents thermal transfer between surface of concrete and air, was experimentally investigated with variables such as velocity of wind, curing condition and ambient temperature. At initial stage, the convection heat transfer coefficient is overestimated by the evaporation quantity. So it is essential to modify the thermal equilibrium considered with the boiling effect. From experimental results, the convection heat transfer coefficient was calculated using equations of thermal equilibrium. Finally, the prediction model for equivalent convection heat transfer coefficient including effects of velocity of wind, curing condition, ambient temperature and boiling effects was theoretically proposed. The convection heat transfer coefficient in the proposed model increases with velocity of wind, and its dependance on wind velocity is varied with curing condition. This tendency is due to a combined heat transfer system of conduction through form and convection to air. From comparison with experimental results, the convection heat transfer coefficient by this model was well agreed with those by experimental results.

• Journal of Astronomy and Space Sciences
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• v.26 no.1
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• pp.75-88
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• 2009

The main purpose of the current research is to introduce the alternative algorithm of the non-recursive batch filter based on the unscented transformation in which the linearization process is unnecessary. The presented algorithm is applied to the orbit determination of a low earth orbiting satellite and compared its results with those of the well-known Bayesian batch least squares estimation and the iterative UKF smoother (IUKS). The system dynamic equations consist of the Earth's geo-potential, the atmospheric drag, solar radiation pressure and the lunar/solar gravitational perturbations. The range, azimuth and elevation angles of the satellite measured from ground stations are used for orbit determination. The characteristics of the non recursive unscented batch filter are analyzed for various aspects, including accuracy of the determined orbit, sensitivity to the initial uncertainty, measurement noise and stability performance in a realistic dynamic system and measurement model. As a result, under large non-linear conditions, the presented non-recursive batch filter yields more accurate results than the other batch filters about 5% for initial uncertainty test and 12% for measurement noise test. Moreover, the presented filter exhibits better convergence reliability than the Bayesian least squares. Hence, it is concluded that the non-recursive batch filter based on the unscented transformation is effectively applicable for highly nonlinear batch estimation problems.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.56-64
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• 1995

The least mean fourth (LMF) adaptive algorithm is a stochastic gradient method that minimizes the error in the mean fourth sense. Despite its potential advantages, the algorithm is much less popular than the conventional least mean square (LMS) algorithm in practice. This seems partly because the analysis of the LMF algorithm is much more difficult than that of the LMS algorithm, and thus not much still has been known about the algorithm. In this paper, we explore the statistical convergence behavior of the LMF algorithm when the input to the adaptive filter is zero-mean, wide-sense stationary, and Gaussian. Under a system idenrification mode, a set of nonlinear evolution equations that characterizes the mean and mean-squared behavior of the algorithm is derived. A condition for the conbergence is then found, and it turns out that the conbergence of the LMF algorithm strongly depends on the choice of initial conditions. Performances of the LMF algorithm are compared with those of the LMS algorithm. It is observed that the mean convergence of the LMF algorithm is much faster than that of the LMS algorithm when the two algorithms are designed to achieve the same steady-state mean-squared estimation error.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.89-102
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• 2001

Using a multiproduct translog cost function model, this paper examines the existence or absence of scale and scope economies in Seoul's urban bus industry. The Paper then conceptualizes that the bus firm produces three outputs (city, seat and local bus-kilometers) using low input factors(labor, capital, fuel and maintenance). Using 1996 annual observations for 81 Seoul's bus firms, the equation system consisting of a cost function and three input share equations is estimated with the nonlinear iterative Zellner method. The findings show that the cost function corresponding to a non-homothetic production technology with separability between local bus outputs and inputs adequately represents the structure of cost for Seoul's bus firms, and that the demand lot all input factors is quite inelastic with respect to their own price. On the other hand, nearly all firms experience mild overall economies or scale, but rather marked product-specific economies of scale with respect to all the three outputs. In addition, there appear to be substantial economies or scope associated with the joint production of city and seat bus services, while considerable diseconomies of scope associated with that of city and local bus services. These results indicate that the merger of smaller firms into larger firms with a fleet of approximately 200 buses would result in more cost-efficient bus services.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.6
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• pp.751-759
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• 2007

We have developed several methods for the optimization problem having large-scale and highly nonlinear system. First, step by step method in optimization process was employed to improve the convergence. In addition, techniques of furnishing good initial guesses for analysis using sensitivity information acquired from optimization iteration, and of manipulating analysis/optimization convergency criterion motivated from simultaneous technique were used. We applied them to flow control problem and verified their efficiency and robustness. However, they are based on quasi-Newton method that approximate the Hessian matrix using exact first derivatives. However solution of the Navier-Stokes equations are very cost, so we want to improve the efficiency of the optimization algorithm as much as possible. Thus we develop a true Newton method that uses exact Hessian matrix. And we apply that to the three-dimensional problem of flow around a sphere. This problem is certainly intractable with existing methods for optimal flow control. However, we can attack such problems with the methods that we developed previously and true Newton method.