• Journal of the Korean Statistical Society
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• v.25 no.3
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• pp.369-379
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• 1996

A study is made of approximate technique for structural reanalysis based on the force method. Perturbntion analysis of generalized least squares problem is adopted to reanalyze a damaged structure, and related results are presented.

• Smart Structures and Systems
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• v.15 no.1
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• pp.57-80
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• 2015

Extended Kalman Filter (EKF) has been widely used for structural identification and damage detection. However, conventional EKF approaches require that external excitations are measured. Also, in the conventional EKF, unknown structural parameters are included as an augmented vector in forming the extended state vector. Hence the sizes of extended state vector and state equation are quite large, which suffers from not only large computational effort but also convergence problem for the identification of a large number of unknown parameters. Moreover, such approaches are not suitable for intelligent structural damage detection due to the limited computational power and storage capacities of smart sensors. In this paper, a two-stage and two-step algorithm is proposed for the identification of structural damage as well as unknown external excitations. In stage-one, structural state vector and unknown structural parameters are recursively estimated in a two-step Kalman estimator approach. Then, the unknown external excitations are estimated sequentially by least-squares estimation in stage-two. Therefore, the number of unknown variables to be estimated in each step is reduced and the identification of structural system and unknown excitation are conducted sequentially, which simplify the identification problem and reduces computational efforts significantly. Both numerical simulation examples and lab experimental tests are used to validate the proposed algorithm for the identification of structural damage as well as unknown excitations for structural health monitoring.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1992.04a
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• pp.58-64
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• 1992

It is usual that underground structures are constructed within multi-layered medium. In this paper, an efficient numerical model ling of multi-layered structural systems is studied using coupled analysis of finite elements and boundary elements. The finite elements are applied to the area in which the material nonlinearity is dominated, and the boundary elements are applied to the far field area where the nonlinearity is relatively weak. In the boundary element model 1 ins of the multi-layered medium, fundamental solutions are restricted. Thus, methods which can utilize existing Kelvin and Melan solution are sought for the interior multi-layered domain problem and semi infinite domain problem. Interior domain problem which has piecewise homogeneous layers is analyzed using boundary elements with Kelvin solution; by discretizing each homogeneous subregion and applying compatibility and equilibrium conditions between interfaces. Semi-infinite domain problem is analyzed using boundary elements with Melan solution, by superposing unit stiffness matrices which are obtained for each layer by enemy method. Each methodology is verified by comparing its results which the results from the finite element analysis and it is concluded that coupled analysis using boundary elements and finite elements can be reasonable and efficient if the superposition technique is applied for the multi-layered semi-infinite domain problems.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1990.10a
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• pp.22-27
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• 1990

Since an eigenvalue problem in structural analysis has been recognized as an important process for the assessment of structural strength, it is usually to be carried out the eigenvalue analysis or buckling analysis of structures when the compression behabiour of the member is dorminant. In general, various variables involved in the eigenvalue problem have also shown their variability. So it is natural to apply the probabilistic analysis into such problem. Since the limit state equation for the eigenvalue analysis or buckling reliability analysis is expressed implicitly in terms of random variables involved, the probabilistic finite element method is combined with the conventional reliability method such as MVFOSM and AFOSM for the determination of probability of failure due to buckling. The accuracy of the results obtained by this method is compared with results from the Monte Carlo simulations. Importance sampling method is specially chosen for overcomming the difficulty in a large simulation number needed for appropriate accurate result. From the results of the case study, it is found that the method developed here has shown good performance for the calculation of probability of buckling failure and could be used for checking the safety of the calculation of probability of buckling failure and could be used for checking the safely of frame structure which might be collapsed by either yielding or buckling.

• Advances in Computational Design
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• v.2 no.4
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• pp.273-281
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• 2017

In this work, a comparative study of multi-objective meta-heuristics (MOMHs) for optimum design of a walking tractor handlebar is conducted in order to reduce the structural mass and increase structural static and dynamic stiffness. The design problem has objective functions as maximising structural natural frequencies, minimising structural mass, bending deflection and torsional deflection with stress constraints. The problem is classified as a many-objective optimisation since there are more than three objectives. Design variables are structural shape and size. Several well established multi-objective optimisers are employed to solve the proposed many-objective optimisation problems of the walking tractor handlebar. The results are compared whereas optimum design solutions of the walking tractor handlebar are illustrated.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.203-210
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• 2002

The great advantages on the Genetic Algorithms(GAs) are ease of implementation, and robustness in solving a wide variety of problems, several GAs based optimization models for solving complex structural problems were proposed. However, there are two major disadvantages in GAs. The first disadvantage, implementation of GAs-based optimization is computationally too expensive for practical use in the field of structural optimization, particularly for large-scale problems. The second problem is too difficult to find proper parameter for particular problem. Therefore, in this paper, a Distributed Hybrid Genetic Algorithms(DHGAs) is developed for structural optimization on a cluster of personal computers. The algorithm is applied to the minimum weight design of steel structures.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.09a
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• pp.497-504
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• 2003

An optimal design method for hybrid structural control system of building structures subject to earthquake excitation is presented in this paper. Designing a hybrid structural control system nay be defined as a process that optimizes the capacities and configuration of passive and active control systems as well as structural members. The optimal design proceeds by formulating the optimization problem via a multi-stage goal programming technique and, then, by finding reasonable solution to the optimization problem by means of a goal-updating genetic algorithm. The process of the integrated optimization design is illustrated by a numerical simulation of a nine-story building structure subject to earthquake excitation. The effectiveness of the proposed method is demonstrated by comparing the optimally designed results with those of a hybrid structural control system where structural members, passive and active control systems are uniformly distributed.

• Journal of Families and Better Life
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• v.29 no.4
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• pp.161-174
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• 2011

The purpose of this study was to investigate the structural relationships among different variables related to school adjustment. 601 elementary school students residing in Pohang-City in Korea completed questionnaires about school adjustment, internal problem behavior, external problem behavior, family adaptability and family cohesion. A variance-covariance matrix of this sample was analyzed using AMOS 19.0, and the maximum likelihood minimization function. The goodness of fit was evaluated via SRMR, RMSEA with a 90% confidence interval, CFI, and TLI. The results were as follows: First, family adaptability, family cohesion, internal problem behavior and external problem behavior were all found to have a significant direct effect how the children adjusted to their school. Second, family adaptability, and family cohesion had a direct effect on internal problem behavior. Third, family cohesion had a direct effect on external problem behavior, but family adaptability had a substantial indirect effect on the children's external problem behavior that was mediated by their internal problem behavior. Fourth, internal problem behavior had a direct effect on external problem behavior.

• Journal of the Korean School Mathematics Society
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• v.13 no.2
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• pp.205-224
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• 2010

This paper examined what structural relationship metacognition and flow, which are identified as major variables that positively influence creative problem solving ability, had with mathematics creative problem solving ability. For this purpose, the Mathematics Creative Problem Solving Ability Test (MCPSAT) was given go 196 general second-year middle school students, and their cognitive and affective states were measured with metacognition and flow tests. The three variables' relationships were examined through a correlation analysis and, through structural equation modeling, the mediating effect of flow was tested in the structural relationships between the three variables and in the relationship between metacognition and mathematics creative problem solving ability. The results of the research show that metacognition did not directly influence mathematics creative solving ability, but exerted influence through the mediating variable of flow. A more detailed examination shows that while metacognition did not influence fluency and originality from among the measured variables for mathematics creative problem solving ability, it did directly influence flexibility. In particular, metacognition's indirect influence through the mediating variable of flow was shown to be much stronger than its direct influence on flexibility. This research showed that the students' high metacognition ability increased flow degree in the problem solving process, and problem solving in this state of flow increased their mathematics creative problem solving ability.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.140-146
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• 2020

This study aimed to provide basic data for enhancing the structural relationship among learning motivation, learning confidence, critical thinking skill and problem-solving ability in junior high school students and factors influencing problem-solving ability, by closely examining them. To this end, it investigated the causality among variables, for 390 junior high school students in Gangwondo, based on the outcomes of a questionnaire survey conducted to verify the effectiveness of digital textbooks. Although learning motivation did not have a significant effect on critical thinking skill, learning confidence had a direct effect on it. In addition, learning motivation, learning confidence and critical thinking skill had direct effects on problem-solving ability. In order to enhance problem-solving ability, therefore, We may be necessary to make efforts to support learning capabilities and provide opportunities for them to experience rich learning and resources.