• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.1
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• pp.81-88
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• 2009

This paper alined at the development of a lateral drift control method that is able to quantitatively control the lateral drift of global node. For this, we applied an efficient partial reanalysis algorithm. By using this algorithm, we could recalculate the displacement and member force of the specific node without reanalyzing the entire structure when member stiffness changes partially. The theoretical concepts of the algorithm are so simple that it is not necessary to solve the complicate differential equation or to repeat the analysis of entire structure. The proposed method calculates the drift contribution of each member for the global displacement according to the variation of section sizes by using the algorithm. Then by changing the member sizes as the order of drift contribution, we could control the lateral drift of global node with a minimum quantity of materials. 20 story braced frame structure system is presented to illustrate the usefulness of proposed method. It is shown that the proposed method is very effective in lateral drift control and the results obtained by proposed method are consistent with those of commercial analysis program.

• Journal of Korea Water Resources Association
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• v.52 no.1
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• pp.61-70
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• 2019

The modified Kling-Gupta efficiency fusion method to merge actual evapotranspiration was proposed and compared with the simple Taylor skill's score method using Global Land Data Assimilation System (GLDAS), Global Land Evaporation Amsterdam Model (GLEAM), MODIS Global Evapotranspiration Project (MOD16), and the flux tower on three different land cover types over the Korean peninsula and China. In the results of the weights estimated from two actual evapotranspiration merging techniques (i.e., STS and KGF), the weights of reanalysis data (i.e, GLDAS and GLEAM) in cropland and grassland showed similar performance, while the results of weights are different according to the merging techniques in forest. Both two merging techniques showed better results than original dataset in grassland and forest. However, there were no improvement in cropland compared to the other land cover types. The results of the KGF method slightly improved compared to those of the STS in grassland and forest.

• Journal of Power System Engineering
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• v.16 no.2
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• pp.11-16
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• 2012

In this paper, the authors formulate the sensitivity analysis algorithm for the natural frequency of a torsional shafting by expanding the transfer stiffness coefficient method. The basic concept of the present algorithm is based on the transfer of sensitivity stiffness coefficient, which is the derivative of stiffness coefficient with respect to design parameter, at every node from the first node to the last node in analytical model. The effectiveness of the present algorithm is confirmed by comparing the results of the sensitivity analysis and those of the reanalysis for the natural frequencies of a torsional shafting with a constant cross section. In numerical calculation, the design parameter is the diameter of the shaft element of the torsional shafting.

• Structural Engineering and Mechanics
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• v.37 no.5
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• pp.475-487
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• 2011

In a flexible multi-body dynamic system the typical topological optimization method for structures cannot be directly applied, as the stiffness varies with position. In this paper, the topological optimization of the flexible multi-body dynamic system is converted into structural optimization using the equivalent static load method. First, the actual boundary conditions of the control system and the approximate stiffness curve of the mechanism are obtained from a flexible multi-body dynamical simulation. Second, the finite element models are built using the absolute nodal coordination for different positions according to the stiffness curve. For efficiency, the static reanalysis method is utilized to solve these finite element equilibrium equations. Specifically, the finite element equilibrium equations of key points in the stiffness curve are fully solved as the initial solution, and the following equilibrium equations are solved using a reanalysis method with an error controlled epsilon algorithm. In order to identify the efficiency of the elements, a non-dimensional measurement is introduced. Finally, an improved evolutional structural optimization (ESO) method is used to solve the optimization problem. The presented method is applied to the optimal design of a die bonder. The numerical results show that the presented method is practical and efficient when optimizing the design of the mechanism.

• Computational Structural Engineering
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• v.25 no.4
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• pp.14-20
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• 2012

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.439-448
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• 2000

A multi-level design synthesis (MLDA) algorithm for efficiently optimizing orthotropic steel deck bridges is proposed in the paper, because it is usually very difficult to optimize orthotropic steel deck bridges using a conventional single-level (CSL) algorithn since the bridges have a large number of members and show complex structural behaviors. In the proposed MLDS algorithms a coordination method is introduced to divide the bridges into main girders and orthotropic steel decks and decomposition method is also used to reduce the number of design variables of the decks for system level optimization. For efficient optimization of the bridges the MLDS algorithm incorporates the crucial approximation techliques such as constraints deletion and stress reanalysis. The constraint deletion technique for deflection is found to be very useful for the optimization problem of the bridges, since a deflection constraint is usually inactive in the design. Considering the complex system of the bridges, the proposed the efficient stress reanalysis technique may prove to be a very effective method, since it does not require expensive design sensitivity analyses. The applicability and robustness of the MLDS algorithm is demonstrated using various numerical examples and compared with other algorithm presently available so far.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05b
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• pp.1187-1194
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• 2002

In this study, we have simulated regional climate over East Asia using dynamical downscaling For dynamic downscaling experiments for regional climate simulation, MM5method. with 27 km horizontal resolution and 18 layers of sigma-coordinate in vertical is nested within global-scale NCEP reanalysis data with 2.5。${\times}$2.5。 resolution in longitude and latitude. In regional simulation, January and July, 1979 monthly mean features have been obtained by both continuous integration and daily restart integration driven by updating the lateral boundary forcing at 6-hr intervals from the NCEP reanalysis data using a nudging scheme with the updating design of initial and boundary conditions in both continuous and restart integrations. In result, we may successfully generated regional detail features which might be forced by topography, lake, coastlines and land use distribution from a regional climate. There is no significant difference in monthly mean features either integrate continuously or integrate with daily restart. For climatologically long integration, the initial condition may not be significantly important. Accordingly, MM5 can be integrated for a long period without restart frequently, if a proper lateral boundary forcing is given.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.180-180
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• 2023

To improve global risk management, understanding the characteristics and distribution of precipitation is crucial. However, obtaining spatially and temporally resolved climatic data remains challenging due to sparse gauge observations and limited data availability, despite the use of satellite and reanalysis products. To address this challenge, merging available precipitation products has been introduced to generate spatially and temporally reliable data by taking advantage of the strength of the individual products. However, most of the existing studies utilize all the available products without considering the varying performances of each dataset in different regions. Comprehensively considering the relative contributions of each parent dataset is necessary since their contributions may vary significantly and utilizing all the available datasets for data merging may lead to significant data redundancy issues. Hence, for this study, we introduce a site-specific precipitation merging method that utilizes the Quadruple Collocation (QC) approach, which acknowledges the existence of error-cross correlation between the parent datasets, to create a high-resolution global daily precipitation data from 2001-2020. The performance of multiple gridded precipitation products are first evaluated per region to determine the best combination of quadruplets to be utilized in estimating the error variances through the QC approach and computation of merging weights. The merged precipitation is then computed by adding the precipitation from each dataset in the quadruplet multiplied by each respective merging weight. Our results show that our approach holds promise for generating reliable global precipitation data for data-scarce regions lacking spatially and temporally resolved precipitation data.

• Journal of Korean Society of Steel Construction
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• v.17 no.6 s.79
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• pp.661-672
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• 2005

For the efficient stochastic optimization of steel structures for which a large number of analyses is required, artificial neural networks,which have emerged as a powerful tool that could have been used to replace time-consuming procedures in many scientific or engineering applications, are applied. They are utilized for the solution of the equilibrium equations resulting from the application of the finite element method in connection with the reanalysis type of problem, for which a large number of finite element analyses are required in this study. As such, the use of artificial neural networks to predict finite element analysis outputs simplifies and facilitates the performance of the stochastic optimal design of structural systems where a trained neural network is used to replace the structural reanalysis phase. Moreover, to improve efficiency of used artificial neural networks, genetic algorithm is utilized. The stochastic optimizer used in this study is an algorithm based on the evolution theory. The efficiency of the proposed procedure is examined in problems with both volume (weight) functions and real-world cost functions

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.6
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• pp.950-956
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• 2013

This paper describes a sensitivity-coefficient-based iterative method for detecting cracks in a structure. The sensitivity coefficients of a cracked structure are obtained by changing its eigenvectors. The proposed method is applied to a cracked cantilever. The crack is modeled as a rotational stiffness. The predicted cracks are in good agreement with those from a structural reanalysis of the cracked structure.