• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.05a
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• pp.337-338
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• 2018

In recent years, residential apartment building parking lots are built in underground spaces, and with conjunction to improve the environment of the urban area, artificial greeen roof systems are installed on the upper slabs. However, early plant growth are resulting in root penetration into concrete cracks and in turn into the waterproofing membranes, leading to degradation and damaging of the waterproofing system and structural durability. This issue highlights a problem of conventional maintenance system of concrete structures, and proposals for amendments follow. In this study, a waterproofing and root barrier construction design for the upper slabs of residential building underground parking lots is proposed, and motioned to be added into future construction specifications.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09b
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• pp.910-911
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• 2006

We newly designed and manufactured a new arranging system for a three-dimensional artificial crystal of monosized micro particles. In this system, a robotic micro-manipulator accurately locates the spherical particle onto the lattice point, and subsequently fiber lasers micro-weld the contact points between the neighboring particles. Actually, one- and two-dimensional arrays were constructed using monosized tin particles with the diameter of 400 m. Moreover, due to optimization of the process parameters, we successfully constructed the artificial crystals of simple cubic and diamond structures. In particular, the diamond structure which can represent a large photonic band gap is expected to progress toward a practical photonic crystal device.

• Journal of Ocean Engineering and Technology
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• v.1 no.2
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• pp.60-66
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• 1987

The object of this study is to investigate behaviors of beach fill replenished at three coasts of different configurations by analyzing successively measured beach profiles. The main results obtained in this study are summarized as follows; 1) The amount of nourishing sand moved in the longshore direction surpasses the amount of nourishing sand transported in the cross-shore direction regardless of shapes of the coasts and types of the structures. 2) A clear correlation between displacements of shoreline and changes of sectional areas can be found soon after the placement of beach fill in the fields. This implies that the deformation of the artificial nourishment and dissipation or remaining rate of nourishing sand can be predicated by the one-line theory. 3) The patterns of sediment movements in the artificially nourished beaches are clearly found by the analysis of empirical eignfuncitions.

• Steel and Composite Structures
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• v.12 no.6
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• pp.505-522
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• 2012

An artificial bee colony (ABC) algorithm is developed for the optimum design of geometrically non-linear steel frames. The ABC is a new swarm intelligence method which simulates the intelligent foraging behaviour of honeybee swarm for solving the optimization problems. Minimum weight design of steel frames is aimed under the strength, displacement and size constraints. The geometric non-linearity of the frame members is taken into account in the optimum design algorithm. The performance of the ABC algorithm is tested on three steel frames taken from literature. The results obtained from the design examples demonstrate that the ABC algorithm could find better designs than other meta-heuristic optimization algorithms in shorter time.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.280-280
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• 2013

In green plants, energy generation is accomplished through light-harvesting photosystem, which utilize abundant visible light and multi-stepwise redox reaction to oxidize water and reduce NADP+, transferring electrons efficiently with active cofactors1. Inspired by natural photosynthesis, artificial solar water-splitting devices are being designed variously. However, the several approaches involving immobilization2, conjugation3, and surface modification4 still have limitations. We have made artificial photosynthesis templates by self-assembling tyrosine-based peptide to mimick photosystem II. Porphyrin sensitizer absorbing blue light strongly was conjugated with the templates and they were hybridized with cobalt oxide through the reduction of cobalt ions in an aqueous solution. The formation of hybrid templates was characterized using TEM, and their water oxidation performance was measured by fluorescence oxygen probe. Our results suggest that the bio-templated assembly of functional compounds has a great potential for artificial photosynthesis.

• Wind and Structures
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• v.32 no.2
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• pp.161-167
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• 2021

In this study, the artificial neural network (ANN) method was used for estimating the monthly mean wind speed of Sivas, in the central part of Turkey. Eighteen years of wind speed data obtained from nine measurement stations during the period of 2000-2017 at 10 m height was used for ANN analysis. It was found that mean absolute percentage error (MAPE) ranged from 3.928 to 6.662, mean bias error (MBE) ranged from -0.089 to -0.003, while root mean square error (RMSE) ranged from 0.050 to 0.157 and R2 ranged from 0.86 to 0.966. ANN models provide a good approximation of the wind speed for all measurement stations, however, a tendency to underestimate is also obvious.

• Structural Engineering and Mechanics
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• v.78 no.5
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• pp.529-543
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• 2021

Inevitable source-uncertainties in geometry configuration, boundary condition, and material properties may deviate the structural dynamics from its expected responses. This paper aims to examine the influence of these uncertainties on the vibration of functionally graded beams. Finite element procedures are presented for Timoshenko beams and utilized to generate reliable datasets. A prerequisite to the uncertainty quantification of the beam vibration using Monte Carlo simulation is generating large datasets, that require executing the numerical procedure many times leading to high computational cost. Utilizing artificial neural networks to model beam vibration can be a good approach. Initially, the optimal network for each beam configuration can be determined based on numerical performance and probabilistic criteria. Instead of executing thousands of times of the finite element procedure in stochastic analysis, these optimal networks serve as good alternatives to which the convergence of the Monte Carlo simulation, and the sensitivity and probabilistic vibration characteristics of each beam exposed to randomness are investigated. The simple procedure presented here is efficient to quantify the uncertainty of different stochastic behaviors of composite structures.

• Steel and Composite Structures
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• v.42 no.4
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• pp.459-475
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• 2022

In this paper a model for the prediction of the ultimate axial compressive capacity of square and rectangular Concrete Filled Steel Tubes, based on an Artificial Neural Network modeling procedure is presented. The model is trained and tested using an experimental database, compiled for this reason from the literature that amounts to 1193 specimens, including long, thin-walled and high-strength ones. The proposed model was selected as the optimum from a plethora of alternatives, employing different activation functions in the context of Artificial Neural Network technique. The performance of the developed model was compared against existing methodologies from design codes and from proposals in the literature, employing several performance indices. It was found that the proposed model achieves remarkably improved predictions of the ultimate axial load.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.135-136
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• 2022

As a recent technology, it is possible to partially grasp the occurrence of displacement of the entire building through artificial intelligence technology for big data through scanning. However, scanning and data processing take a lot of time, so there is a limit to constant monitoring, so constant monitoring technology of building behavior that combines wireless remote sensors and 3D shape scanning is required. Therefore, in this study, artificial intelligence program coding technology is linked. In addition, a technology capable of real-time wireless remote measurement of structure displacement will be developed through technology development in response to safety management that combines existing building technologies such as sensors. Through this, it is possible to establish an integrated management system for safety inspection and diagnosis.

• Steel and Composite Structures
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• v.46 no.3
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• pp.435-449
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• 2023

Time domain method and frequency domain method are commonly used in the current fatigue life calculation theory. The time domain method has complicated procedures and needs a large amount of calculation, while the frequency domain method has poor applicability to different materials and different spectrum, and improper selection of spectrum model will lead to large errors. Considering that artificial neural network has strong ability of nonlinear mapping and generalization, this paper applied this technique to random fatigue life prediction, and the effect of average stress was taken into account, thereby achieving more accurate prediction result of random fatigue life.