• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.10
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• pp.91-97
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• 1998

The modulation performance of 10 Gbps electro-absorption InGaAsP/InGaAsP strain compensated MQW (Multiple Quantum Well) modulator module depends on the modulator as well as the package parasitics. The high frequency package parasitics resulting from various structural discontinuities, limit the modulation bandwidth and increase the chirp-parameter. Therefore, we propose the double bondwires embedded in dielectric materials to minimize the bondwire parasitics. Using the proposed structure with 50 $\Omega$ terminating resistor, the modulation bandwidth is greatly increased by 125 % than the bare chip and the chirp-parameter is also reduced. This technique can be used in optimizing the package of high speed external modulators.

• Proceedings of the Korean Reliability Society Conference
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• 2011.06a
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• pp.107-113
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• 2011

The windshield wiper consists of 4 parts: a blade, an arm, a linkage and a motor. The wiper blade makes contact with the windshield and is designed to be operated normally at an angle of 30~50 degrees to the front glass. If the contact pressure between the wiper blade and windshield surface is too high, noise and wear of the rubber will result. On the other hand, if the contact pressure is too low, the performance will do badly, since foreign substances such as dust and stains will not be removed well. The pressure and friction of the wiper blade has a great influence on its effectiveness in cleaning the front window. This is due to the contact of the rubber with the window. This paper presents the dynamic analysis method to estimate the performance of the flat type blade of the wiper system. The blade has a nonlinear characteristic since the rubber is an incompressible hyper-elastic and visco-elastic material. Thus, Structural dynamic analysis using a complex contact model for the blade is performed to find the characteristics of the blade. The flexible multi-body dynamic model is verified by the comparison between test and analysis result. Also, the optimization using the central composite design table is performed.

• Structural Engineering and Mechanics
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• v.29 no.5
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• pp.489-504
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• 2008

In piezoelectric flexible structures, the contribution of vibration modes to the dynamic response of system may change with the location of piezoelectric actuator patches, which means that the ability of actuators to control vibration modes should be taken into account in the development of modal reduction model. The spatial $H_2$ norm of modes, which serves as a measure of the intensity of modes to system dynamical response, is used to pick up the modes included in the reduction model. Based on the reduction model, the paper develops the state-space representation for uncertain flexible tructures with piezoelectric material as non-collocated actuators/sensors in the modal space, taking into account uncertainties due to modal parameters variation and unmodeled residual modes. In order to suppress the vibration of the structure, a dynamic output feedback control law is designed by imultaneously considering the conflicting performance specifications, such as robust stability, transient response requirement, disturbance rejection, actuator saturation constraints. Based on linear matrix inequality, the vibration control design is converted into a linear convex optimization problem. The simulation results show how the influence of vibration modes on the dynamical response of structure varies with the location of piezoelectric actuators, why the uncertainties should be considered in the reductiom model to avoid exciting high-frequency modes in the non-collcated vibration control, and the possiblity that the conflicting performance specifications are dealt with simultaneously.

• Journal of Korean Association for Spatial Structures
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• v.23 no.3
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• pp.87-94
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• 2023

Chloride is one of the most common threats to reinforced concrete (RC) durability. Alkaline environment of concrete makes a passive layer on the surface of reinforcement bars that prevents the bar from corrosion. However, when the chloride concentration amount at the reinforcement bar reaches a certain level, deterioration of the passive protection layer occurs, causing corrosion and ultimately reducing the structure's safety and durability. Therefore, understanding the chloride diffusion and its prediction are important to evaluate the safety and durability of RC structure. In this study, the chloride diffusion coefficient is predicted by machine learning techniques. Various machine learning techniques such as multiple linear regression, decision tree, random forest, support vector machine, artificial neural networks, extreme gradient boosting annd k-nearest neighbor were used and accuracy of there models were compared. In order to evaluate the accuracy, root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE) and coefficient of determination (R2) were used as prediction performance indices. The k-fold cross-validation procedure was used to estimate the performance of machine learning models when making predictions on data not used during training. Grid search was applied to hyperparameter optimization. It has been shown from numerical simulation that ensemble learning methods such as random forest and extreme gradient boosting successfully predicted the chloride diffusion coefficient and artificial neural networks also provided accurate result.

• Structural Engineering and Mechanics
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• v.90 no.1
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• pp.97-106
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• 2024

This paper presents a significant contribution to aided design by conducting an analytical examination of geometric links with the aim of establishing criteria for assessing an analogy measure of the extrinsic geometric and kinematic characteristics of the Variable Compression Ratio (VCR) engine with a Geared Mechanism (GBCM) in comparison to the existing Fixed Compression Ratio (FCR) engine with a Standard-Reciprocating Crankshaft configuration. Employing a mechanical approach grounded in projective computational methods, a parametric study has been conducted to analyze the kinematic behavior and geometric transformations of the moving links. The findings indicate that in order to ensure equivalent extrinsic behavior and maintain consistent input-output performance between both engine types, precise adjustments of intrinsic geometric parameters are necessary. Specifically, for a VCR configuration compared to an FCR configuration, regardless of compression ratio and gearwheel radius, for the same crankshaft ratios and stroke lengths, it is imperative to halve lengths of connecting rods, and crank radius. These insights underscore the importance of meticulous parameter adjustment in achieving comparable performance across different engine configurations, offering valuable implications for design optimization.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.1
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• pp.17-27
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• 2019

In this paper, we study the applicability of Tuned Mass Damper(TMD) to improve seismic performance of piping system under earthquake loading. For this purpose, a mode analysis of the target pipeline is performed, and TMD installation locations are selected as important modes with relatively large mass participation ratio in each direction. In order to design the TMD at selected positions, each corresponding mode is replaced with a SDOF damped model, and accordingly the corresponding pipeline is converted into a 2-DOF system by considering the TMD as a SDOF damped model. Then, optimal design values of the TMD, which can minimize the dynamic amplification factor of the transformed 2-DOF system, are derived through GA optimization method. The proposed TMD design values are applied to the pipeline numerical model to analyze seismic performance with and without TMD installation. As a result of numerical analyses, it is confirmed that the directional acceleration responses, the maximum normal stresses and directional reaction forces of the pipeline system are reduced, quite a lot. The results of this study are expected to be used as basic information with respect to the improvement of the seismic performance of the piping system in the future.

• Journal of the Korean Institute of Gas
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• v.24 no.3
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• pp.47-53
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• 2020

In this study, the optimization design data was presented by analyzing the performance and durability of the cooling fan by one-way fluid-structure interaction analysis of the cooling fan shape used in the engine generator. For this purpose, a steady-state analysis was performed on the flow field inside the cooling fan, and the durability was analyzed by using the steady-state calculation results as input data for structural analysis. Six types were modeled for fluid analysis by changing the blade and sweep angle of the cooling fan, and the ratio of mass flow rate and torque was best in A type, but B type with relatively large mass flow rate was the best. It was judged to have flow performance. As a result of examining the structural analysis by setting the four blade thickness of the B type selected through the fluid analysis, it was judged that B Type-3 is the most suitable when considering the fatigue safety factor.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.1
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• pp.69-78
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• 2011

In this study, an optimization method using multi-objective genetic algorithm(MOGA) has been proposed to develop a fuzzy control algorithm that can effectively control a smart tuned mass damper(TMD). A 76-story benchmark building subjected to wind load was selected as an example structure. The smart TMD consists of 100kN MR damper and the natural period of the smart TMD was tuned to the first mode natural period of the example structure. Damping force of MR damper is controlled to reduce the wind-induced responses of the example structure by a fuzzy logic controller. Two input variables of the fuzzy logic controller are the acceleration of 75th floor and the displacement of the smart TMD and the output variable is the command voltage sent to MR damper. Multi-objective genetic algorithm(NSGA-II) was used for optimization of the fuzzy logic controller and the acceleration of 75th story and the displacement of the smart TMD were used as objective function. After optimization, a series of fuzzy logic controllers which could appropriately reduce both wind responses of the building and smart TMD were obtained. Based on numerical results, it has been shown that the control performance of the smart TMD is much better than that of the passive TMD and it is even better than that of the sample active TMD in some cases.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.3
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• pp.137-145
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• 2014

We present a design sensitivity analysis(DSA) method for multiscale problems based on bridging scale decomposition. In this paper, we utilize a bridging scale method for the coupled system analysis. Since the analysis of full MD systems requires huge amount of computational costs, a coupled system of MD-level and continuum-level simulation is usually preferred. The information exchange between the MD and continuum levels is taken place at the MD-continuum boundary. In the bridging scale method, a generalized Langevin equation(GLE) is introduced for the reduced MD system and the GLE force using a time history kernel is applied at the boundary atoms in the MD system. Therefore, we can separately analyze the MD and continuum level simulations, which can accelerate the computing process. Once the simulation of coupled problems is successful, the need for the DSA is naturally arising for the optimization of macro-scale design, where the macro scale performance of the system is maximized considering the micro scale effects. The finite difference sensitivity is impractical for the gradient based optimization of large scale problems due to the restriction of computing costs but the analytical sensitivity for the coupled system is always accurate. In this study, we derive the analytical design sensitivity to verify the accuracy and applicability to the design optimization of the coupled system.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.113-119
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• 2023

Most infrastructure structures were completed during periods of economic growth. The number of infrastructure structures reaching their lifespan is increasing, and the proportion of old structures is gradually increasing. The functions and performance of these structures at the time of design may deteriorate and may even lead to safety accidents. To prevent this repercussion, accurate inspection and appropriate repair are requisite. To this end, demand is increasing for computer vision and deep learning technology to accurately detect even minute cracks. However, deep learning algorithms require a large number of training data. In particular, label images indicating the location of cracks in the image are required. To secure a large number of those label images, a lot of labor and time are consumed. To reduce these costs as well as increase detection accuracy, this study proposed a learning structure based on mean teacher method. This learning structure was trained on a dataset of 900 labeled image dataset and 3000 unlabeled image dataset. The crack detection network model was evaluated on over 300 labeled image dataset, and the detection accuracy recorded a mean intersection over union of 89.23% and an F1 score of 89.12%. Through this experiment, it was confirmed that detection performance was improved compared to supervised learning. It is expected that this proposed method will be used in the future to reduce the cost required to secure label images.