• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.6
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• pp.349-357
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• 2019

Finite element method (FEM) is utilized in the development of products to realistically analyze and predict the mechanical behavior of materials in various fields. However, the approach based on the numerical analysis of glass fiber reinforced plastic (GFRP) composites, for which the fiber orientation and strain rate affect the mechanical properties, has proven to be challenging. The purpose of this study is to define and evaluate the mechanical properties of glass fiber reinforced plastic composites using the numerical analysis models of Digimat, a linear, nonlinear multi-scale modeling program for various composite materials such as polymers, rubber, metal, etc. In addition, the aim is to predict the behavior of realistic polymeric composites. In this regard, the tensile properties according to the fiber orientation and strain rate of polybutylene terephthalate (PBT) with short fiber weight fractions of 30wt% among various polymers were investigated using references. Information on the fiber orientation was calculated based on injection analysis using Moldflow software, and was utilized in the finite element model for tensile specimens via a mapping process. LS-Dyna, an explicit commercial finite element code, was used for coupled analysis using Digimat to study the tensile properties of composites according to the fiber orientation and strain rate of glass fibers. In addition, the drawbacks and advantages of LS-DYNA's various anisotropic material models were compared and evaluated for the analysis of glass fiber reinforced plastic composites.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.2
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• pp.187-193
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• 2017

This study evaluated tidal stream energy resources according to tidal flow properties around Uido off the west coast of, Jeollanam-do, South Korea. A feasibility study was first carried out through the collection of bathymetry data and tidal phase information. For this simulation, a depth-averaged 2D ADCIRC (Advanced Circulation) model for real sea situations was applied to a Finite Element Method (FEM) approach for tides given the variation of tidal current speed. Hydrodynamics were simulated with 4 major tidal constituents (M2, S2, K1, and O1) after setting up 4 observation points. From the real depth-averaged model simulation results, it was found that the spring tide Higher High Water (HHW) and tidal current speed values at the 4 observation points were about 2.2 m and 1.33 m/s, respectively. The ADCIRC model results were analyzed with reference to the Korea Hydrographic and Oceanographic Agency's (KHOA) observed data for verification. Furthermore, using topographical characteristics via the Tidal Flux Method (TFM), tidal energy density distribution was calculated, indicating a maximum tidal energy density of about $1.75kW/m^2$ for the 5 assessment areas around Uido. The tidal energy density was evaluated with consideration given to topographical characteristics as well as tidal elevation and tidal current speed to determine an optimum tidal farm candidate.

• Journal of KIISE:Databases
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• v.34 no.3
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• pp.193-205
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• 2007

Increasing amount of digital images requires more accurate and faster way of image retrieval. So far, image retrieval method includes content-based retrieval and keyword based retrieval, the former utilizing visual features such as color and brightness and the latter utilizing keywords which describe the image. However, the effectiveness of these methods as to providing the exact images the user wanted has been under question. Hence, many researchers have been working on relevance feedback, a process in which responses from the user are given as a feedback during the retrieval session in order to define user’s need and provide improved result. Yet, the methods which have employed relevance feedback also have drawbacks since several feedbacks are necessary to have appropriate result and the feedback information can not be reused. In this paper, a novel retrieval model has been proposed which annotates an image with a keyword and modifies the confidence level of the keyword in response to the user’s feedback. In the proposed model, not only the images which have received positive feedback but also the other images with the visual features similar to the features used to distinguish the positive image are subjected to confidence modification. This enables modifying large amount of images with only a few feedbacks ultimately leading to faster and more accurate retrieval result. An experiment has been performed to verify the effectiveness of the proposed model and the result has demonstrated rapid increase in recall and precision while receiving the same number of feedbacks.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.3
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• pp.24-37
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• 2024

Due to the thin nature of semiconductor packages, even minor thermal loads can cause significant warpage, impacting product reliability through issues like delamination or cracking. The mold curing process, which encloses the package to protect the semiconductor chip, is particularly challenging to predict due to the complex thermal, chemical, and mechanical interactions. This study proposes a cost-effective machine learning model to predict warpage in the mold curing process. We developed methods to characterize the curing degree based on time and temperature and quantify the material's mechanical properties accordingly. A Finite Element Method (FEM) simulation model was created by integrating these properties into ABAQUS UMAT to predict warpage for various design factors. Additionally, a Warpage formula was developed to estimate local warpage based on the package's stacking structure. This formula combines bending theory with thermo-chemical-mechanical properties and was validated through FEM simulation results. The study presents a method to construct a machine learning model for warpage prediction using this formula and proposes a cost-effective approach for building a training dataset by analyzing input variables and design factors. This methodology achieves over 98% prediction accuracy and reduces simulation time by 96.5%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.237-244
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• 2016

The workability of mortar determines its construction performance in a structure showing its designed resistance to external loads. Measuring the rheological properties of mortar is one way of quantifying its workability, but its field-applications are limited due to economical and spatial issues. The robustness of the slump flow test allows its use for evaluating the workability of mortar, even though it is a rather qualitative test method. This paper proposes a channel flow test and develops a correlation between its result and the rheological properties of mortar. The volume-of-fluid simulation for the channel flow test was accomplished, and a numerical database for the correlation was composed. A correlation model to estimate the rheological properties of mortar using the results of the channel flow test as inputs is proposed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.12
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• pp.1635-1642
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• 2012

The identification of the dynamic properties of structural joints is important for predicting the dynamic behavior of assembled systems. However, the identification of the properties using analytical or experimental approaches is extremely difficult or even impossible. Several studies have proposed hybrid or synthesis methods that simultaneously used analytical and experimental approaches to identify the dynamic properties of a joint. However, among the many types of joints, only the bolt joint was treated as a practical example in these studies. In this study, for a simple assembly system comprising two plates and one hinge joint, a simple methodology involving the use of the static-based subpart analysis method to identify the dynamic properties is proposed. Finally, the proposed method is applied to a glove box in a passenger vehicle that includes hinge joints.

• Journal of the Korean Geotechnical Society
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• v.37 no.1
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• pp.17-27
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• 2021

It takes a long period to conduct the test on soil water retention curve (SWRC) in unsaturated soils. To improve such a problem, the high air entry disk has been replaced by micro-membrane. After the soil water retention test, the results by the micro-membrane were compared with those by the ceramic disk. Multiple samples in 5 regions were used to validate that SWRCs by micro-membrane are equivalent to those by ceramic disk. Therefore, a quick procedure based on micro-membrane has been developed, which makes it available to acquire much soil water retention data. The data of SWRCs were obtained for total 29 samples using ceramic disk or micro-membrane. For Korean weathered soils, the unsaturated hydraulic characteristics are sorted by three groups. Based on van Genuchten model, the group is divided by the parameter n, and the value of n could be correlated to the void ratio as each function.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.136-152
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• 2017

The thermodynamic models, PC-SAFT (Perturbed-Chain Statistical Associated Fluid Theory) state equation and the Two-model approach liquid activity coefficient model NRTL (Non Random Two Liquid) + Henry + Peng-Robinson, for modeling the Rectisol process using methanol aqueous solution as the $CO_2$ removal solvent were compared. In addition, to determine the new binary interaction parameters of the PC-SAFT state equations and the Henry's constant of the two-model approach, absorption equilibrium experiments between carbon dioxide and methanol at 273.25K and 262.35K were carried out and regression analysis was performed. The accuracy of the newly determined parameters was verified through the regression results of the experimental data. These model equations and validated parameters were used to model the carbon dioxide removal process. In the case of using the two-model approach, the methanol solvent flow rate required to remove 99.00% of $CO_2$ was estimated to be approximately 43.72% higher, the cooling water consumption in the distillation tower was 39.22% higher, and the steam consumption was 43.09% higher than that using PC-SAFT EOS. In conclusion, the Rectisol process operating under high pressure was designed to be larger than that using the PC-SAFT state equation when modeled using the liquid activity coefficient model equation with Henry's relation. For this reason, if the quantity of low-solubility gas components dissolved in a liquid at a constant temperature is proportional to the partial pressure of the gas phase, the carbon dioxide with high solubility in methanol does not predict the absorption characteristics between methanol and carbon dioxide.

• Journal of the Korean Geographical Society
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• v.51 no.4
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• pp.509-523
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• 2016

The soil prediction can provide quantitative soil information for sustainable mountainous ecosystem management. Visible near infrared spectroscopy, one of soil prediction methods, has been applied to predict several soil properties with effective costs, rapid and nondesctructive analysis, and satisfactory accuracy. Spectral preprocessing is a essential procedure to correct noisy spectra for visible near infrared spectroscopy. However, there are no attempts to evaluate various spectral preprocessing methods. We tested 5 different pretreatments, namely continuum removal, Savitzky-Golay filter, discrete wavelet transform, 1st derivative, and 2nd derivative to predict soil carbon(C) and nitrogen(N). Partial least squares regression was used for the prediction method. The total of 153 soil samples was split into 122 samples for calibration and 31 samples for validation. In the all range, absorption was increased with increasing C contents. Specifically, the visible region (650nm and 700nm) showed high values of the correlation coefficient with soil C and N contents. For spectral preprocessing methods, continuum removal had the highest prediction accuracy(Root Mean Square Error) for C(9.53mg/g) and N(0.79mg/g). Therefore, continuum removal was selected as the best preprocessing method. Additionally, there were no distinct differences between Savitzky-Golay filter and discrete wavelet transform for visual assessment and the methods showed similar validation results. According to the results, we also recommended Savitzky-Golay filter that is a simple pre-treatment with continuum removal.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.115-123
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• 2006

This paper presents long-term dynamic characteristics of a cable-stayed bridge where installed SHM (Structural Health Monitoring) system. Modal parameters such as natural frequencies and mode shapes are identified by modal analysis using three dimensional finite element model. The developed baseline model has a good correlation with measured natural frequencies identified from field ambient vibrations. By statistical data processing between measured natural frequencies and temperatures, it is demonstrated that the natural frequency is in linearly inverse proportion to the temperature. The estimation of temperature effects against frequency variations is performed. Mode shapes are identified from the TDD (Time Domain Decomposition) technique for ambient vibration measurements. Finally, these results demonstrate that the TDD method can apply to identify modal parameters of a cable-stayed bridge.