• Journal of ILASS-Korea
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• v.20 no.1
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• pp.53-58
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• 2015

In this study, we prepare the Ag nanofluids synthesized by the chemical reduction method and measure the extinction coefficient of those nanofluids at a wavelength of 632.8 nm. The Ag nanofluids are synthesized by the chemical reduction method using silver nitrate ($AgNO_3$) and sodium borohydride ($NaBH_4$) in water and ethylene glycol (EG). For stable dispersion of Ag particles in the base liquids, polyvinyl pyrrolidone (PVP) is added as a surfactant. The extinction coefficient of manufactured Ag nanofluids is measured by an in-house developed measurement system at the wavelength of 632.8 nm. The results show that the extinction coefficient of water-based and EG-based Ag nanofluids is linearly increased with respect to the particle loadings. Moreover, it is shown that the extinction coefficient of EG-based Ag nanofludis is higher than that of water-based Ag nanofluids. Finally we compare the experimental results with both the Maxwell-Garnett model and Rayleigh scattering approximation model, and they demonstrate that the Rayleigh scattering approximation model is reasonably predict the extinction coefficient of Ag nanofluids using hydraulic diameter of silver nanoparticle.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.563-574
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• 2023

Recently, climate change has affected functional responses of river basins to meteorological variables, emphasizing the importance of rainfall-runoff simulation research. Simultaneously, the growing interest in machine learning has led to its increased application in hydrological studies. However, it is not yet clear whether machine learning models are more advantageous than the conventional conceptual models. In this study, we compared the performance of the conventional GR6J model with the machine learning-based Random Forest model across 38 basins in Korea using both gauged and ungauged basin prediction methods. For gauged basin predictions, each model was calibrated or trained using observed daily runoff data, and their performance was evaluted over a separate validation period. Subsequently, ungauged basin simulations were evaluated using proximity-based parameter regionalization with Leave-One-Out Cross-Validation (LOOCV). In gauged basins, the Random Forest consistently outperformed the GR6J, exhibiting superiority across basins regardless of whether they had strong or weak rainfall-runoff correlations. This suggest that the inherent data-driven training structures of machine learning models, in contrast to the conceptual models, offer distinct advantages in data-rich scenarios. However, the advantages of the machine-learning algorithm were not replicated in ungauged basin predictions, resulting in a lower performance than that of the GR6J. In conclusion, this study suggests that while the Random Forest model showed enhanced performance in trained locations, the existing GR6J model may be a better choice for prediction in ungagued basins.

• Journal of Drive and Control
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• v.12 no.2
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• pp.39-48
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• 2015

In order to control the actuators of hydraulic machinery such as excavators, various control valves are typically assembled in a single block. Such a control block is called a main control valve(MCV). In this paper, we analyzed the working principle and the particular purpose of the design of all valves included in the MCV system. To Examine the reliability of the analysis model, the pressure drop of the MCV at each port was measured. The authors developed an analytical model of the control valve(main spool, load poppet, pressure relief, make up, and regeneration). The authors considered the notch shape of the spool while developing the analytical models of the main spool valve. Most importantly, at the stage before the analysis model was applied in the design tuning, the reliability was ensured by comparing the analysis results with the test results. This paper showed a process of developing an analysis model that can be utilized in the design and tuning stages.

• Journal of computational fluids engineering
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• v.12 no.4
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• pp.44-53
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• 2007

A three-dimensional (3D) unstructured hydrodynamic solver for transient two-phase flows has been developed for a 3D component of a nuclear system code and a component-scale analysis tool. A two-fluid three-field model is used for the two-phase flows. The three fields represent a continuous liquid, an entrained liquid, and a vapour field. An unstructured grid is adopted for realistic simulations of the flows in a complicated geometry. The semi-implicit ICE (Implicit Continuous-fluid Eulerian) numerical scheme has been applied to the unstructured non-staggered grid. This paper presents the numerical method and the preliminary results of the calculations. The results show that the modified numerical scheme is robust and predicts the phase change and the flow transitions due to boiling and flashing very well.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.354-366
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• 2020

This work mainly focuses on determination of the fully plastic J-integral solutions for welded center cracked plates subjected to remote tension loading. Detailed three-dimensional elasticeplastic Finite Element Analyses (FEA) were implemented to compute the fully plastic J-integral along the crack front for a wide range of crack geometries, material properties and weld strength mismatch ratios for 900 cases. According to the database generated from FEA, Back-propagation Neural Network (BPNN) model was proposed to predict the values and distributions of fully plastic J-integral along crack front based on the variables used in FEA. The determination coefficient R2 is greater than 0.99, indicating the robustness and goodness of fit of the developed BPNN model. The network model can accurately and efficiently predict the elastic-plastic J-integral for weld centerline crack, which can be used to perform fracture analyses and safety assessment for welded center cracked plates with varying strength mismatch conditions under uniaxial loading.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.5
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• pp.103-109
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• 2004

This paper presents a fairing method for reverse engineering of a free-formed surface. Utilizing measured data points, reverse engineering is a useful method to construct a CAD model from physical model. Measured data points should be faired since raw data may have outliers. A fairing algorithm of polynomial regression model generates smooth curves of approximation in this paper. The faired curves are utilized to construct a free-formed surface. For a verifying example, an impeller blade is digitized with a CMM to collect raw data on the surfacce and a CAD model is constructed. This research produces impeller blades with 5-axis machining center through the CAD model and compares them with a physical model. As a result the produced surface modeled with the fairing method gives less error than that without the fairing.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.9
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• pp.52-57
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• 2010

The analysis of a crack in a bone-like material is performed numerically. The bone-like material is hierarchically structured and each hierarchy is structured by mineral platelets and protein matrix through staggered arrangement. Mechanical behavior of the composite can be analyzed using tension shear chain model. The Dugdale model is adopted to evaluate the fracture energy of Bone-like material. The fracture energy dissipation is assumed to concentrate within a strip near the crack tip along the prospective crack path. Fracture criterion of the bone-like material is estimated by using J integral. Effects of hierarchical level, ratio of elastic modulus of mineral to protein, aspect ratio of mineral platelet and volume fraction on J integral are investigated. It is found that the J integral decreases as elastic modulus ratio and hierarchy level increase. It is also shown that the J integral increases as the volume fraction and aspect ratio decrease.

• Transactions of Materials Processing
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• v.25 no.5
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• pp.325-331
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• 2016

In this paper, a three-dimensional part model is constructed for the finite element analysis of hemming models where hemming defects frequently occur. The roller path is modeled as the boundary condition with the one-dimensional beam element and the revolute joint model. With the constructed part model and the roller movement, a finite element analysis has been pursued in order to identify the hemming load and hemming defects such as wrinkling in the flange region. The analysis result shows that the maximum hemming load occurs in the intake situation while oscillatory behavior of the load is found especially when hemming the curved model because of wrinkle generation. This paper compares the amplitude and the period of wrinkle between the analysis result and the experiment, which shows good agreement with each other.

• Electronics and Telecommunications Trends
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• v.35 no.3
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• pp.9-19
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• 2020

Recently, a technique for applying a deep learning language model pretrained from a large corpus to fine-tuning for each application task has been widely used as a language processing technology. The pretrained language model shows higher performance and satisfactory generalization performance than existing methods. This paper introduces the major research trends related to deep learning pretrained language models in the field of language processing. We describe in detail the motivations, models, learning methods, and results of the BERT language model that had significant influence on subsequent studies. Subsequently, we introduce the results of language model studies after BERT, focusing on SpanBERT, RoBERTa, ALBERT, BART, and ELECTRA. Finally, we introduce the KorBERT pretrained language model, which shows satisfactory performance in Korean language. In addition, we introduce techniques on how to apply the pretrained language model to Korean (agglutinative) language, which consists of a combination of content and functional morphemes, unlike English (refractive) language whose endings change depending on the application.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.82-83
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• 1996

In this paper, we present a simplified model for complicance determination of the moving-actuator type totally implantable artificial heart (TAH). The modeling equations are derived from the mechanics and geometry of the TAH components. The interventricular pressure and volume are computed for determining the compliance of the interventricular space using this model. The model is capable of generating realistic hemodynamic variables such as the left atrial pressure and interventricular pressure and is proved to be acceptable. This model can be used as an initial step for analyzing characteristics of the moving-actuator type TAH.