• Transactions of Materials Processing
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• v.21 no.5
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• pp.319-323
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• 2012

In order to predict the internal void closing behavior in open die forging process, multiple scale modeling has been developed and applied. The huge size difference between ingot and inner void makes it almost impossible to simultaneously model the actual loading conditions and the void shape. Multiple scale modeling is designed to integrate macro- and micro- models effectively and efficiently. The void closing behavior was simulated at 39 different locations in a large ingot during upsetting and cogging. The correlation between the closing behavior and variables such as effective plastic strain and maximum compressive strain was studied in order to find an efficient measure for predicting the soundness of the forging.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.6
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• pp.93-101
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• 2001

This paper presents modeling of an inductive micro position sensing system and its analysis. The parameters affected the system response are excitation frequency, turn ratio, input position, air-gap size, load resistance, and geometric dimensions. To analyze the system, we try to establish a modeling based on an equivalent magnetic circuit with permeances. The model is verified by the experimental results from 1 kHz to 20 kHz. The magnetic circuit model is well fitted to the experimental data except a little error due to LC resonance in the large turn-ratio system. Modeling enables us to theoretically approach the response characteristics. Based on the magnetic circuit model, system parameters can be selected in such a way to obtain the required characteristics such as high sensitivity, good linearity, or small size.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.9
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• pp.1923-1930
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• 2002

In this paper, we present modeling and simulation of microlens formation by means of a deep X-ray lithography followed by a thermal treatment of a PMMA (Polymethylmethacrylate) sheet. According to this modeling, X-ray irradiation causes the decrease of molecular weight of PMMA, which in turn decreases the glass transition temperature and consequently causes a net volume increase during the thermal cycle resulting in a swollen microlens. In this modeling, the free volume theory including the relaxation process during the cooling process was considered. The simulation results indicate that the modeling in this study is able to predict the fabricated microlens shapes and the variation pattern of the maximum heights of microlens which depends on the conditions of the thermal treatment. The prediction model could be applied to optimization of microlens fabrication process and to designing a micro mold insert for micromolding processes.

• Advances in Computational Design
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• v.8 no.2
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• pp.97-112
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• 2023

The Finite Element (FE) modeling of Reinforced Concrete (RC) under seismic loading has a sensitive impact in terms of getting good contribution compared to experimental results. Several idealized model types for simulating the nonlinear response have been developed based on the plasticity distribution alone the model. The Continuum Models are the most used category of modeling, to understand the seismic behavior of structural elements in terms of their components, cracking patterns, hysteretic response, and failure mechanisms. However, the material modeling, contact and nonlinear analysis strategy are highly complex due to the joint operation of concrete and steel. This paper presents a numerical simulation of a chosen RC column under monotonic and cyclic loading using the FE Abaqus, to assessthe hysteretic response and failure mechanisms in the RC columns, where the perfect bonding option is used for the contact between concrete and steel. While results of the numerical study under cyclic loading compared to experimental tests might be unsuccessful due to the lack of bond-slip modeling. The monotonic loading shows a good estimation of the envelope response and deformation components. In addition, this work further demonstrates the advantage and efficiency of the damage distributions since the obtained damage distributions fit the expected results.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.1
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• pp.17-24
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• 2013

In this paper, a micro-mechanical failure prediction program is developed based on SIFT (Strain Invariant Failure Theory) by using the multi-scale modeling method for fiber-reinforced composite materials. And the failure analysis are performed for open-hole composite laminate specimen in order to verify the developed program. First of all, the critical strain invariants are obtained through the tensile tests for three types of specimens. Also, the matrices of strain amplification factors are determined through the finite element analysis for micro-mechanical model, RVE (Representative Volume Element). Finally, the microscopic failure analysis is performed for the open-hole composite laminate specimen model by applying a failure load obtained from tensile test, and the predicted failure indices are evaluated for verification of the developed program.

• Journal of the Korean Geosynthetics Society
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• v.15 no.4
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• pp.33-42
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• 2016

Discrete Element Method was conducted for rock and coarse-grained materials in development of granular mechanics and related numerical model due to analyze and apply micromechanical property. And it was verified that the analysis to consider bonding effect was insufficient. In this study, to overcome limits of existing method, it was conducted to analyze difference between indoor test result and bonding effect using $PFC^{3D)}$. For indoor test of mixed soil, uniaxial compression tests by curing time and by cement content were performed. And, DEM to suitable for each condition of indoor test was conducted. In the result of this study, in terms of geotechnics, it was verified that DEM can be used for application as numerical laboratory as well as prediction of micro and macro behavior about bonding effect of mixed soil.

• Journal of the Korean Recycled Construction Resources Institute
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• v.7 no.3
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• pp.56-61
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• 2012

The most common deterioration cause of concrete structures over the world is chloride ions attacks. Thus, service life modeling of concrete is a crucial issue in civil engineering society. Many studies on the durability of concrete have been accomplished, however, it is not easy to review literatures about environmental analysis. Since the durability of concrete depends on the properties of the surface concrete. micro-climatic condition which influences on surface concrete realistically should be considered. This study is devoted to analysis the micro-climatic condition of concrete structures, based on the in-situ monitoring of weather in marine environment. The effect of degree of saturation on chloride diffusivity of concrete is also examined. It is expected that the result of this work should be available for the prediction of chloride profile of marine concrete.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.19-30
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• 2023

An electric scooter(e-scooter), one popularized micro-mobility vehicle has shown rapidly increasing use in many cities. In South Korea, the use of e-scooters has greatly increased, as some companies have launched e-scooter sharing services in a few large cities, starting with Seoul in 2018. However, the use of e-scooters is still controversial because of issues such as parking and safety. Since the perception toward the means of transportation affects the mode choice, it is necessary to track the trends for electric scooters to make the use of e-scooters more active. Hence, this study aimed to analyze the trends related to e-scooters. For this purpose, we analyzed news articles related to e-scooters published from 2014 to 2020 using dynamic topic modeling to extract issues and sentiment analysis to investigate how the degree of positive and negative opinions in news articles had changed. As a result of topic modeling, it was possible to extract three different topics related to micro-mobility technologies, shared e-scooter services, and regulations for micro-mobility, and the proportion of the topic for regulations for micro-mobility increased as shared e-scooter services increased in recent years. In addition, the top positive words included quick, enjoyable, and easy, whereas the top negative words included threat, complaint, and ilegal, which implies that people satisfied with the convenience of e-scooter or e-scooter sharing services, but safety and parking issues should be addressed for micro-mobility services to become more active. In conclusion, this study was able to understand how issues and social trends related to e-scooters have changed, and to determine the issues that need to be addressed. Moreover, it is expected that the research framework using dynamic topic modeling and sentiment analysis will be helpful in determining social trends on various areas.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.4
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• pp.251-257
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• 2011

In the present study, a 3-dimensional (3D) numerical model was developed to mimic the micro porous structure of a geological $CO_2$ storage reservoir. Especially, 3D modeling technique assigning random pore size to a 3D micro porous structure was devised. Numerical method using CFD (computational fluid dynamics) was applied for the 3D micro porous structure to calculate supercritical $CO_2$ flow field. The three different configurations of 3D micro porous model were designed and their flow fields were calculated. For the physical conditions of $CO_2$ flow, temperature and pressure were set up equivalent to geological underground condition where $CO_2$ fluid was stored. From the results, the characteristics of the supercritical $CO_2$ flow fields were scrutinized and the influence of the micro pore configuration on the flow field was investigated. In particular, the pressure difference and consequent $CO_2$ permeability were calculated and compared with increasing $CO_2$ flow rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3005-3027
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• 2015

Spam has become one of the top threats of micro-blogging networks as the representations of rumor spreading, advertisement abusing and malware distribution. With the increasing popularity of micro-blogging, the problems will exacerbate. Prior detection tools are either designed for specific types of spams or not robust enough. Spammers may escape easily from being detected by adjusting their behaviors. In this paper, we present a novel model to quantitatively evaluate information diffusion in micro-blogging networks. Under this model, we found that spam posts differ wildly from the non-spam ones. First, the propagations of non-spam posts mostly result from their followers, but those of spam posts are mainly from strangers. Second, the non-spam posts relatively last longer than the spam posts. Besides, the non-spam posts always get their first reposts/comments much sooner than the spam posts. With the features defined in our model, we propose an RBF-based approach to detect spams. Different from the previous works, in which the features are extracted from individual profiles or contents, the diffusion features are not determined by any single user but the crowd. Thus, our method is more robust because any single user's behavior changes will not affect the effectiveness. Besides, although the spams vary in types and forms, they're propagated in the same way, so our method is effective for all types of spams. With the real data crawled from the leading micro-blogging services of China, we are able to evaluate the effectiveness of our model. The experiment results show that our model can achieve high accuracy both in precision and recall.