• Textile Coloration and Finishing
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• v.27 no.1
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• pp.11-17
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• 2015

Recently, super fiber reinforced composite materials are widely used in many industries due to high mechanical properties. In this study, 2 different types of composite materials were manufactured in order to compare their mechanical properties. Carbon and Aramid fibers were used for reinforcement materials and Bisphenol-A type epoxy resin was for matrix. Two kinds of fiber-reinforced materials were manufactured by RIM(Resin Injection Molding) method. Before manufacturing composite materials, the optimal manufacturing and curing process condition were established and the ratio of reinforcement to epoxy resin was discussed. FT-IR analysis was conducted to clarify the structure of epoxy resin. Thermal and mechanical property test were also carried out. The cross-section of composite materials was observed using a scanning electron microscope(SEM).

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.93-101
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• 2012

PURPOSES : This study is to develop ISM for potential risk factor in School Zone. METHODS : Based on the literature review, the Analytic Hierarchy Process (AHP) has been used most widely. However, it is difficult to apply in practice because the AHP results have the characteristics of the independence between each element and the interlayer can not explain the interrelationship. The Network Analysis Process (ANP) is possible to analyze the relationship between the elements and the network through the feedback. But, the reliability of the analysis fall because of complicated pair of comparison, also it is difficult to solve the super matrix. In this study, the complicated relationship between each element is inquired through the Interpretive Structural Modeling (ISM). RESULTS : The methodology of ISM is developed to remove the children's potential risk factors in school zone. CONCLUSIONS : It is possible to remove the children's potential risk factors from low level to high level step by step and improve safety. Through this, risk factors can be removed from the low-level, and upper-level will automatically improve.

• Korean Journal of Materials Research
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• v.16 no.2
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• pp.137-143
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• 2006

The effects of Cu and Fe additions on the thermal stability, microstructure and mechanical properties of $Al_{85}-Ni_{8.5}-Mm_{6.5},\;Al_{84}-Ni_{8.5}-Mm_{6.5}Cu_1,\;Al_{84}-Ni_{8.5}-M_{m6.5}Fe_1$ alloys, manufactured by gas atomization, degassing and hot-extrusion were investigated. Gas atomization, with a wide super-cooled liquid region, allowed the alloy powders to exhibit varying microstructure depending primarily on the powder size and composition. Al hotextruded alloys consisted of homogeneously-distributed fine-grained fcc-Al matrix and intermetallic compounds. A substitution of 1 at.% Al by Cu increased the thermal stability of the amorphous phase and produced alloy microstructure with smaller fcc-Al grains. On the other hand, the same substitution of 1 at.% Al by Fe decreased the stability of the amorphous phase and produced larger fcc-Al grains. The formation of intermetallic compounds such as $Al_3Ni,\;Al_{11}Ce_3\;and\;Al_{11}La_3$ was suppressed by the addition of Cu or Fe. Among the three alloys examined, the highest Vickers hardness and compressive strength were obtained for $Al_{84}-Ni_{8.5}-M_{m6.5}Cu_1$ alloy, and related to the finest fcc-Al grain size attained from increased thermal stability with Cu addition.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.4_2
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• pp.683-691
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• 2020

In the era of super-aged societies, research and development (R&D) projects related to aging are very important agenda for establishing the direction of future R&D planning and technological competitiveness in the country. In order to respond promptly to this agenda, it is essential to establish a national-level convergence R&D policy. In this study, we utilized the global R&D funding project data from major nations (US, Europe, Japan), and then standardized them with the same fields. To analyze the current status of global R&D related to aging, we performed cluster analysis based on the co-occurrence matrix to explore convergence R&D areas in the US, Europe, and Japan related to aging. In addition, comparative analysis by country suggested that different points on the interdisciplinary area and the convergence of aging-related R&D by each country. These results provide fundamental understandings for the status of convergence in aging-related global R&D, the current technology trends, and establish the direction and strategy of R&D policy.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.03a
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• pp.329-336
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• 2003

The box system that is composed only of reinforced concrete walls and slabs are adopted on many high-rise apartment buildings recently constructed in Korea. And the framed structure with shear wall core that can effectively resist horizontal forces is frequently adopted for the structural system for high-rise building structures. In these structures, a shear wall may have one or more openings for functional reasons. It is necessary to use subdivided finite elements for accurate analysis of the shear wall with openings. But it would take significant amount of computational time and memory if the entire building structure is subdivided into a finer mesh. An efficient analysis method that can be used regardless of the number, size and location of openings is proposed in this study. The analysis method uses super element, substructure, matrix condensation technique and fictitious beam technique. Three-dimensional analyses of the box system and the framed structure with shear wall core having various types of openings were peformed to verify the efficiency of the proposed method. It was confirmed that the proposed method have outstanding accuracy with drastically reduced time and computer memory from the analyses of example structures.

• Corrosion Science and Technology
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• v.20 no.2
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• pp.62-68
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• 2021

Artificial neural network techniques show an excellent ability to predict the data (output) for various complex characteristics (input). It is primarily specialized to solve nonlinear relationship problems. This study is an experimental investigation that applies artificial neural network techniques and an experimental design to predict the cyclic polarization curves of the super-austenitic stainless steel AL-6XN alloy with sensitization. A cyclic polarization test was conducted in a 3.5% NaCl solution based on an experimental design matrix with various factors (degree of sensitization, temperature, pH) and their levels, and a total of 36 cyclic polarization data were acquired. The 36 cyclic polarization patterns were used as training data for the artificial neural network model. As a result, the supervised learning algorithms with back-propagation showed high learning and prediction performances. The model showed an excellent training performance (R²=0.998) and a considerable prediction performance (R²=0.812) for the conditions that were not included in the training data.

• Corrosion Science and Technology
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• v.20 no.6
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• pp.466-474
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• 2021

A wet type scrubber for merchant vessel uses super austenitic stainless steels with pitting resistance equivalent number (PREN) of 40 or higher for operation in a harsh corrosive environment. However, it is expensive due to a high nickel content. Thus, electrochemical behavior and cavitation erosion characteristics of UNS S32750 as an alternative material were investigated. Microstructure analysis revealed fractions of ferritic and austenitic phases of 48% and 52%, respectively, confirming the existence of ferritic matrix and austenitic island. Potentiodynamic polarization test revealed damage at the interface of the two phases because of galvanic corrosion due to different chemical compositions of ferritic and austenitic phases. After a cavitation test, a compressive residual stress was formed on the material surface due to impact pressure of cavity. Surface hardness was improved by water cavitation peening effect. Hardness value was the highest at 30 ㎛ amplitude. Scanning electron microscopy revealed wave patterns due to plastic deformation caused by impact pressure of the cavity. The depth of surface damage increased with amplitude. Cavitation test revealed larger damage caused by erosion in the ferritic phase due to brittle fracture derived from different strain rate sensitivity index of FCC and BCC structures.

• Corrosion Science and Technology
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• v.21 no.6
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• pp.445-453
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• 2022

SiO_x was prepared from a mixture of Si and SiO₂ via high-energy ball milling as a negative electrode material for Li-ion batteries. The molar ratio of Si to SiO₂ as precursors and the milling time were varied to identify the synthetic condition that could exhibit desirable anode performances. With an appropriate milling time, the material showed a unique microstructure in which amorphous Si nanoparticles were intimately embedded within the SiO₂ matrix. The interface between the Si and SiO₂ was composed of silicon suboxides with Si oxidation states from 0 to +4 as proven by X-ray photoelectron spectroscopy and electrochemical analysis. With the addition of a conductive carbon (Super P carbon black) as a coating material, the SiO_x/C manifested superior specific capacity to a commercial SiO_x/C composite without compromising its cycle-life performance. The simple mechanochemical method described in this study will shed light on cost-effective synthesis of high-capacity silicon oxides as promising anode materials.

• Korean Journal of Materials Research
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• v.10 no.7
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• pp.489-492
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• 2000

Three different white cast irons alloyed with Cr and Si were prepared in order to study their distribution be-havior in matrices and carbides. The specimens were produced using a 15kg-capacity high frequency induction fur-nace. Melts were super-heated to $1600^{\circ}C$, and poured at $1550^{\circ}C$ into a pepset mold. Three combinations of the alloys were selected so as to observe the distribution behavior of Cr and Si : 0.5%C-25.0%Cr-1.0%Si(alloy No. 1), 0.5%C-5.0%Cr-1.0%Si(alloy No. 2) and 2.0%C-5.0%Cr-1.0%Si(alloy No. 3). Cellular $M_7C_3$ carbides-$\delta$ferrite eutectic were developed at $\delta$ferrite liquid interfaces in the alloy No. 1 while only traces of $M_7C_3$ carbides-$\delta$ferrite eutectic were precipitated in the alloy No. 2. With the addition of 2.0% C and 5.0% Cr, ledeburitic $M_3C$ carbides instead of cellular $M_7C_3$ carbides were precipitated in the alloy No. 3. Cr was distributed preferentially to the $M_7C_3$ carbides rather than to the matrix structure while more Si was partitioned in the matrix structure rather than the $M_7C_3$ carbides. $K^m$ for Cr was ranged from 0.56 to 0.68 while that for Si was from 1.12 to 1.28. $K^m$ for Cr had a lower value with increased carbon contents. The mass percent of Cr was higher in the $M_7C_3$ carbides with increased Cr contents.

• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.105-120
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• 2019

The World Health Organization (WHO) and other government agencies aroundthe world have warned against antibiotic-resistant bacteria due to abuse of antibiotics and are strengthening their care and monitoring to prevent infection. However, it is highly necessary to develop an expeditious and accurate prediction and estimating method for preemptive measures. Because it takes several days to cultivate the infecting bacteria to identify the infection, quarantine and contact are not effective to prevent spread of infection. In this study, the disease diagnosis and antibiotic prescriptions included in Electronic Health Records were embedded through neural embedding model and matrix factorization, and deep learning based classification predictive model was proposed. The f1-score of the deep learning model increased from 0.525 to 0.617when embedding information on disease and antibiotics, which are the main causes of antibiotic resistance, added to the patient's basic information and hospital use information. And deep learning model outperformed the traditional machine hospital use information. And deep learning model outperformed the traditional machine learning models.As a result of analyzing the characteristics of antibiotic resistant patients, resistant patients were more likely to use antibiotics in J01 than nonresistant patients who were diagnosed with the same diseases and were prescribed 6.3 times more than DDD.