• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.5
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• pp.323-330
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• 2023

The development of an analysis model that reflects the microstructure characteristics of polyvinyl alcohol (PVA) fiber-reinforced cementitious composites, which have a highly complex microstructure, enables synergy between efficient material design and real experiments. PVA fiber orientations are an important factor that influences the mechanical behavior of PVA fiber-reinforced cementitious composites. Owing to the difficulty in distinguishing the gray level value obtained from micro-CT images of PVA fibers from adjacent phases, fiber segmentation is time-consuming work. In this study, a micro-CT test with a voxel size of 0.65 ㎛³ was performed to investigate the three-dimensional distribution of fibers. To segment the fibers and generate training data, histogram, morphology, and gradient-based phase-segmentation methods were used. A U-net model was proposed to segment fibers from micro-CT images of PVA fiber-reinforced cementitious composites. Data augmentation was applied to increase the accuracy of the training, using a total of 1024 images as training data. The performance of the model was evaluated using accuracy, precision, recall, and F1 score. The trained model achieved a high fiber segmentation performance and efficiency, and the approach can be applied to other specimens as well.

• The Journal of Engineering Geology
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• v.33 no.4
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• pp.611-626
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• 2023

Overseas examples of the characterization stage of site selection proposed by the International Atomic Energy Agency were reviewed to highlight the factors necessary for consideration in the deep disposal of high-level radioactive waste. Studies in Sweden, Finland, the USA, and Canada were considered. Site investigations in Sweden and Finland commonly covered the fields of geology, hydrogeology, and hydrogeochemistry using similar field investigation techniques. The USA considered survey groups and factors under pre- and post-lockdown guidelines, as well as those for desaturated and saturated surveys. involving geophysical, hydrological, hydrogeological, hydrogeochemical, mechanical/physical, and thermal-characterization investigations. Canada provided a list of investigative methods for both preliminary and detailed site assessments including geological, physical, boring, hydrological, laboratory testing, and chemical analysis studies. Results of this study should elucidate site-selection investigation factors and survey methods applicable to Korea.

• Journal of Biomedical Engineering Research
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• v.44 no.6
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• pp.404-413
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• 2023

In this research, we studied the development of a SUS304 microneedle array based on microfabrication technology and the applicability of Parylene-C thin film, a medical polymer material. First of all, four materials commonly used in the field of medical engineering (SUS304, Ti, PMMA, and PEEK) were selected and a 5 ㎛ Parylene-C thin film was deposited. The applicability of Parylene-C coating to each material was confirmed through SEM analysis, contact angle measurement, surface roughness(Ra) measurement, and adhesion test according to ASTM standards for each specimen. Parylene-C thin film was deposited based on chemical vapor deposition (CVD), and a 5 ㎛ Parylene-C deposition process was established through trial and error. Through characteristic experiments to confirm the applicability of Parylene-C, SUS304 material, which is the easiest to apply Parylene-C coating without pretreatment was selected to develop a microneedle array based on CNC micromachining technology. The CNC micromachining process was divided into a total of 5 steps, and a microneedle array consisting of 19 needles with an inner diameter of 200 ㎛, an outer diameter of 400 ㎛, and a height of 1.4 mm was designed and manufactured. Finally, a 5 ㎛ Parylene-C coated microneedle array was developed, which presented future research directions in the field of microneedle-based drug delivery systems.

• Composites Research
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• v.36 no.5
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• pp.297-302
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• 2023

There are several methods for shaping foams, but the most commonly used methods involve the use of resin mixed with a foaming agent, which is then foamed under high temperature and pressure in the case of compression foaming, or foamed under high temperature without applying pressure in the case of atmospheric foaming. The polymers used for foaming require design and analysis of optimal foaming conditions in order to achieve foaming under ambient pressure. Environmentally friendly bio-based polymers face challenges when it comes to foaming on their own, which has led to ongoing research in blending them with resins capable of traditional foam production. This study investigates changes in the characteristics of bio-based polymer-EVA blend foams based on variations in the content of bio-based polymers and explores the optimal foaming conditions according to crosslinking. The correlation between foaming characteristics and mechanical properties of the foams was examined. Through this research, we gained insights into how the content of bio-based polymers affects the properties of foams containing bio-based polymers and identified differences between ambient pressure and high-pressure foaming processes. Additionally, the feasibility of commercializing bio-based polymer-EVA composite foams was confirmed.

• Journal of the Korean GEO-environmental Society
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• v.24 no.12
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• pp.5-11
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• 2023

Economic damage is occurring due to landslides and debris flows that occur when the ground artificially created for roads or photovoltaic power generation facilities is weakened by rainfall such as torrential rain. In order to understand the stability of the artificially created ground, it is very important to check the ground information such as the compositional state and mechanical characteristics of the stratum. However, since most of the investigation sites are steep slopes or there are no access roads, it is not easy to enter the drilling equipment commonly used to check ground information and perform standard penetration tests. In this study, a dynamic cone penetration test (DCP) device using a miniaturized auger drilling equipment and an automatic drop device was developed to check the cone resistance value and the dynamic cone penetration test value and analyze the correlation with the standard penetration test value to confirm its applicability at the mountain solar power generation site. As a result, the cone resistance value is q_d = 0.46 N and the dynamic cone penetration test value is N_d = 1.58 N, confirming a value similar to the results of existing researchers to secure its reliability.

• Composites Research
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• v.36 no.5
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• pp.355-360
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• 2023

Epoxy-based carbon fibers reinforced plastic (CFRP) exhibit limitations in their suitability for industrial applications due to high brittleness characteristics. To address this challenge, extensive investigations are underway to enhance their toughness properties. This research focuses on evaluating the toughening mechanisms achieved by Polyamide 6 particles(p-PA6) and Carboxyl-Terminated Butadiene-Acrylonitrile (CTBN) elastomer, with a specific emphasis on utilizing minimal additive quantities. The study explores the impact of varying concentrations of p-PA6 and CTBN additives, namely 0.5, 1, 2.5, and 5 phr, through comprehensive Mode I fracture toughness and tensile strength analyses. The inclusion of p-PA6 demonstrated improvements in toughness when introduced at a relatively low content of 1phr. This improvement manifested as a sustained fracture behavior, contributing to enhanced toughness, while simultaneously maintaining the material's tensile strength. Furthermore, the investigation revealed that the incorporation of p-PA6 affected in particle aggregation, thus influencing the overall toughening mechanism. Incorporation of CTBN, an elastomeric modifier, exhibited a pronounced increase in fracture toughness at higher concentrations of 2.5 phr and beyond. However, this increase in toughness was accompanied by a reduction in tensile strength, resulting in fracture behavior similar to conventional CFRP exhibiting brittleness. The synergy between pPA6, CTBN and CFRP appeared to marginally enhance tensile strength under specific content conditions. As a result of this study, optimized conditions for the application of the p-PA6, CTBN toughening technology have been identified and established.

• Journal of the Korean Society of Safety
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• v.38 no.5
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• pp.8-14
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• 2023

Lithium ions can induce the thermal runaway phenomenon and lead to reignition due to electrical, mechanical, and environmental factors such as high temperature, smoke generation, explosions, or flames, which is extremely likely to create safety concerns. Therefore, one of the ways to improve the flame retardancy of the electrolyte is to use a flame-retardant additive. Comparing the associated characteristic value of existing substances with the required experimental value, it was found that these values were either considerably different or were not documented. It is vital to know a substance's combustion characteristic values, flash point, explosion limit, and autoignition temperature (AIT) as well as its combustion characteristics before using it. In this research, the flash point and AIT of materials were measured by mixing a highly volatile and flammable substance, diethyl carbonate (DEC), with flame-retardant dimethyl methylphosphonate (DMMP). The flash point of DEC, which is a pure substance, was 29℃, and that for DMMP was 65℃. Further, the lower explosion limit calculated using the measured flash point of DEC was 1.79 Vol.%, while that for DMMP was 0.79 Vol.%. The AIT was 410℃ and 390℃ for DEC and DMMP, respectively. In particular, since the AIT of DMMP has not been discussed in any previous study, it is necessary to ensure safety through experimental values. In this study, the experimental and regression analysis revealed that the average absolute deviation (ADD) for the flash point of the DEC+DMMP DEC+DMMP system is 0.58 sec and that the flash point tends to increase according to changes in the composition employed. It also revealed that the AAD for the AIT of the mixture was 3.17 sec and that the AIT tended to decrease and then increase based on changes in the composition.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.165-184
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• 2023

Recently, Deep learning analysis of unstructured text data using language models, such as Google's BERT and OpenAI's GPT has shown remarkable results in various applications. Most language models are used to learn generalized linguistic information from pre-training data and then update their weights for downstream tasks through a fine-tuning process. However, some concerns have been raised that privacy may be violated in the process of using these language models, i.e., data privacy may be violated when data owner provides large amounts of data to the model owner to perform fine-tuning of the language model. Conversely, when the model owner discloses the entire model to the data owner, the structure and weights of the model are disclosed, which may violate the privacy of the model. The concept of offsite tuning has been recently proposed to perform fine-tuning of language models while protecting privacy in such situations. But the study has a limitation that it does not provide a concrete way to apply the proposed methodology to text classification models. In this study, we propose a concrete method to apply offsite tuning with an additional classifier to protect the privacy of the model and data when performing multi-classification fine-tuning on Korean documents. To evaluate the performance of the proposed methodology, we conducted experiments on about 200,000 Korean documents from five major fields, ICT, electrical, electronic, mechanical, and medical, provided by AIHub, and found that the proposed plug-in model outperforms the zero-shot model and the offsite model in terms of classification accuracy.

• Journal of Drive and Control
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• v.20 no.4
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• pp.115-122
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• 2023

This study utilized a discrete element method (DEM) simulation, as one of the virtual field trials, to predict the impact of tillage depth on the rotary blade shaft during rotavator tilling. The virtual field for the simulation was generated according to soil properties observed in an actual field. Following the generation of particles for the virtual field, a sequence of calibration steps followed to align the mechanical properties more closely with those of real soil. Calibration was conducted with a focus on bulk density and shear torque, resulting in calibration errors of just 0.02% for bulk density and 0.52% for shear torque. The prediction of the load on a rotary tiller's blade shaft involved a three-pronged approach, considering shaft torque, draft force, and vertical force. In terms of shaft torque, the values exhibited significant increases of 42.34% and 36.91% for every 5-centimeter increment in tillage depth. Similarly, the vertical force saw substantial growth by 40.41% and 36.08% for every 5-centimeter increment. In contrast, the variation in draft force based on tillage depth was comparatively lower at 18.49% and 0.96%, indicating that the effect of tillage depth on draft force was less pronounced than its impact on shaft torque and vertical force. From a perspective of agricultural machinery research, this study provides valuable insights into the DEM soil modeling process, accounting for changes in soil properties with varying tillage depths. These findings are expected to be instrumental in future agricultural machinery design studies.

• Journal of Korea Foundry Society
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• v.43 no.6
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• pp.279-285
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• 2023

In order to predict the mechanical properties of ductile cast iron heat treated in an intercritical temperature range, samples machined from cast iron with a tensile strength of 450 MPa were heat-treated at various intercritical temperatures and air-cooled, after which a microstructural analysis and Brinell hardness test were conducted. As the heat treatment temperature was increased in the intercritical temperature range, the ferrite fraction in the ductile cast iron decreased and the pearlite fraction increased, whereas the nodularity and nodule count did not change considerably from the corresponding values in the as-cast condition. The Brinell hardness values of the heat-treated ductile cast iron increased gradually as the heat treatment temperature was increased. Based on the measured alloy composition, the fraction of each stable phase and the hardness model from the literature, the hardness of the ductile cast iron heat treated in the intercritical temperature range was calculated, showing values very similar to the measured hardness data. In order to check whether it is possible to predict the hardness of heat-treated ductile cast iron by using the phase fraction obtained from thermodynamic calculations, the volumes of graphite, ferrite, and austenite in the alloy were calculated for each temperature condition. Those volume fractions were then converted into areas of each phase for hardness prediction of the heat-treated ductile cast iron. The hardness values of the cast iron samples based on thermodynamic calculations and on the hardness prediction model were similar within an error range up to 27 compared to the measured hardness data.