• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.7
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• pp.471-478
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• 2022

This paper is about research and development of Korea Aerospace University's Solar-Powered UAV System that named of KAU-SPUAV, and describes the design process of the 4.2 m solar UAV that succeeded in a long flight of 32 hours and 19 minutes at June 2020. In order to improve the long-term flight performance of the KAU-SPUAV, For reduce drag, a circular cross-section of the fuselage was designed, and manufactured light and sturdy fuselage by applying a monocoque structure using a glass fiber composite material. In addition, a solar module optimized for the wing shape of a 4.2 m solar drone was constructed and arranged, and a propulsion system applied with the 23[in] × 23[in] propeller was constructed to improve charging and flight efficiency. The developed KAU-SPUAV consumes an average of 55W when cruising and can receive up to 165W of energy during the day, and its Long-term Endurance was verified through flight tests.

• Journal of the Korean Geotechnical Society
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• v.38 no.4
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• pp.21-32
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• 2022

Steel pile foundations are widely used for offshore constructions due to their high bearing capacity and efficiency. Typically, offshore structures that have reached the end of their design life are required to be demolished. However, pile foundations are often left on site due to technical and economic limitations. The pile left on the site not only pollutes the environment, but can also cause obstacles for the construction of new structures. Therefore, research is required to completely eliminate these foundations at the site. In this study, a new type of double-wall pile foundation that can drastically reduce the pull-out load was conceptually proposed, and a series of model tests were performed to validate the performance of the double-wall pile foundation. The installation and extraction of the double-wall pile were simulated in dry sand in the model test, and the measured up-lift load was compared to that of the conventional pile. According to the result, the maximum up-lift load induced by the decommissioning of the double-wall pile was reduced by 45% when compared to the traditional pile in dense sand. This study verified the mechanism for reducing the up-lift load of the double-wall foundation and confirmed the possibility of completely decommissioning a pile that has reached the end of its nominal service life.

• Journal of the Korea Institute of Building Construction
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• v.22 no.3
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• pp.251-258
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• 2022

In the cement industry, in order to reduce CO₂ emissions, technology for raw materials substitution and conversion, technology for improving process efficiency of utilizing low-carbon new heat sources, and technology for collecting and recycling process-generated CO₂ are being developed. In this study, we conducted a basic experiment to contribute to the development of CSC that can store CO₂ as carbonate minerals among process-generated CO₂ capture and recycling technologies. Three types of CSC clinker with different SiO₂/(CaO+SiO₂) molar ratios were prepared with the clinker raw material formulation, and the characteristics of the clinker were analyzed. As a result of analysis and observation of CSC clinker, wollastonite and rankinite were formed. In addition, as a result of the carbonation test of the CSC paste, it was confirmed that calcite was produced as a carbonation product. The lower the SiO₂/(CaO+SiO₂) molar ratio in the CSC clinker chemical composition, the lower the wollastonite production amount, and the higher the rankinite production amount. And the amount of calcite production increased with the progress of carbonation of the CSC paste specimen. It is judged that rankinite is more reactive in mineralizing CO₂ than wollastonite.

• Resources Recycling
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• v.31 no.4
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• pp.3-11
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• 2022

Owing to the increasing demand for electric vehicles (EVs), appropriate management of their waste batteries is required urgently for scrapped vehicles or for addressing battery aging. With respect to technological developments, data-driven diagnosis of waste EV batteries and management technologies have drawn increasing attention. Moreover, robot-based automatic dismantling technologies, which are seemingly interesting, require industrial verifications and linkages with future battery-related database systems. Among these, it is critical to develop and disseminate various advanced battery diagnosis and assessment techniques to improve the efficiency and safety/environment of the recirculation of waste batteries. Incorporation of lithium-related chemical substances in the public pollutant release and transfer register (PRTR) database as well as in-depth risk assessment of gas emissions in waste EV battery combustion and their relevant fire safety are some of the necessary steps. Further research and development thus are needed for optimizing the lifecycle management of waste batteries from various aspects related to data-based diagnosis/classification/disassembly processes as well as reuse/recycling and final disposal. The idea here is that the data should contribute to clean design and manufacturing to reduce the environmental burden and facilitate reuse/recycling in future production of EV batteries. Such optimization should also consider the future technological and market trends.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.5
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• pp.127-134
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• 2022

In this study, RCPTs (Rapid Chloride Penetration Test) were performed for fly ash concrete with curing age of 4 ~ 6 years. The concrete mixtures were prepared with 3 levels of water to binder ratio (0.37, 0.42, and 0.47) and 2 levels of substitution ratio of fly ash (0 and 30%), and the improved passed charges of chloride ion behavior were quantitatively analyzed. Additionally, the results were trained through the univariate time series models consisted of GRU (Gated Recurrent Unit) algorithm and those from the models were evaluated. As the result of the RCPT, fly ash concrete showed the reduced passed charges with period and an more improved resistance to chloride penetration than OPC concrete. At the final evaluation period (6 years), fly ash concrete showed 'Very low' grade in all W/B (water to binder) ratio, however OPC concrete showed 'Moderate' grade in the condition with the highest W/B ratio (0.47). The adopted algorithm of GRU for this study can analyze time series data and has the advantage like operation efficiency. The deep learning model with 4 hidden layers was designed, and it provided a reasonable prediction results of passed charge. The deep learning model from this study has a limitation of single consideration of a univariate time series characteristic, but it is in the developing process of providing various characteristics of concrete like strength and diffusion coefficient through additional studies.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.261-269
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• 2021

Without any validation of the incompressible assumption, most of previous studies on cavitation flow and its noise have utilized numerical methods based on the incompressible Reynolds Average Navier-Stokes (RANS) equations because of advantage of its efficiency. In this study, to investigate the effects of the flow compressibility on the Tip Vortex Cavitation (TVC) flow and noise, both the incompressible and compressible simulations are performed to simulate the TVC flow, and the Ffowcs Williams and Hawkings (FW-H) integral equation is utilized to predict the TVC noise. The DARPA Suboff submarine body with an underwater propeller of a skew angle of 17 degree is targeted to account for the effects of upstream disturbance. The computation domain is set to be same as the test-section of the large cavitation tunnel in Korea Research Institute of Ships and Ocean Engineering to compare the prediction results with the measured ones. To predict the TVC accurately, the Delayed Detached Eddy Simulation (DDES) technique is used in combination with the adaptive grid techniques. The acoustic spectrum obtained using the compressible flow solver shows closer agreement with the measured one.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.6
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• pp.787-792
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• 2022

In winter, the excessive use of deicing salt deteriorates concrete pavement durability. To reduce the amount of deicing salt used, phase-change materials (PCMs) potentially offer an alternative way to melt snow through their latent heat storage characteristics. In this research, thermal energy storage concrete was developed by using PCM-impregnated expanded clay as 50 % replacement to normal aggregate by volume. In addition, to improve the thermal efficiency of PCM lightweight aggregate (PCM-LWA)-incorporated concrete, multi-walled carbon nanotubes (MWCNTs) were incorporated in proportions of 0.10 %, 0.15 %, and 0.20 % by binder weight. Compressive strength testing and programmed thermal cycling were performed to evaluate the mechanical and thermal responses of the PCM-LWA concrete. Results showed a significant strength reduction of 54 % due to the PCM-LWA; however, the thermal performance of the PCM-LWA concrete was greatly improved with the addition of MWCNTs. Thermal test results showed that 0.10 % MWCNT-incorporated concrete had high thermal fatigue resistance as well as uniform heat flow, whereas specimens with 0.15 % and 0.20 % MWCNT content had a reduced thermal response due to supercooling when the ambient temperature was varied between -5℃ and 10℃.

• The Journal of Sustainable Design and Educational Environment Research
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• v.21 no.4
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• pp.21-28
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• 2022

This study analyzes the reality of the overall operating system, such as recognition and satisfaction with school field support work system of the Education Facilities Management Center, recognition level of restructuring of work areas, and the direction of improvement for school facility maintenance support in various types of future learning environments. To analyze the problem of this study, a survey was conducted on 290 education administrative officials in Gyeonggi-do. First, school site awareness and work performance satisfaction of the Educational Facilities Management Center were evaluated as "below average," and it is necessary to improve the qualitative work area that is practically helpful to schools. Second, in the area of organizational operation, it is desirable to avoid simple tasks with a low evaluation of "below average" and to switch to an operating system that improves efficiency. Third, the need for the facility environment area (professionalism, safety) was the highest, but the center's ability and work processing level were evaluated very low as "below average," so it is urgent to improve the center's capacity. Fourth, in the area of social and educational policy change, the center received a high score for the need for access from the perspective of a learning environment linked to future education. Therefore, a policy review on the restructuring and improvement of work areas suitable for this is necessary.

• Membrane Journal
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• v.32 no.2
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• pp.140-149
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• 2022

In this study, the conditions of low temperature and high pressure of biogas upgrading process using polysulfone membrane have been designed and tested to achieve the high recovery and efficiency corresponding to those of the highly selective polymeric materials. Polysulfone hollow fiber membrane with 4-component dope solution was spun via non-solvent induced phase separation. The hollow fiber membrane was mounted into a 1.5 inch housing. The effective area was 1.6 m², and its performance was examined in various operation temperatures and pressures. CO₂ and CH₄ permeances were 412 and 12.7 GPU at 20℃, and 280 and 3.6 GPU at -20℃, respectively, while the CO₂/CH₄ selectivity increased from 32.4 to 77.8. Single gas test was followed by the mixed gas experiments using single-stage and double stage where the membrane area ratio varied from 1:1 to 1:3. At the single-stage, CH₄ purity increased and the recovery decreased as the stage-cut increased. At the double stage, the area ratio of 1:3 showed the higher CH₄ recovery as decreasing the operation temperature at the same purity of CH₄ 97%. Finally, polysulfone hollow fiber membranes have yielded of both CH₄ purity and recovery of 97% at -20℃ and 16 barg.

• Smart Structures and Systems
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• v.29 no.4
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• pp.625-640
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• 2022

Maglev rail joints are vital components serving as connections between the adjacent F-type rail sections in maglev guideway. Damage to maglev rail joints such as bolt looseness may result in rough suspension gap fluctuation, failure of suspension control, and even sudden clash between the electromagnets and F-type rail. The condition monitoring of maglev rail joints is therefore highly desirable to maintain safe operation of maglev. In this connection, an online damage detection approach based on three-dimensional (3D) convolutional neural network (CNN) and time-frequency characterization is developed for simultaneous detection of multiple damage of maglev rail joints in this paper. The training and testing data used for condition evaluation of maglev rail joints consist of two months of acceleration recordings, which were acquired in-situ from different rail joints by an integrated online monitoring system during a maglev train running on a test line. Short-time Fourier transform (STFT) method is applied to transform the raw monitoring data into time-frequency spectrograms (TFS). Three CNN architectures, i.e., small-sized CNN (S-CNN), middle-sized CNN (M-CNN), and large-sized CNN (L-CNN), are configured for trial calculation and the M-CNN model with excellent prediction accuracy and high computational efficiency is finally optioned for multiple damage detection of maglev rail joints. Results show that the rail joints in three different conditions (bolt-looseness-caused rail step, misalignment-caused lateral dislocation, and normal condition) are successfully identified by the proposed approach, even when using data collected from rail joints from which no data were used in the CNN training. The capability of the proposed method is further examined by using the data collected after the loosed bolts have been replaced. In addition, by comparison with the results of CNN using frequency spectrum and traditional neural network using TFS, the proposed TFS-CNN framework is proven more accurate and robust for multiple damage detection of maglev rail joints.