• Journal of the Korean Society of Safety
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• v.12 no.4
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• pp.214-219
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• 1997

The mechanical seals, which are installed in rotating machines like pump and compressor, are generally used as sealing devices in the many fields of industries. The failure of mechanical seals such as leakage, crack, breakage, fast and severe wear, excessive torque, and squeaking results in big problems. To identify abnormal phenomena on mechanical seals and to propose the proper monitoring parameter for the failure of mechanical seals, sliding wear experiments were conducted. Acoustic emission, torque, and temperature were measured during experiments. Optical microstructure was observed for the wear processing after every 10 minute sliding at rotation speed of 1750 rpm and scanning electron microscopy was also observed. Except for the initial part of every experiment, the variation of acoustic emission was well coincided with torque variation during the experiments. This study concludes that acoustic emission and torque are proper monitoring parameters for the failure of mechanical seals. The intensity of acoustic emission signals is measured in root mean square voltage. Temperature of sealing face will be used as a parallel parameter for increasing the reliability of monitoring system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.5
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• pp.563-569
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• 2012

The superheater and reheater tubes of a heavy-load fossil power plant boiler can be damaged by overheating, and therefore, the degree of overheating is assessed by measuring the oxide scale thickness inside the tube during outages. The tube temperature prediction from the oxide scale thickness measurement is necessarily accompanied by destructive tube sampling, and the result of tube temperature prediction cannot be expected to be accurate unless the selection of the overheated point is precise and the initial-operation tube temperature has been obtained. In contrast, if the tube temperature is to be predicted analytically, considerable effort (to carry out the analysis of combustion, radiation, convection heat transfer, and turbulence fluid dynamics of the gas outside the tube) is required. In addition, in the case of analytical tube temperature prediction, load changes, variations in the fuel composition, and operation mode changes are hardly considered, thus impeding the continuous monitoring of the tube temperature. This paper proposes a method for the short-term prediction of tube temperature; the method involves the use of boiler operation information and flow-network-analysis-based tube heat flux. This method can help in high-temperaturedamage monitoring when it is integrated with a practical tube-damage-assessment method such as the Larson-Miller Parameter.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.194-204
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• 2020

Cultivar parameters, which are key inputs to a crop growth model, have been estimated using observation data in good quality. Observation data with high quality often require considerable labor and cost, which makes it challenging to gather a large quantity of data for calibration of cultivar parameters. Alternatively, data in sufficient quantity can be collected from the reports on the evaluation of cultivars by region although these data are of questionable quality. The objective of our study was to assess the quality of crop and management data available from the reports on the regional adaptation trials for rice cultivars. We also aimed to propose the measures for improvement of the data quality, which would aid reliable estimation of cultivar parameters. DatasetRanker, which is the tool designed for quantitative assessment of the data for parameter calibration, was used to evaluate the quality of the data available from the regional adaptation trials. It was found that these data for rice cultivars were classified into the Silver class, which could be used for validation or calibration of key cultivar parameters. However, those regional adaptation trial data would fall short of the quality for model improvement. Additional information on management, e.g., harvest and irrigation management, can increase the quantitative quality by 10% with the minimum effort and cost. The quality of the data can also be improved through measurements of initial conditions for crop growth simulations such as soil moisture and nutrients. In addition, crop model improvement can be facilitated using crop growth data in time series, which merits further studies on development of approaches for non-destructive methods to monitor the crop growth.

• Ocean and Polar Research
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• v.29 no.1
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• pp.9-31
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• 2007

Most seismic sea waves in the East Sea originate from earthquakes occurring near the Japanese west coast. While the waves propagate in the East Sea, they are deformed by refraction, diffraction and scattering. Though the Boussinesq equation is most applicable for such wave phenomena, it was not used in numerical modelling of seismic sea waves in the East Sea. To examine characteristics of seismic sea waves in the East Sea, numerical models based on the Boussinesq equation are established and used to simulate recent tsunamis. By considering Ursell parameter and Kajiura parameter, it is proved that Boussinesq equation is a proper equation for seismic sea waves in the East Sea. Two models based on the Boussinesq equation and linear wave equation are executed with the same initial conditions and grid size ($1min{\times}1min$), and the results are compared in various respects. The Boussinesq equation model produced better results than the linear model in respect to wave propagation and concentration of wave energy. It is also certified that the Boussinesq equation model can be used for operational purpose if it is optimized. Another Boussinesq equation model whose grid size is $40sec{\times}30sec$ is set up to simulate the 1983 and 1993 tsunamis. As the result of simulation, new propagation charts of 2 seismic sea waves focused on the Korean east coast are proposed. Even though the 1983 and 1993 tsunamis started at different areas, the propagation paths near the Korean east coast are similar and they can be distinguished into 4 paths. Among these, total energy and propagating time of the waves passing over North Korea Plateau(NKP) and South Korea Plateau(SKP) determine wave height at the Korean east coast. In case of the 1993 tsunami, the wave passing over NKP has more energy than the wave over SKP. In case of the 1983 tsunami, the huge energy of the wave passing over SKP brought about great maximum wave heights at Mukho and Imwon. The Boussinesq equation model established in this study is more useful for simulation of seismic sea waves near the Korean east coast than it is the Japanese coast. To improve understanding of seismic sea waves in shallow water, a coastal area model based on the Boussinesq equation is also required.

• Journal of the Korean Magnetics Society
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• v.18 no.3
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• pp.120-125
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• 2008

In this study, NiCoZn ferrites with the variation of sintering temperature and chemical composition were prepared by the coprecipitation. Microstructures Crystal structure of NiCoZn ferrites were analyzed by XRD and their electric magnetic characteristics were analyzed by LCR meter and their morphology observed by SEM. We identified that these powders have a typical NiCoZn spinel structure and nanoparticles average size of 40 nm. The impurity, the initial permeability and the Q factor value are the lowest of sintered NiCoZn ferrite at $1250^{\circ}C$. Also, we measured S-parameter for $(Ni_{0.4}Co_{0.1}Zn_{0.5})Fe_2O_4$ which showed a maximum reflection loss of -3.1 dB at 6 GHz for the 2 mm thick sample. From this result, we found that the NiCoZn ferrite can be used in ferrite microwave-absorbing application at a higher frequency region (> 6 GHz).

• Korean Journal of Head & Neck Oncology
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• v.24 no.1
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• pp.47-52
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• 2008

Purpose：The incidence of papillary thyroid microcarcinoma(PTMC) has increased due to the widespread use of high resolution ultrasonography and fine-needle aspiration biopsy. However, the clinical and biologic behaviors of PTMC is debatable. The aim of this study was to describe clinicopathologic features of PTMC and to suggest whether tumor size(5mm) might prove the useful parameter for determining the surgical strategy in PTMC. Material and Methods：From Jan. 2000 to Dec. 2005, 1355 of 2678 patients with papillary thyroid carcinoma were identified as having PTMC, based on tumor size${\leq}$10mm(50.6%). Among patients with PTMC, we further separated tumors<5mm(minute group：group M) from those 5 to 10mm(tiny group：group T). We compared the clinicopathological characteristics and the TNM stagings between two groups. Results：There were 114(8.4%) men and 1241(91.6%) women with a median age of 47 years(range；13-79). During a mean follow-up of 47.3(range；22-93), 13 patients(1.0%) developed locoregional recurrences and 3 patients(0.2%) showed distant metastases at initial presentation. Statistical analysis revealed that the presence of extracapsular invasion(p<0.0001), invasion to adjacent structure(p<0.0001), multifocality(p<0.0001), central lymph node metastasis(p<0.0001), and lateral lymph node metastasis(p<0.0001) were all significantly higher in tiny group(tumor${\geq}$5mm). Furthermore, minute group demonstrated a significantly lower tumor stage(AJCC TNM classification) compared with tiny group(p<0.0001). Conclusion：Patients with PTMC have a favorable treatment outcomes, although the distinction needs to be made with reference to the clinicopathologic behaviors. It would be reasonable to consider that tumor size(5mm) would be useful parameter for the treatment strategy of PTMC.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.58-64
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• 2021

As the number of registered vehicles increases, traffic congestion will worsen worse, which may act as an inhibitory factor for urban social and economic development. Through accurate traffic flow prediction, various AI techniques have been used to prevent traffic congestion. This paper uses the data from a VDS (Vehicle Detection System) as input variables. This study predicted traffic flow in five levels (free flow, somewhat delayed, delayed, somewhat congested, and congested), rather than predicting traffic flow in two levels (free flow and congested). The Catboost model, which is a machine-learning algorithm, was used in this study. This model predicts traffic flow in five levels and compares and analyzes the accuracy of the prediction with other algorithms. In addition, the preprocessed model that went through RandomizedSerachCv and One-Hot Encoding was compared with the naive one. As a result, the Catboost model without any hyper-parameter showed the highest accuracy of 93%. Overall, the Catboost model analyzes and predicts a large number of categorical traffic data better than any other machine learning and deep learning models, and the initial set parameters are optimized for Catboost.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.3
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• pp.92-102
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• 2022

Various numerical analysis models can be used to evaluate the behavior characteristics of tunnel facilities which are representative underground structures. In general, the Mohr-Coulomb model, which is most often used for numerical analysis, is an elastic-perfect plastic behavior model. And the deformation characteristics are the same during the load increase-load reduction phase. So there is a problem that the displacement may appear different from the field situation in the case of excavation analysis. In contrast, the HS-small strain stability model has a wide range of applications for each ground. And it is known that soil deformation characteristics can be analyzed according to field conditions by enabling input of initial elastic modulus and nonlinear curve parameter and so on. However, civil engineers are having difficulty using nonlinear models that can apply material nonlinear properties due to difficulties in estimating ground property coefficients. In this study, the necessity of rational model selection was reviewed by comparing the results of seismic performance evaluation using the Mohr-Coulomb model, which civil engineers generally apply for numerical analysis of tunnels, and the HS Small strain Stiffness model, which can consider ground nonlinearity.

• Composites Research
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• v.36 no.4
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• pp.246-252
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• 2023

A secondary barrier made of glass fiber reinforced composites has been installed infinitely using automatic bonding machine(ABM) in membrane type LNG cargo containment system (CCS). At the same time, significant thermal stress due to cryogenic heat shrinkage has occurred in the composite on the non-bonding area between the adhesive fixation at both ends. There have been studies from the perspective of structural safety evaluation taking this into account, but none that have analyzed mechanical property taking an prolonged length into account. In this study, 2-parameter Weibull distribution statistical analysis was used to standardize reliable mechanical property for actual length, taking into account the composite's brittle fracture of ceramic material with wide fracture strength dispersion. Related experimental data were obtained by performing uniaxial tensile tests at specific temperatures below cryogenic condition considering LNG environment. As a result, the mechanical strength increased about 1.5 times compared to -20℃ at -70℃ and initial non-linear behavior of fiber stretched was suppressed. As the temperature decreased until the cryogenic, the mechanical strength continued to increase due to cold brittleness. The suggested mechanical property in this study would be employed to secure reliable analysis support material property when assessing the safety of secondary barrier's structures.

• Steel and Composite Structures
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• v.48 no.2
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• pp.163-177
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• 2023

Complex and intricate preparation techniques, the imperative for utmost precision and sensitivity in instrumentation, premature sample failure, and fragile specimens collectively contribute to the arduous task of measuring the fracture toughness of concrete in the laboratory. The objective of this research is to introduce and refine an equation based on the gene expression programming (GEP) method to calculate the fracture toughness of reinforced concrete, thereby minimizing the need for costly and time-consuming laboratory experiments. To accomplish this, various types of reinforced concrete, each incorporating distinct ratios of fibers and additives, were subjected to diverse loading angles relative to the initial crack (α) in order to ascertain the effective fracture toughness (Keff) of 660 samples utilizing the central straight notched Brazilian disc (CSNBD) test. Within the datasets, six pivotal input factors influencing the Keff of concrete, namely sample type (ST), diameter (D), thickness (t), length (L), force (F), and α, were taken into account. The ST and α parameters represent crucial inputs in the model presented in this study, marking the first instance that their influence has been examined via the CSNBD test. Of the 660 datasets, 460 were utilized for training purposes, while 100 each were allotted for testing and validation of the model. The GEP model was fine-tuned based on the training datasets, and its efficacy was evaluated using the separate test and validation datasets. In subsequent stages, the GEP model was optimized, yielding the most robust models. Ultimately, an equation was derived by averaging the most exemplary models, providing a means to predict the Keff parameter. This averaged equation exhibited exceptional proficiency in predicting the Keff of concrete. The significance of this work lies in the possibility of obtaining the Keff parameter without investing copious amounts of time and resources into the CSNBD test, simply by inputting the relevant parameters into the equation derived for diverse samples of reinforced concrete subject to varied loading angles.