• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.617-628
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• 2022

A ground support pattern should be designed by properly integrating various support materials in accordance with the rock mass grade when constructing a tunnel, and a technical decision must be made in this process by professionals with vast construction experiences. However, designing supports at the early stage of tunnel design, such as feasibility study or basic design, may be very challenging due to the short timeline, insufficient budget, and deficiency of field data. Meanwhile, the design of the support pattern can be performed more quickly and reliably by utilizing the machine learning technique and the accumulated design data with the rapid increase in tunnel construction in South Korea. Therefore, in this study, the design data and ground exploration data of 48 road tunnels in South Korea were inspected, and data about 19 items, including eight input items (rock type, resistivity, depth, tunnel length, safety index by tunnel length, safety index by rick index, tunnel type, tunnel area) and 11 output items (rock mass grade, two items for shotcrete, three items for rock bolt, three items for steel support, two items for concrete lining), were collected to automatically determine the rock mass class and the support pattern. Three machine learning models (S1, A1, A2) were developed using two machine learning algorithms (SVR, ANN) and organized data. As a result, the A2 model, which applied different loss functions according to the output data format, showed the best performance. This study confirms the potential of support pattern design using machine learning, and it is expected that it will be able to improve the design model by continuously using the model in the actual design, compensating for its shortcomings, and improving its usability.

• Journal of the Korean Geosynthetics Society
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• v.20 no.2
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• pp.23-33
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• 2021

In Korea, many reservoirs have been built for the purpose of solving the food shortage problem and supplying agricultural water. However, the current 75.6% of the reservoirs are in serious aged as more than 50 years have passed since the year of construction. In the case of such an aging reservoir, the stability due to scour and erosion inside the reservoir is very reduced, and if concentrated rainfall due to recent abnormal weather occurs, the aging reservoir may collapse, leading to a lot of damage to property and human life. Accordingly, each agency that manages aging reservoirs uses Ordinary Portland Cement (OPC) as an injection material and applies the grouting method. However, in the case of OPC, it may deteriorate over time and water leakage may occur again. And there are environmental problems such as consumption of natural resources and generation of greenhouse gases. So, there is a need to develop new materials and methods that can replace the OPC. In this study, an laboratory test and analysis were performed on the grout material developed to induce a curing reaction similar to that of OPC by recycling power plant byproduct. In addition, test in the field such as electric resistivity survey, Standard Penetration Test (SPT), and field permeability test were performed to analyzed to reinforcement effect and determine the possibility of using instead of OPC. As a results of the test, in the case of recycled power plant byproduct, the compressive strength was 2.9 to 3.2 times and the deformation modulus was 2.3 to 3.3 times higher, indicating that it is excellent in strength and can be used instead of OPC. And it was analyzed that the N value of the reservoir was increased by 1~2, and the coefficient of permeability (k) decreased to the level of 8.9~42.5%. showing sufficient reinforcing effect in terms of order.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.1
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• pp.16-22
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• 2021

This experiment was conducted to study on the growth characteristics and seed productivity of Italian ryegrass (Lolium multiflorum Lam., IRG) planted in the Spring in Gangwon Highland according to the seeding distance (20, 30 and 40 cm). The field was located in highland around 600 m above sea level. The experimental design was randomized block design with three replication and the tested IRG variety was 'Greencall' developed by National Institute of Animal Science (NIAS). IRG was sown on March 26, 2020, and harvested on July 2. The plant height was the shortest at 80.5 cm in the 40 cm seeding distance plot (P<0.05), and there was no significant difference between the 20 and 30 cm seeding distance. The number of spike per square meter (㎡) was significantly higher in the 20 cm seeding distance plot than that of 40 cm (937 vs. 571). The dry matter (DM) content of seed and straw after harvesting was 49.70 and 33.36 % on average, and there was no significant difference between treatments (P>005). However, there was a significant difference in the fresh and DM yield of seeds and straw (P<0.05). DM yield of seeds was significantly higher in 20 cm distance than that of 40 cm, and the yield of straw was the same trend. On the other hand, there was no significant difference in DM yield between 20 cm and 30 cm and also in the feed value of straw after seed harvesting among seeding distance. The average CP, ADF, NDF, and TDN contents were 6.91, 36.76, 61.75 and 59.86%, respectively, and the RFV value was 91. Considering the above results, the production of Italian ryegrass seeds sown in the spring in the highlands of the Gangwon is lower than that of autumn sowing, but it is judged that it needs to be reviewed in case it is unavoidable. In the future, there should be an economic analysis and the development of technology that can increase production.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.469-484
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• 2021

Rock mass classification results have a great influence on construction schedule and budget as well as tunnel stability in tunnel design. A total of 3,526 tunnels have been constructed in Korea and the associated techniques in tunnel design and construction have been continuously developed, however, not many studies have been performed on how to assess rock mass quality and grade more accurately. Thus, numerous cases show big differences in the results according to inspectors' experience and judgement. Hence, this study aims to suggest a more reliable rock mass classification (RMR) model using machine learning algorithms, which is surging in availability, through the analyses based on various rock and rock mass information collected from boring investigations. For this, 11 learning parameters (depth, rock type, RQD, electrical resistivity, UCS, V_p, V_s, Young's modulus, unit weight, Poisson's ratio, RMR) from 13 local tunnel cases were selected, 337 learning data sets as well as 60 test data sets were prepared, and 6 machine learning algorithms (DT, SVM, ANN, PCA & ANN, RF, XGBoost) were tested for various hyperparameters for each algorithm. The results show that the mean absolute errors in RMR value from five algorithms except Decision Tree were less than 8 and a Support Vector Machine model is the best model. The applicability of the model, established through this study, was confirmed and this prediction model can be applied for more reliable rock mass classification when additional various data is continuously cumulated.

• Korean journal of applied entomology
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• v.61 no.3
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• pp.399-408
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• 2022

There has been much debate on the morphometric divergence between the recently identified Apis cerana koreana and Apis cerana honey bees. The aim of this study was to obtain phenotypic information that can be used to compare A. c. koreana data with other A. cerana subspecies data from open resources and determine breeding results on the basis of morphometric traits. To differentiate A. c. koreana, we investigated 22 classic morphological characteristics; royal jelly secretion; and the weight of workers, queens, and drones of A. c. koreana bred in Korea. To define the selection results, we used the geometric morphometric method. The artificially selected A. c. koreana secreted significantly more royal jelly (1.18 times) than the naturally selected A. c. koreana, which positively influenced the health of the colonies. These honey bees were identified more clearly with the geometric morphometric method than with the classic morphometric method, which is traditionally used to determine the subspecies. Large trends were noted for A. c. koreana on the basis of our results and literature from the 1980s regarding A. cerana sizes in Korea (tarsal index, length of forewing, and cubital index were measured). The cluster analysis revealed the proximity of A. c. koreana, A. cerana in China, and A. c. indica on the basis of eight classic characters, which, perhaps, relay the origin of the honey bees. The results of this study defined the morphometric responses of A. c. koreana honey bees to geographic isolation, climate change, and selection, which are important to identify, protect, and preserve honey bee stock in Korea.

• Journal of the Korean Geotechnical Society
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• v.25 no.4
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• pp.91-103
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• 2009

Slope failure depends upon the climatic features related to related rainfall, structural geology and geomorphological features as well as the variation of the mechanical behaviors of soil constituting a slope. In this paper, among many variables, effects of soil layer thickness on the slope failure process, and variations of matric suction and volumetric water content were observed. When the soil layer is relatively thick, the descending wetting front decreases matric suction and the observed matric suction reaches to "0" value. When the wetting front reaches to the impermeable boundary, the bottom surface of steel soil box, ascending wetting front was observed. This observation can be postulated to be the effects of various sizes of pores. When macro size pores exist, the capillary effects can be reduced and infilling of pore will be limited. The partially filled pores would be filled with water during the ascending of the wetting front, which bounces from the impermeable boundary. This assumption has been assured from the observation of variation of the volumetric water contents at different depth. When the soil layer is thick (thickness = 20 cm), for granular material, erosion is a cause triggering the slope failure. It has been found that the initiation of erosion occurs when the top soil is fully saturated. Meanwhile, when the soil layer is shallow (thickness = 10 cm), slope slides as en mass. The slope failure for this condition occurs when the wetting front reaches to the interface between the soil layer and steel soil box. As the wetting front approaches to the bottom of soil layer, reduction of shear resistance along the boundary and increase of the unit weight due to the infiltration occur and these produce complex effects on the slope failure processes.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.2
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• pp.54-62
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• 2024

SICM (Scanning Ion Conductivity Microscopy) is a technique for measuring surface topography in an environment where electrochemical reactions occur, by detecting changes in ion conductivity as a nanopipette tip approaches the sample. This study includes an investigation of the current response curve, known as the approach curve, according to the distance between the tip and the sample. First, a simulation analysis was conducted on the approach curves. Based on the simulation results, then, several measuring experiments were conducted concurrently to analyze the difference between the simulated and measured approach curves. The simulation analysis confirms that the current squeezing effect occurs as the distance between the tip and the sample approaches half the inner radius of the tip. However, through the calculations, the decrease in current density due to the simple reduction in ion channels was found to be much smaller compared to the current squeezing effect measured through actual experiments. This suggests that ion conductivity in nano-scale narrow channels does not simply follow the Nernst-Einstein relationship based on the diffusion coefficients, but also takes into account the fluidic hydrodynamic resistance at the interface created by the tip and the sample. It is expected that SICM can be combined with SECM (Scanning Electrochemical Microscopy) to overcome the limitations of SECM through consecutive measurement of the two techniques, thereby to strengthen the analysis of electrochemical surface reactivity. This could potentially provide groundbreaking help in understanding the local catalytic reactions in electroless plating and the behaviors of organic additives in electroplating for various kinds of patterns used in semiconductor damascene processes and packaging processes.