• 한국신재생에너지학회:학술대회논문집
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• 2011.11a
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• pp.42.2-42.2
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• 2011

Noise generated from wind turbines has been predicted by numerical methods. Sound pressure level(SPL) on the turbines is predicted after aerodynamic analysis is carried out by Wind Turbine Flow, Aeroacoustics and Structure analysis (WINFAS) code. The level of each panel of acoustic sphere is determined by the sum of tonal, turbulence ingestion and airfoil self noise. With the noise source database, the acoustic sphere, SPL on the ground is calculated using the model based on acoustic ray theory. The model has been designed to consider the effects on the condition of terrain and atmosphere. The variations of SPL on the ground occur not only because of the different source level but also because of the nonuniform distributions of the sound speed along the height. Hence, the profile of an effective sound speed which is the sum of the contribution of sound speed to a temperature gradient and a wind speed variation is used by the theory based on atmospheric stability. With the integrated numerical method, the prediction of sound propagation on the wind farm is carried out with the states of the atmospheric stability.

• Tunnel and Underground Space
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• v.18 no.5
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• pp.355-365
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• 2008

Displacement caused by tunneling is difficult to predict since it is affected by many factors such as ground condition, excavation method and supplementary method of reinforcement. In this study, horizontal inclinometer was employed to monitor ground settlements above a tunnel face before and after the excavation. Monitoring results were analyzed to predict the preceding displacement and settlement of the surface structures. The result of the analysis can be used to establish a proper counter measure which keeps the serviceability of the surface structures. Based on the analysis of the monitoring result, ground properties of the site were deduced and the influence of the tunnel excavation on the settlement of the foundation above the tunnel is analyzed.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.4
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• pp.481-485
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• 2013

Rotor wake causes unsteady aerodynamics of rotor blade. So, accurate prediction of wake is very important and vortex method is good solution for this problem. Aerodynamic force of the rotor blade is calculated by potential panel method and the rotor wake is simulated by vortex particle method. The vortex particle method is easier to treat wake-body interaction and has better performance to expect the effect of ground and fuselage interaction. Rotor in hovering and forward flight condition is simulated through these methods. Thrust and surface pressure of rotor are compared with experiment data.

• Structural Engineering and Mechanics
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• v.6 no.6
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• pp.693-710
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• 1998

This paper concerns studies on the shape formation of post-tensioned and shaped steel domes. The post-tensioned and shaped steel domes, assembled initially at ground level in an essentially flat condition, are shaped to a curved space form and erected into the final position by means of a post-tensioning technique. Based on previous studies on this shape formation principle, three post-tensioned and shaped steel domes have been constructed. The results of the shape formation tests and finite element analyses are reported in this paper. It is found that the first two test domes did not furnish a part-spherical shape as predicted by finite element analyses, because the movements of some mechanisms were not controlled sufficiently. With a revised post-tensioning method, the third dome obtained the theoretical prediction. The test results of the three post-tensioned and shaped domes have shown that a necessary condition to form a desired space shape from a planar layout with low joint stiffnesses is that the movements of all the existing mechanisms must be effectively controlled as indicated by the finite element analysis. The extent of the maximum elastic deformation of a post-tensioned and shaped steel structure is determined by the strength of the top chords and their joints. However, due to the semi-rigid characteristic of the top chord joints, the finite element analyses cannot give a close prediction for the maximum elastic deformations of the post-tensioned and shaped steel domes. The results of the current studies can be helpful for the design and construction of this type of structure.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.1212-1221
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• 2010

A theoretical equation was proposed to consider the effect of fill and ponding for the excess pore water pressure in agricultural reservoir on soft clay ground. For the purpose of verification of the proposed equation, laboratory model tests and field tests were performed and excess pore water pressure was compared to those predicted with the Terzaghi's method. The degree of consolidation according to ponding predicted by applying the proposed equation was close to the observed degree of consolidation on the double drainage condition(at DP-3) but it was less than the observed degree of consolidation on the single drainage condition(at DP-5). The predicted excess pore water pressure according to fill and ponding was very applicable to practice because it was close to the observed data.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.2
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• pp.106-111
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• 2001

The applicability of near infrared reflectance spectroscopy(NIRS) was tested to determine the protein and oil contents in ground soybean [Glycine max (L.) Merr.] seeds. A total of 189 soybean calibration samples and 103 validation samples were used for NIRS equation development and validation, respectively. In the NIRS equation of protein, the most accurate equation was obtained at 2, 8, 6, 1(2nd derivative, 8 nm gap, 6 points smoothing and 1 point second smoothing) math treatment condition with SNV-D (Standard Normal Variate and Detrend) scatter correction method and entire spectrum by using MPLS (Modified Partial Least Squares) regression. In the case of oil, the best equation was obtained at 1, 4, 4, 1 condition with SNV-D scatter correction method and near infrared (1100-2500nm) region by using MPLS regression. Validation of these NIRS equations showed very low bias (protein:-0.016%, oil : -0.011 %) and standard error of prediction (SEP, protein: 0.437%, oil: 0.377%) and very high coefficient of determination ($R^2$, protein: 0.985, oil : 0.965). Therefore, these NIRS equation seems reliable for determining the protein and oil content, and NIRS method could be used as a mass screening method of soybean seed.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1666-1672
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• 2008

In this study, it collected and analyzed a construction case of the improved top-down support system application field on a case by case retaining wall method. The behavior of horizontal displacement was analyzed according to retaining wall type after reviewing a design stage and estimated horizontal displacement under the construction. The study results showed that it is judged stable until excavation termination irrelevant to a retaining wall method at the improved top-down support system application. It is judged that the settlement of behind ground can minimize because the retaining wall head displacement also behave stably. It was compared the predicted horizontal displacement in design and the measured horizontal displacement acquired through a measurement by using Elasto-Plastic analysis program. The comparison results showed that a similar horizontal displacement was predicted within stability standard irrelevant to a retaining wall method. So, it is decided that the advanced prediction is reasonable by Elasto-Plastic analysis in design applied the improved top-down support system. In the case of the ground anchor method application under a same condition, it is decided that a horizontal displacement will more increase than the improved top-down support system is applied. If a section condition is same, it was decided that to apply top-down support system is more stable than that.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.55 no.4
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• pp.357-364
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• 2010

Kjeldahl method used in many materials from various plant parts to determine protein contents, is laborious and time-consuming and utilizes hazardous chemicals. Near-infrared (NIR) reflectance spectroscopy, a rapid and environmentally benign technique, was investigated as a potential method for the prediction of protein content. Near-infrared reflectance spectra(1100-2400 nm) of coarse cereal grains(n=100 for each germplasm) were obtained using a dispersive spectrometer as both of grain itself and flour ground, and total protein contents determined according to Kjeldahl method. Using multivariate analysis, a modified partial least-squares model was developed for prediction of protein contents. The model had a multiple coefficient of determination of 0.99, 0.99, 0.99, 0.96 and 0.99 for foxtail millet, sorghum, millet, adzuki bean and mung bean germplasm, respectively. The model was tested with independent validation samples (n=10 for each germplasm). All samples were predicted with the coefficient of determination of 0.99, 0.99, 0.99, 0.91 and 0.99 for foxtail millet, sorghum, millet, adzuki bean and mung bean germplasm, respectively. The results indicate that NIR reflectance spectroscopy is an accurate and efficient tool for determining protein content of diverse coarse cereal germplasm for nutrition labeling of nutritional value. On the other hands appropriate condition of cereal material to predict protein using NIR was flour condition of grains.

• Journal of Korean Tunnelling and Underground Space Association
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• v.6 no.4
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• pp.327-343
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• 2004

During tunnel construction, ground failures often occur due to existence of weak zones, such as faults, joints, and cavities, ahead of tunnel face. It is hard to detect effectively weak zones, which can lead underground structure to fail after excavation and before supporting, by using conventional characterization methods. In this study, an enhanced analytical method of predicting weak zones ahead of tunnel face is developed to overcome some problems in the conventional geophysical exploration methods. The analytical method is based on Coulomb's and Gauss' laws with considering the characteristics of electric fields subjected to rock mass. Using the developed method, closed form solutions are obtained to detect a spherical shaped zone and an oriented fault ahead of tunnel face respectively. The analytical results suggest that the presence of weak zones and their sizes, location, and states can be accurately predicted by combining a proper inversion process with resistance measured from several electrodes on the tunnel face. It appears that the skin depth or resistivity in rock mass is affected by the diameter of tunnel face, natural electric potential and noises induced by experimental measurement and spatial distribution of uncertain properties. The developed analytical solution is verified through experimental tests. About 1800 concrete blocks of 5cm by 5cm by 5cm in size are prepared and used to model a joint rock mass around tunnel face. Weak zones are simulated ahead of tunnel face with a material which has relatively higher conductivity than concrete blocks. Experimental results on the model test show a good agreement with analytical results.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.5
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• pp.641-656
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• 2019

In this study, a machine learning method was proposed to use in predicting optimal replacement period of shield TBM (Tunnel Boring Machine) disc cutter. To do this, a large dataset of ground condition, disc cutter replacement records and TBM excavation-related data, collected from a shield TBM tunnel site in Korea, was built and they were used to construct a disc cutter replacement period prediction model using a machine learning algorithm, SVM (Support Vector Machine) and to assess the performance of the model. The results showed that the performance of RBF (Radial Basis Function) SVM is the best among a total of three SVM classification functions (80% accuracy and 10% error rate on average). When compared between ground types, the more disc cutter replacement data existed, the better prediction results were obtained. From this results, it is expected that machine learning methods become very popularly used in practice in near future as more data is accumulated and the machine learning models continue to be fine-tuned.