• Journal of the Korean Society for Precision Engineering
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• v.18 no.3
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• pp.195-204
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• 2001

Virtual computer numerical control(VCNC) arises from the concept that one can experience pseudo-real machining with a computer-numerically-controlled(CNC) machine before actually cutting an object. To achieve accurate VCNC, it is important to determine abnormal behavior, such as chatter, before cutting. Detecting chatter requires an understanding of the dynamic cutting force model. In general, the cutting process is a closed loop system that consists of structural and cutting dynamics. Machining instability, namely chatter, results from the interaction between these two dynamics. Several previous reports have predicted stability for a single path, using a simple cutting force model without tool runout and penetration effects. This study considers both tool runout and penetration effects, using experimental modal analysis, to obtain more accurate predictions. The machining stability in the corner cut, which is a typical transient cut, was assessed from an evaluation of the cutting configurations at the corner.

• Computers and Concrete
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• v.20 no.1
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• pp.1-10
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• 2017

This paper focuses on the mesh-size dependency in numerical simulations of reinforced concrete (RC) structures subjected to blast loading. A tensile failure criterion that can minimize the mesh-dependency of simulation results is introduced based on the fracture energy theory. In addition, conventional plasticity based damage models for concrete such as the CSC model and the HJC model, which are widely used for blast analyses of concrete structures, are compared with the orthotropic model that adopts the introduced tensile failure criterion in blast tests to verify the proposed criterion. The numerical predictions of the time-displacement relations at the mid-span of RC beams subjected to blast loading are compared with experimental results. The analytical results show that the numerical error according to the change in the finite element mesh size is substantially reduced and the accuracy of the numerical results is improved by applying a unique failure strain value determined by the proposed criterion.

• Progress in Superconductivity
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• v.12 no.1
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• pp.36-40
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• 2010

We have studied the anisotropy of the London penetration depth of carbon doped $MgB_2$ single crystals, which was obtained from reversible magnetization measurements with the magnetic field both parallel and perpendicular to the c-axis. Similar to the pure $MgB_2$, the anisotropy of the upper critical field ${\gamma}_H$ decrease with temperature while the anisotropy of the London penetration depth ${\gamma}_{\lambda}$ slowly increases with temperature. However, the temperature dependence of ${\gamma}_H$ is drastically reduced and the value of ${\gamma}_{\lambda}$ becomes nearly ~1 as C is introduced. These results indicate that C substitution increases impurity scattering mainly in the $\sigma$ bands. The temperature dependence of the anisotropies agree well with the theoretical predictions with impurity scattering.

• 한국전산유체공학회:학술대회논문집
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• 2003.10a
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• pp.172-174
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• 2003

Nnumerical investigations of the tip vortical characteristics were conducted with lateral tip blowing to reduce Blade-Vortex Interaction (BVI) noise. The predictions of BVI noise were performed using a combined method of an unsteady Euler code with an aeroacoustic code based on Ffowcs- Williams and Hawkings formulation. A moving overlapped grid system with three types of grids (blade grid, inner and outer background grid) was used to simulate BVI of helicopter with two OLS-airfoil blades in forward/ descending flight condition. The calculated waveform of BVI noise, which is characterized by the distinct peaks caused during blade vortex interaction, clearly shows the effect of lateral blowing at tip to reduce BVI noise

• Journal of Korean Vacuum Science & Technology
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• v.4 no.4
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• pp.112-121
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• 2000

The paper investigates electrical discharge properties in neon gas mixed with xenon. The breakdown temperature T$\sub$b/ and voltage V$\sub$b/ are obtained in terms of the gas mixture ratio X. It is shown that the breakdown voltage decreases, reaches the minimum value at X=0.02 and then increases again, as the mixture ratio X increases from zero to unity. Therefore, mixing the neon gas with a few percent of xenon is the most beneficial to reduce the breakdown voltage. Plasma density at breakdown in neon gas mixed with xenon is described in terms of the gas mixture ratio. The optimum value of mixture ratio for highest plasma density is found to be Xm=0.03. A preliminary experiment of AC-PDP is carried out for neon gas mixed with a few percent of xenon to verify some of the theoretical models. The experimental data agree qualitatively well with theoretical predictions.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1327-1335
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• 2002

The shock wave process represents an abrupt change in fluid properties, in which finite variations in pressure, temperature, and density occur over the shock thickness which is comparable to the mean free path of the gas molecules involved. This shock wave fluid phenomenon is simulated by using the finite difference lattice Boltzmann method (FDLBM). In this paper, a new model is proposed using the lattice BGK compressible fluid model in FDLBM for the purpose of speeding up the calculation as well as stabilizing the numerical scheme. The numerical results of the proposed model show good agreement with the theoretical predictions.

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.127-137
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• 2018

Parturition is an important event for farmers as it provides economic gains for the farms. Thus, the effective management of parturition is essential to farm management. In particular, the unit price of cattle is higher than other livestock and the productivity of cattle is closely associated to farm income. In addition, 42% of calving occurs in the nighttime so accurate parturition predictions are all the more important. In this paper, we propose a method that accurately predicts the calving date by applying core body temperature of cattle to deep learning. The body temperature of cattle can be measured without being influenced by the ambient environment by applying an ingestible bio-sensor in the cattle's rumen. By experiment on cattle, we confirmed this method to be more accurate for predicting calving dates than existing parturition prediction methods, showing an average of 3 hour 40 minute error. This proposed method is expected to reduce the economic damages of farms by accurately predicting calving times and assisting in successful parturitions.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.1
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• pp.73.1-73.1
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• 2012

We present the results of dust scattering simulations carried out for the Orion Eridanus Superbubble region by comparing them with observations made in the far-ultraviolet. The albedo and the phase function asymmetry factor (g-factor) of interstellar grains were estimated as well as the distance and thickness of the dust layers. The results are: 0.39-0.45 for the albedo and 0.25-0.65 for the g-factor, in good agreement with previous determinations and theoretical predictions. The distance of the assumed single dust layer, modeled for the Orion Molecular Cloud Complex, was estimated to be -110 pc and the thickness ranged from -130 at the core to -50 pc at the boundary for the region of the present interest, implying that the dust cloud is located in front of the Superbubble. The simulation result also indicates that a thin (-10 pc) dust shell surrounds the inner X-ray cavities of hot gas at a distance of -70-90 pc.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.98.1-98.1
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• 2012

We present the results of dust scattering simulations carried out for the Orion-Eridanus Superbubble region by comparing them with observations made in the far-ultraviolet. The albedo and the phase function asymmetry factor (g-factor) of interstellar grains were estimated, as were the distance and thickness of the dust layers. The results are as follows: [0.43]_(-0.04)^(+0.02) for the albedo and [0.43]_(-0.2)^(+0.2) for the g-factor, in good agreement with previous determinations and theoretical predictions. The distance of the assumed single dust layer, modeled for the Orion Molecular Cloud Complex, was estimated to be ~110 pc, and the thickness ranged from ~130 at the core to ~50 pc at the boundary for the region of present interest, implying that the dust cloud is located in front of the superbubble. The simulation result also indicates that a thin (~10 pc) dust shell surrounds the inner X-ray cavities of hot gas at a distance of ~70-90 pc.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.2
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• pp.101-115
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• 2024

The ocean heatwave is emerging as a major issue due to global warming, posing a direct threat to marine ecosystems and humanity through decreased food resources and reduced carbon absorption capacity of the oceans. Consequently, the prediction of ocean heatwaves in the vicinity of the Korean Peninsula is becoming increasingly important for marine environmental monitoring and management. In this study, an LSTM model was developed to improve the underestimated prediction of ocean heatwaves caused by the coarse vertical grid system of the Korean Peninsula Ocean Prediction System. Based on the results of ocean heatwave predictions for the Korean Peninsula conducted in 2023, as well as those generated by the LSTM model, the performance of heatwave predictions in the East Sea, Yellow Sea, and South Sea areas surrounding the Korean Peninsula was evaluated. The LSTM model developed in this study significantly improved the prediction performance of sea surface temperatures during periods of temperature increase in all three regions. However, its effectiveness in improving prediction performance during periods of temperature decrease or before temperature rise initiation was limited. This demonstrates the potential of the LSTM model to address the underestimated prediction of ocean heatwaves caused by the coarse vertical grid system during periods of enhanced stratification. It is anticipated that the utility of data-driven artificial intelligence models will expand in the future to improve the prediction performance of dynamical models or even replace them.