• Journal of the Korean Society of Safety
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• v.21 no.5 s.77
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• pp.6-11
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• 2006

This study aims to measure a smoke density and velocity by using the PIV method in case a fire occurs in tunnels. By doing so, this will estimate a critical velocity, examine its appropriateness, and present the basic materials necessary for designing a smoke control equipment. For this study, a visualization test was conducted based on the 1/20 miniature of a real tunnel according to the Froude scaling. As a part of basic experiments, a correlation between smoke density and brightness was analyzed here, and a critical velocity was estimated on the condition that a fire breaks out in tunnels. As a result, this study finds that there is a correlation between smoke density and brightness within a range of 100% to 30% transmittance, from which a quantitative smoke density can be obtained. The study also suggests that a critical velocity calculated from the Kennedy formula shows about 10% difference from that estimated in the test.

• Progress in Superconductivity
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• v.1 no.2
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• pp.146-150
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• 2000

Step edge Josephson junctions in c-axis oriented $YBa_2Cu_3O_7$ films were fabricated on $CeO_2$ buffered sapphire substrates. The step angle was controlled in the wide range of $20^{\circ}\sim75^{\circ}$ by the Ar ion milling technique. I-V curves of junction fabricated on the thickness ratio of $\sim$0.8 and the step angle of $35^{\circ}$ were exhibited RSJ-like behavior with $I_CR_N$ product of $\sim250{\mu}A$ and critical current density of $\sim2\times10^4A/cm^2$ at 77 K. Critical current of step edge junction was increased linearly with decreasing temperature but the normal resistance was almost constant. Total samples of step edge Josephson junction was satisfied a scaling behavior of $I_CR_N{\propto}(J_C)^{0.5}$.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1276-1279
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• 2006

This article on environmental noise qualify is concerned with the relationships between the annoyance and perception and sound quality metrics according to exposition time for traffic noise. For invested the characteristics of noise quality, we conducted to the subjective experiments of the annoyance response using the absolute 100 scaling method for the traffic noise sources. The traffic noise sources are composed to varieties exposition time from 15sec to 1200sec. As the results, the first there are decreased the perception loud level for the increase of exposition time with logarithm scale, but increased the annoyance. Second, evaluation index of annoyance is correlated to the loudness(sones), tonality and logarithm scale time with R2=0.83. Also, the composition ratio of traffic noise according to exposition time has the change of range as the logarithm scale ($30{\sim}50%$), tonality($27{\sim}37%$) and loudness($34{\sim}20%$).

• Journal of Industrial Technology
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• v.25 no.A
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• pp.39-47
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• 2005

Air void systems in hardened concrete has an important influence on concrete durability such as freeze-thaw resistance, water permeability, surface scaling resistance. Linear traverse method and point count method described at ASTM are the routine analysis of the air void system that have been widely used to estimate the spacing factor in hardened concrete. Recently, many concretes often have a spacing factor higher than the generally accepted $200-250{\mu}m$ limit for the usual range of air contents. This study is proposed to estimate the plane spacing factor by calculation of simplicity. The plane spacing factor need two parameters that are air content and numbers of air voids in the hardened concrete. Those obtained from the standard air-void system analysis of the ASTM C 457. The equation is valid for all values of paste-to-air ratio because the estimation of paste content is unnecessary at the using ASTM C 457. The plane spacing factor yields a similar estimate of the standard spacing factor.

• 유체기계공업학회:학술대회논문집
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• 1999.12a
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• pp.81-89
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• 1999

The major source of noise in the process of transporting liquids is related to the cavitation phenomenon. The control valve noise is mostly dominated by bubble dynamics under cavitating conditions. In this investigation, an orifice configuration is set-up to correlate its flow-field and acoustic signatures with those from a control valve device. The performance and noise characteristics form the orifice configuration in anechoic surroundings were measured to reveal the noise sources depending on pressure differences across the orifice configuration. The sound powers from the orifice configuration are effectively normalized using proposed scaling parameters. Flow-excited dynamic systems for which there is no strong coupling between the flow and the system response can be described using a linear source-filter model. On this assumption, the normalized sound powers can be decomposed of noise source function and a response function. To find noise sources, pressure spectra measured over a range of pressure differences are transformed into the product of two non-dimensional frequency function : $P_{ss}(He,f_{ca},x/D) = F(f_{ca})\;G(He,x/D)$. This scheme of finding noise sources is shown to be applicable to the cavitation noise from the control valve effectively Two kinds of cavitating modes based on our experimental data are found and discussed.

• Journal of Electrical Engineering and Technology
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• v.2 no.2
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• pp.178-187
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• 2007

One important issue in power systems is dynamic instability due to loosing balance relation between electrical generation and a varying load demand that justifies the necessity of stabilization. Moreover, Power System Stabilizer (PSS) must have capability of producing appropriate stabilizing signals over a wide range of operating conditions and disturbances. To overcome these drawbacks, this paper proposes a new method for robust design of PSS by using an auto-tuning fuzzy control in combination with Real-Coded Genetic Algorithm (RCGA). This method includes two fuzzy controllers; internal fuzzy controller and supervisor fuzzy controller. The supervisor controller tunes the internal one by on-line applying of nonlinear scaling factors to inputs and outputs. The RCGA-based method is used for off-line training of this supervisor controller. The proposed PSS is tested in three operational conditions; nominal load, heavy load, and in the case of fault occurrence in transmission line. The simulation results are provided to compare the proposed PSS with conventional fuzzy PSS and conventional PSS. By evaluating the simulation results, it is shown that the performance and robustness of proposed PSS in different operating conditions is more acceptable

• Proceedings of the KIEE Conference
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• summer
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• pp.292-294
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• 2004

In this paper, we design the GA-fuzzy precompensator of a Power System Stabilizer for Thyristor Controlled Series Capacitor(TCSC-PSS) for enhancement of power system stability. Here a fuzzy precompensator is designed as a fuzzy logic-based precompensation approach for TCSC-PSS. This scheme is easily implemented simply by adding a fuzzy precompensator to an existing TCSC-PSS. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership Auction and control rules. Simulation results show that the proposed control technique is superior to a conventional PSS in dynamic responses over the wide range of operating conditions and is convinced robustness and reliableness in view of structure.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.3892-3901
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• 2021

The pressure drop of a moisture separator in a steam generator is the important design parameter to ensure the successful performance of a nuclear power plant. The moisture separators have a wide range of operating conditions based on the arrangement of them. The prediction of the pressure drop in a moisture separator is challenging due to the complexity of the multi-dimensional two-phase vortex flow. In this study, the moisture separator test facility using the air/water two-phase flow was used to predict the pressure drop of a moisture separator in a Korean OPR-1000 reactor. The prototypical steam/water two-phase flow conditions in a steam generator were simulated as air/water two-phase flow conditions by preserving the centrifugal force and vapor quality. A series of experiments were carried out to investigate the effect of hydraulic characteristics such as the quality and liquid mass flux on the two-phase pressure drop. A new prediction model based on the scaling law was suggested and validated experimentally using the full and half scale of separators. The suggested prediction model showed good agreement with the steam/water experimental results, and it can be extended to predict the steam/water two-phase pressure drop for moisture separators.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3182-3198
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• 2019

Vision-based Human Pose Estimation has been considered as one of challenging research subjects due to problems including confounding background clutter, diversity of human appearances and illumination changes in scenes. To tackle these problems, we propose to use a new multi-stage convolution machine for estimating human pose. To provide better heatmap prediction of body joints, the proposed machine repeatedly produces multiple predictions according to stages with receptive field large enough for learning the long-range spatial relationship. And stages are composed of various modules according to their strategic purposes. Pyramid stacking module and dilation module are used to handle problem of human pose at multiple scales. Their multi-scale information from different receptive fields are fused with concatenation, which can catch more contextual information from different features. And spatial and channel information of a given input are converted to gating factors by squeezing the feature maps to a single numeric value based on its importance in order to give each of the network channels different weights. Compared with other ConvNet-based architectures, we demonstrated that our proposed architecture achieved higher accuracy on experiments using standard benchmarks of LSP and MPII pose datasets.

• Journal of Biomedical Engineering Research
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• v.40 no.2
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• pp.48-54
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• 2019

This paper proposed a method of validation data augmentation for improving the grading accuracy of diabetic macular edema (DME) using deep learning. The data augmentation technique is basically applied in order to secure diversity of data by transforming one image to several images through random translation, rotation, scaling and reflection in preparation of input data of the deep neural network (DNN). In this paper, we apply this technique in the validation process of the trained DNN, and improve the grading accuracy by combining the classification results of the augmented images. To verify the effectiveness, 1,200 retinal images of Messidor dataset was divided into training and validation data at the ratio 7:3. By applying random augmentation to 359 validation data, $1.61{\pm}0.55%$ accuracy improvement was achieved in the case of six times augmentation (N=6). This simple method has shown that the accuracy can be improved in the N range from 2 to 6 with the correlation coefficient of 0.5667. Therefore, it is expected to help improve the diagnostic accuracy of DME with the grading information provided by the proposed DNN.