• Journal of the Korean Society of Combustion
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• v.20 no.1
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• pp.24-31
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• 2015

Flame structure, which contains a useful information for studying combustion instability of the flame, is often quantitatively visualized with PLIF (planar laser-induced fluorescence) and/or chemiluminescence images. The latter, a line-integral of a flame property, needs to be preprocessed before being inverted, mainly due to its inherent noise and the axisymmetry assumption of the inversion. A preprocessing scheme utilizing multi-division of ROI (region of interest) of the chemiluminescence image is proposed. Its feasibility has been tested with OH PLIF and $OH^*$ chemiluminescence images of SNG (synthetic natural gas) swirl-stabilized flames taken from a model gas turbine combustor. It turns out that the multi-division technique outperforms two conventional ones: those are, one without preprocessing and the other with uni-division preprocessing, reconstructing the SNG flame structure much better than its two counterparts, when compared with the corresponding OH PLIF images. It is also found that the Canny edge detection algorithm used for detecting edges in the multi-division method works better than the Sobel algorithm does.

• Korean Journal of Mathematics
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• v.21 no.2
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• pp.125-150
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• 2013

The stabilized Gauge-Uzawa method (SGUM), which is a second order projection type algorithm to solve the time-dependent Navier-Stokes equations, has been newly constructed in 2013 Pyo's paper. The accuracy of SGUM has been proved only for time discrete scheme in the same paper, but it is crucial to study for fully discrete scheme, because the numerical errors depend on discretizations for both space and time, and because discrete spaces between velocity and pressure can not be chosen arbitrary. In this paper, we find out properties of the fully discrete SGUM and estimate its errors and stability to solve the evolution Navier-Stokes equations. The main difficulty in this estimation arises from losing some cancellation laws due to failing divergence free condition of the discrete velocity function. This result will be extended to Boussinesq equations in the continuous research (part II) and is essential in the study of part II.

• Geomechanics and Engineering
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• v.36 no.4
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• pp.329-341
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• 2024

Retaining structures are one of the most important elements in the stabilization of excavations and slopes in various engineering projects. Mechanically stabilized earth (MSE) walls are widely used as retaining structures due to their flexibility, easy and economical construction. These benefits are especially prominent for projects built on soft and weak foundation soils, which have relatively low resistance and high compressibility. For high retaining walls on weak foundations, conventional design methods are not cost-effective. Therefore, two alternative solutions for different foundation weakness are proposed in this research: optimized multi-tiered MSE walls and single tier wall with foundation improvement. The cost optimization considers both the construction components and the land price. The results show that the optimal solution depends on several factors, including the foundation strength and more importantly, the land price. For low land price, the optimized multi-tiered wall is more economical, while for high land price (urban areas), the foundation improvement is preferable. As the foundation strength decreases, the foundation improvement becomes inevitable.

• The Journal of the Acoustical Society of Korea
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• v.24 no.4E
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• pp.123-127
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• 2005

In this paper, we propose a new method for reducing the number of distance calculations in the LBG (Linde, Buzo, Gray) algorithm, which is widely used method to construct a codebook in vector quantization of speech recognition system. The proposed algorithm can reduce the distance calculation between input vector and codeword by utilizing the observation that codewords are quickly stabilized as the number of iteration increases. From the simulation results, it is shown that we can reduce the running times over $43.77\%$ on average in comparison with current LBG algorithm without sacrificing the performance of codebook.

• Structural Engineering and Mechanics
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• v.38 no.4
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• pp.405-416
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• 2011

An efficient two-level domain decomposition parallel algorithm is suggested to solve large-DOF structural problems with nonlinear material models generating unsymmetric tangent matrices, such as a group of plastic-damage material models. The parallel version of the stabilized bi-conjugate gradient method is developed to solve unsymmetric coarse problems iteratively. In the present approach the coarse DOF system is solved parallelly on each processor rather than the whole system equation to minimize the data communication between processors, which is appropriate to maintain the computing performance on a non-supercomputer level cluster system. The performance test results show that the suggested algorithm provides scalability on computing performance and an efficient approach to solve large-DOF nonlinear structural problems on a cluster system.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.342-342
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• 2000

We present 3-axis stabilized spacecraft attitude determination algorithm using the magnetometer. The magnetometer has been used as a reliable, light-weight and inexpensive sensor in attitude determination and reaction wheel momentum dumping system. Recent studies have attempted to use the magnetometer when other attitude sensor, such as star tracker, fails. The differences between the measured and computed the Earth's magnetic field components are spacecraft attitude errors. In this paper, we propose extended Kalman filter(EKF) to determine spacecraft attitude with the magnetometer data and gyro-measured body rates. We develop and simulate this algorithm using MATLAB/SIMULINK. This algorithm can be used as a backup attitude determination system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.779-783
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• 2006

A The estimation of electrical power consumption is becoming more important to supply stabilized electrical power recently. In this paper, we propose a supplied forecasting system of electrical power using Fuzzy Compensative Algorithm to estimate electrical load accurately than the previous. We evaluate a time series of supplied electrical power have the chaotic character using quantitative and qualitative analysis, compose a forecasting system by the maximum change $rate(\alpha)$ of Fuzzy Algorithm and compensative parameter. Simulating it for obtained time series, we can obtain more accurate results than the previous proposed system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.922-925
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• 2005

This article describes a FM modulation algorithm to increase the measurement speed by increasing the beat frequency of the laser without acousto-optic modulator(AOM) in the heterodyne laser interferometer. The proposed algorithm can increase the beat frequency of the heterodyne laser which limit the measurement speed by adjusting a carrier frequency through electronic circuit, while AOM is used to shift the frequency of the heterodyne laser in conventional method. Electronic circuit is constructed to modulate the signals from a laser interferometer and a waveform generator. The brier analysis, the measurement scheme of the system, and the experimental results using a Zeeman-stabilized He-Ne laser are presented. They demonstrate that the proposed algorithm is proven to enhance the measurement speed limit by increasing the beat frequency of the heterodyne laser.

• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3283-3292
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• 2022

Based on the Deep Q-Network(DQN) algorithm of reinforcement learning, an active fault-tolerance method with incremental action is proposed for the control system with sensor faults of the once-through steam generator(OTSG). In this paper, we first establish the OTSG model as the interaction environment for the agent of reinforcement learning. The reinforcement learning agent chooses an action according to the system state obtained by the pressure sensor, the incremental action can gradually approach the optimal strategy for the current fault, and then the agent updates the network by different rewards obtained in the interaction process. In this way, we can transform the active fault tolerant control process of the OTSG to the reinforcement learning agent's decision-making process. The comparison experiments compared with the traditional reinforcement learning algorithm(RL) with fixed strategies show that the active fault-tolerant controller designed in this paper can accurately and rapidly control under sensor faults so that the pressure of the OTSG can be stabilized near the set-point value, and the OTSG can run normally and stably.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.570-575
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• 2019

Active muffler is implemented by applying active noise control technique to reduce exhaust noise of automobile muffler. Conventional Filtered_x LMS algorithm has a problem that the degree of control filter becomes very large and convergence deteriorates when acoustic feedback is present. The recursive LMS algorithm can compensate for this problem because it can be easily diverted in the adaptive filter adaptation process. In this paper, the structure of the primary path and the secondary path transfer function is designed as the IIR filter to improve the convergence performance and the computational burden, and the stabilization filter algorithm is applied to secure stability which is a disadvantage of the IIR filter structure. The stabilization filter algorithm plays a role of pulling the pole into the unit circle to prevent the pole of the transfer function corresponding to the acoustic feedback from diverging during the adaptation process. In this way, the computational burden of the active muffler system and the convergence performance can be improved. In order to show the usefulness of the proposed system, we compared the performance of the proposed Filtered_x LMS algorithm with the performance of the proposed system for the exhaust sound of a diesel engine, which is a variable environment. Compared to conventional algorithm, proposed algorithm's computational burden is less than half, and convergence performances are more than 4 times.