• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.149-150
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• 2019

When concrete is exposed to fire, the decomposition of Portland cement paste results in critical damage to the concrete structure of a building. However the recovery process of the damaged concrete structure has not yet been fully elucidated. In addition, research on appropriate additives such as carbon nanotube (CNT) and nanosilica has been increasing recently, however, investigation of CNT and nanosilica incorporated cement paste after decomposition of CNT by high temperature is not fully investigated. In this study, we investigated the physicochemical properties of CNT incorporated cement paste under different temperatures ($200^{\circ}C$, $500^{\circ}C$ and $800^{\circ}C$). Also, the effects of different rehydration conditions ($20^{\circ}C$ 60% RH and in water for different curing times) on the recovery of the paste were studied. The changes in tensile strength, surface observation of the specimens were characterized. In addition, the decomposition and formation of hydrates in the paste due to the heating process were studied using X-ray diffraction. The results showed that incorporation of nanosilica enhanced tensile strength after heating to each target temperatures.

• 유체기계공업학회:학술대회논문집
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• 1999.12a
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• pp.200-207
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• 1999

An efficient inverse design technique based on the MGM (Modified Garabedian-McFadden) method has been developed. The 2-D Navier-Stokes equations are solved for obtaining the surface pressure distributions and coupled with the MGM method to perform the inverse design. The solver is parallelized by using the domain decomposition method and the standard MPI library for communications between the processors. The MGM method is a residual-correction technique, in which the residuals are the difference between the desired and the computed pressure distribution. The developed code was applied to several airfoil shapes and the axial blade. It has been found that they are well converged to their target pressure distribution.

• Journal of the Korean Society for Railway
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• v.15 no.3
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• pp.286-293
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• 2012

Korean government is enforcing 'Greenhouse gas target management' in order to achieve Greenhouse gas reduction target. To attain Greenhouse gas reduction target, companies in Korea must establish their GHG inventory system and analysis their GHG emissions characteristics for deduction of mitigation measures. LMDI(Log Mean Divisia Index) decomposition analysis is widely used to understand characteristics of GHG emission and energy consumption. In this paper, the characteristics of GHG emission from the line of railroad in Korea is respectively analyzed in terms of conversion effect, intensity effect, production effect and distance effect. Data of railroad GHG emission from 2000 to 2007 are used. As a result, total effect of railroad's GHG emission is $96,813tCO_2eq$. Production effect ($39,865tCO_2eq$) and distance effect ($327,923tCO_2eq$) affect increase of railroad GHG emissions while Conversion effect ($-158,161tCO_2eq$) and intensity effect ($-112,814tCO_2eq$) influence decrease of the emissions.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.389-392
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• 2004

Classification of Earth natural components within a full polarimetric SAR image is one of the most important applications of radar polarimetry in remote sensing. In this paper, the unsupervised classification algorithms based on the combined use of the polarimetric processing technique such as the target decomposition and statistical complex Wishart classification method are evaluated and applied to vegetated terrain in Jeju volcanic island.

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.591-600
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• 2018

Recent SAR systems provide fully polarimetric SAR data, which is known to be useful in a variety of applications such as disaster monitoring, target recognition, and land cover classification. The objective of this study is to evaluate the performance of polarization SAR data for landslide detection. The detectability of different SAR parameters was investigated based on the supervised classification approach. The classifier used in this study is the Adaptive Boosting algorithms. A fully polarimetric L-band PALSAR-2 data was used to examine landslides caused by the 2016 Kumamoto earthquake in Kyushu, Japan. Experimental results show that fully polarimetric features from the target decomposition technique can provide improved detectability of landslide site with significant reduction of false alarms as compared with the single polarimetric observables.

• Korean Journal of Computational Design and Engineering
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• v.12 no.5
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• pp.354-365
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• 2007

We present novel methods to generate a sequence of shapes that represents the pattern of morphological development or transformation of Bezier curves. The presented methods utilize the intrinsic geometric structures of a Bezier curve that are derived from rib and fan decomposition (RFD). Morphological development based on RFD shows a characteristic pattern of structural growth of a Bezier curve, which is the direct consequence of development path defined by fans. Morphological transformation based RFD utilizes development patterns of source and target curves to mimic the theory of evolutionary developmental biology: although the source and target curves are quite different in shapes, we can easily find similarities in their younger shapes, which makes it easier to set up feature correspondences for blending them. We also show that further controls on base transformation for intensity of feature blending, and extrapolation can compensate the immaturity of blended curves. We demonstrate the experimental results where transformation patterns are smoother and have unique geometric style that cannot be generated using conventional methods based on multi-linear blending.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.7
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• pp.1078-1082
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• 2017

This paper presents an L1 optimization based filtering technique which effectively eliminates the optical misalignment effects encountered in the squint guidance mode with strapdown seekers. We formulated a series of L1 optimization problems in order to separate the bias and the gradient components from the measured data, and solved them via the alternating direction method of multipliers (ADMM) and sparse matrix decomposition techniques. The proposed technique was able to rapidly detect arbitrary discontinuities and gradient changes from the measured signals, and was shown to effectively cancel the undesirable effects coming from the seeker misalignment angles. The technique was implemented on embedded flight computers and the real-time operational performance was verified via the hardware-in-the-loop simulation (HILS) tests in parallel with the automatic target recognition algorithms and the intra-red synthetic target images.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2420-2422
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• 2003

In this paper, two Fuzzy Logics for path planning of an autonomous mobile robot are proposed. If a target point is given, such problems regarding the velocity and object recognition are closely related with path to which the mobile robot navigates. Therefore, to ensure safety navigation of the mobile robot for two fuzzy logic parts, path planning considering the surrounding environment was performed in this paper. First, feature points for local and global path are determined by utilizing Cell Decomposition off-line computation. Second, the on-line robot using two Fuzzy Logics navigates around path when it tracks the feature points. We demonstrated optimized path planning only for local path using object recognition fuzzy logic corresponds to domestic situation. Furthermore, when navigating, the robot uses fuzzy logic for velocity and target angle. The proposed algorithms for path planning has been implemented and tested with pioneer-dxe mobile robot.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.4
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• pp.328-335
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• 2017

In this paper, we propose an efficient method to remove noise component contained in high resolution range profile(HRRP) to improve target identification performance. The proposed method can effectively eliminate the noise component using both the statistical characteristics of the noise component and EMD algorithm. Experimental results show that the proposed method can substantially improve the identification capability, removing the noise component effectively.

• Journal of the Korean Society of Propulsion Engineers
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• v.12 no.3
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• pp.1-8
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• 2008

We present a model for simulating high energy laser heating of metal for ignition of energetic materials. The model considers effect of ablation of steel plate with long laser pulses and continuous lasers of several kilowatts and the thermal response of well-characterized high explosives for ignition. Since there is enough time for the thermal wave to propagate into the target and to create a region of hot spot in the high explosives, electron thermal diffusion of ultra-short (femto- and pico-second) lasing is ignored; instead, heat diffusion of absorbed laser energy in the solid target is modeled with thermal decomposition kinetic models of high explosives. Numerically simulated pulsed-laser heating of solid target and thermal explosion of RDX, TATB, and HMX are compared to experimental results. The experimental and numerical results are in good agreement.