• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.05a
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• pp.112-113
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• 2019

Recently, supplementary cementitious materials such as blast-furnace slag, fly ash and silica fume have been widely used as substitutes for cementitious materials. In this study, the deformation behavior of compressive loading of C₃S paste with 50% fly ash was analyzed by X-ray scattering data and pair distribution function analysis. The obtained results were compared with 131-day-old pure C₃S paste. The Ca(OH)₂ of the C₃S-FA paste showed almost complete elastic behavior, consistent with the deformation behavior of the r-range of 20 to 40, and the C-S-H phase contributed to the range of PDF r-range of less than 20. In addition, C-S-H of C₃S-FA showed greater deformation resistance than C₃S paste.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.170-171
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• 2019

When the cement paste in concrete is exposed to high temperatures, the mechanical performance decreases due to a series of reactions inside the cement. In this study, we investigated the change of nanostructure of $C_3S$ when $C_3S$ was exposed to high temperature using pair distribution function (PDF) based on high energy X-ray scattering. As a result of X-ray diffraction, there was no significant difference when $C_3S$ was heated at $300^{\circ}C$, but most of $Ca(OH)_2$ was decomposed into CaO at $500^{\circ}C$. In addition, it was confirmed that CaO is dominant in the nanostructure when $C_3S$ is heated to $500^{\circ}C$.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.10a
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• pp.94-95
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• 2016

Calcium Silicate Hydrate (C-S-H), which takes up most of the hydration products of Portland Cement (PC), has the greatest impact on the mechanical behavior and strength development of concrete. The exact mechanism of its deformation, however, has not yet been elucidated. The present study aims to demonstrate the mechanism of nano-deformation behavior of C-S-H in tricalcium silicate paste under compressive loading, unloading and reloading by interpreting atomic pair distribution function (PDF) based on synchrotron X-ray scattering. The strain of the tricalcium silicate paste for a short-range of 0 ~ 20 Å under compressive load exhibited two stages, I) nano-packing of interlayer of C-S-H and II) micro-packing of C-S-H globules, whereas the deformation for a long-range order of 20 ~ 40 Å was similar to that of a calcium hydroxide phase measured by Bragg peak shift. Moreover, the residual strains due to the plastic deformation of C-S-H was clearly observed.

• Journal of the Korean Applied Science and Technology
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• v.27 no.4
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• pp.452-460
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• 2010

Any theory of liquid should account for interactions between molecules, since molecules in a liquid are close to each other. For this matter statistical-mechanical methodology has been used and various models have been proposed on the basis of this methodology. Among them Kirkwood-Buff solution theory has attracted a lot of interest, because it is regarded as being the most powerful. In this article Kirkwood-Buff solution theory is revisited and its key equations are derived. On the way to these equations, the concepts of pair correlation function, radial distribution function, Kirkwood-Buff integration are explained and implemented. Since complexity of statical mechanics involved in this theory, the equations are applied to one-component systems and the results are compared to those obtained by classical thermodynamics. This may be a simple way for Kirkwood-Buff solution theory to be examined for its validity.

• Smart Structures and Systems
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• v.26 no.6
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• pp.721-733
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• 2020

The present study investigates the employing of piezoelectric patches in active control of a sandwich plate. Indeed, the active control and optimal patch distribution on this structure are presented together. A sandwich plate with honeycomb core and composite reinforced by carbon nanotubes in facesheet layers is considered so that the optimum position of actuator/sensor patches pair is guaranteed to suppress the vibration of sandwich structures. The sandwich panel consists of a search space which is a square of 200 × 200 mm with a numerous number of candidates for the optimum position. Also, different dimension of square and rectangular plates to obtain the optimal placement of piezoelectric actuator/senor patches pair is considered. Based on genetic algorithm and LQR, the optimum position of patches and fitness function is determined, respectively. The present study reveals that the efficiency and performance of LQR control is affected by the optimal placement of the actuator/sensor patches pair to a large extent. It is also shown that an intelligent selection of the parent, repeated genes filtering, and 80% crossover and 20% mutation would increase the convergence of the algorithm. It is noted that a fitness function is achieved by collection actuator/sensor patches pair cost functions in the same position (controllability). It is worth mentioning that the study of the optimal location of actuator/sensor patches pair is carried out for different boundary conditions of a sandwich plate such as simply supported and clamped boundary conditions.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.5
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• pp.60-65
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• 2019

Since nanofluids (NFs), which are a mixture of a small amount of nanoparticles and a bulk liquid solvent, were first proposed by Stephen Choi at the Argonne National Lab in 1995, they have been considered for use in many technical studies of power cooling systems and their practical application due to their high thermal conductivity and heat transfer coefficients compared to conventional coolants. Although nanofluids are a well-known form of engineering fluid that show great promise for use in future cooling systems, their underlying physics as demonstrated in experiments remain unclear. One proven method of determining the heat transfer performance of nanofluids is measuring the concentration of nanoparticles in a mixture. However, it is experimentally inefficient to build testbeds to systematically observe particle distributions on a nanoscale. In this paper, we demonstrate the distribution of nanoparticles under a temperature gradient in a solution using molecular dynamics simulations. First, temperature profiles based on substrate temperature are introduced. Following this, the radial pair distribution functions of pairs of nanoparticles, solvents, and substrates are calculated. Finally, the distribution of nanoparticles in different heating regions is determined.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.4
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• pp.71-82
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• 2001

Using the computer simulation method, we invest19ate the probability distribution of maximum eigenvalue of pair-wise comparison matrix, which has been used as a parameter for measuring the consistency of responses in analytic hierarchy process (AHP). We show that the shape of the distribution of the maximum eigenvalue is different according to the dimension of the matrix. In addition, we cannot find any evidence that the distribution of the Consistency Index is a Normal distribution, which has been claimed in the Previous literature. Accordingly, we suggest using so called K-index calcu1ated based on the concept of cumulative distribution function lather than based on that of arithmetic mean because the probabilistic distribution cannot be assumed to be a Normal distribution. We interpret the simulation results by comparing them with the suggestion of Saaty[11]. Our results show that using Saaty＇s value could be too generous when the dimension of the matrix is 3 and strict over 4. Finally, we propose new criteria for measuring the response consistency in AHP.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.3
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• pp.522-538
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• 2013

Content based image retrieval has become an increasingly important research topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The retrieval systems rely on a key component, the predefined or learned similarity measures over images. We note that, the similarity measures can be potential improved if the data distribution information is exploited using a more sophisticated way. In this paper, we propose a similarity measure learning approach for image retrieval. The similarity measure, so called Fisher kernel, is derived from the probabilistic distribution of images and is the function over observed data, hidden variable and model parameters, where the hidden variables encode high level information which are powerful in discrimination and are failed to be exploited in previous methods. We further propose a discriminative learning method for the similarity measure, i.e., encouraging the learned similarity to take a large value for a pair of images with the same label and to take a small value for a pair of images with distinct labels. The learned similarity measure, fully exploiting the data distribution, is well adapted to dataset and would improve the retrieval system. We evaluate the proposed method on Corel-1000, Corel5k, Caltech101 and MIRFlickr 25,000 databases. The results show the competitive performance of the proposed method.

• Journal of Industrial Technology
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• v.9
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• pp.119-125
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• 1989

Lennard-Jones 유체 혹은 거의 구형에 가까운 분자들의 혼합물의 열역학적 성질을 예측하기 위한 용액이론이 유도되었다. 이 이론에는 에너지와 분자직경에 대한 두 개의 변수가 존재하며, 강구(hard sphere)를 중심으로 하여 동경함수(pair distribution function)를 확장시키는 교반이론(perturbation theory)에서 1/kT에 대한 일차와 이차계수의 관계로부터 얻어지는 혼합법칙을 이용하는 HSE이론과 달리 Orstein-Zernike결과와 일치되는 분자직경 변수를 먼저 구한 다음, 일차계수와 함께 얻어진 혼합법칙이 유도되었다. 이 방법으로 위 유체들의 혼합물에 적용시켰을 때, 원래의 HSE나 vdW-1의 방법보다 좋은 결과의 열역학적 성질을 예측할 수 있었다.

• Journal of the Korean Statistical Society
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• v.19 no.2
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• pp.105-112
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• 1990

Let (X, Y) be a pair random variables and let f denote the regression function of the response Y on the measurement variable X. Let K(f) denote a derivative of f. The least squares method is used to obtain a tensor spline estimator $\hat{f}$ of f based on a random sample of size n from the distribution of (X, Y). Under some mild conditions, it is shown that $K(\hat{f})$ achieves the optimal rate of convergence for the estimation of K(f) in $L_2$ and $L_{\infty}$ norms.