• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.5
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• pp.213-219
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• 2017

This study investigated the thermal conductivity of $CO_2$ gas mixtures in order to ascertain the effects of particular impurities in $CO_2$ in pipeline transportation. We predicted the thermal conductivity of three $CO_2$ gas mixtures ($CO_2+N_2$, $CO_2+H_2S$, and $CO_2+CH_4$) by utilizing three different methods : Chung et al., TRAPP, and the REFPROP model. We validated predictions by comparing the estimated results with 216 experimental data for $CO_2+CH_4$, $CO_2+N_2$, and $CO_2+C_2H_6$. Following $CO_2$ transportation conditions, we observed that the model developed by Chung et al. showed the lowest mean deviation of 3.07%. Further investigations were carried out on the thermal conductivity of $CO_2$ gas mixtures based on the Chung et al. model including the effects of the operation parameters of pressure, temperature, and mole fraction of impurities.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2006.05a
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• pp.310-313
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• 2006

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.2
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• pp.45-51
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• 2009

A probabilistic approach may be adopted to predict freeze and thaw depths to account for the variability of (1) material properties, and (2) contemporary and future surface energy input parameters(e.g. air temperatures, cloud cover, snow cover) predicted with global climate models. To illustrate the probabilistic approach, an example of the predicted of thaw depths in cold regions is considered. More specifically, the Stefan equation is used together with the Monte Carlo simulation technique to make a probabilistic prediction of thaw penetration. The simulation results indicate that the variability in material properties, surface energy input parameters and temperature data can lead to significant uncertainty in predicting thaw penetration.

• Composites Research
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• v.29 no.1
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• pp.33-39
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• 2016

In this study, geometric modeling and finite element analysis of 3-dimensional plain weave composite unit cell consisting of 3 interlaced fiber tows and resin pocket were performed to predict effective properties. First, tow properties were obtained from micro-mechanics finite element unit cell analysis, which were then used in the meso-mechanics analysis. The effective properties were obtained from a series of unit cell analyses simulating uniaxial tensile and shear tests. Analysis results were compared to the analysis and experimental results in the literature. Various crimp angles were considered and the effect on the effective properties was investigated. Initial failure strengths and failure sequence were also examined.

• Clean Technology
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• v.18 no.3
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• pp.265-271
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• 2012

The use of renewable energies has been required to diminish the dependency on fossil fuels. As one of clean energy sources biomass has been extensively studied because various biomass resources necessitated rapid characterization of their chemical and physical properties in an on-line or real-time basis. For such an analysis near-infrared (NIR) spectroscopy has been successfully applied because of its non-invasive and informative characteristics. In this work, the applicability of nonlinear chemometric techniques based on biomass near infrared (NIR) data is evaluated for the rapid prediction of ash/char contents in different types of biomass. The prediction results of various prediction models and the effect of using preprocessing methods for NIR data are compared using six types of biomass NIR data. The results showed that nonlinear prediction models yielded better prediction performance than linear ones. It also turned out that by adopting the use of proper preprocessing methods the performance of prediction of biomass properties improved.

• Journal of the korean Society of Automotive Engineers
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• v.14 no.6
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• pp.1-8
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• 1992

본 고에서는 균질화법의 정식화를 이용하여 복합재료의 거시적 균질화된 재료상수를 구하고, 이 재료상수를 이용하여 거시구조물의 변형과 응력을 구하고, 이로부터 다시 미시구조의 응력분포와 변형도를 구하는 방법을 기술하였다. 주기성을 가정한 균질화법은 복합재료 구조물의 물성평가와 거동예측에 대한 매우 적절한 수치해석 방법이다. 균질화법은 이러한 선형변형의 문제뿐만 아니라, 내압을 존재하는 빈공간 소재의 물성, 기지재료와 강화재료 계면의 미끄러짐 등으로 인한 미세 파손현상 등의 예측이 가능하다. 그외에도 탄소성 대변형 거동 이론과 균질화법을 함께 적용하여, squeeze casting에서 발생하기 쉬운 계면분리나 파단 등의 미소결함과 같은 2차 성형성의 예측도 가능하다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.277-280
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• 2019

본 논문에서는 화학분야 특허 문서에 존재하는 도표(TABLE) 데이터를 인공지능 기술을 활용하여 자동으로 추출하고 정형화된 형태로 가공하는 방법을 제안한다. 특허 문서에서 도표 데이터는 실시예에서 실험결과나 비교결과를 간결하고 가시적으로 표현하기 위하여 주로 사용되나, 셀의 속성을 정의하는 헤더부분과 수치가 표현되는 값 부분의 경계가 모호하여 구조화하는데 어려움이 있다. 본 논문에서 제안하는 방법은 소량의 학습데이터를 구축하고 기계학습을 통해 도표에 존재하는 셀의 속성을 예측하고, 예측된 속성을 토대로 조성과 물성 정보를 자동으로 구분하여 추출하는 방법을 제시한다. 제시된 방법을 활용하여 화학 분야 조성물 특허의 도표데이터에 시뮬레이션 결과 각 항목별 98.17%의 속성 예측 정확도를 나타내었으며 기존 규칙기반 연구보다 작업난이도, 예측정확도에서 우수한 성과를 보인다.

• Proceeding of EDISON Challenge
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• 2015.03a
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• pp.229-233
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• 2015

복합재는 높은 비강도와 비강성을 가지고 있어 자동차, 항공기 등 전반적인 산업분야에서 널리 사용되는 재료이다. 우주선의 노즐 부분과 같이 높은 온도뿐만 아니라 높은 압력이 작용하는 환경에서 사용하기 위한 재료로 복합재가 필요하다. 복합재의 물성치를 아는 것은 매우 중요한데 모재(matrix)와 강화섬유(fiber) 각각의 물성치를 수치적으로 대입해 얻는 결과는 실험값과의 오차가 커 예측하는데 있어 더 정확한 방법이 필요할 것이다. 본 연구에서는 유한요소법을 이용한 EDISON용 CASADsolver 프로그램을 활용해 분석하였다. Matrix와 fiber의 물성치를 대입해 복합재의 물성치를 구해 실험으로 측정된 물성치, 경험식으로 계산된 물성치와 비교를 하였다.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.11a
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• pp.123-126
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• 2011

A Fuel-rich preburner using kerosene fuel is operated in a non-equilibrium condition and a prediction of burnt-gas properties is not easy from a chemical equilibrium analysis. A premixed counter-flow flame analysis was conducted for the prediction of burnt-gas properties. JP10 was selected for a representative kerosene fuel and a non-equilibrium combustion analysis was accomplished in supercritical condition using UC San Diego reaction mechanism. The premixed counter-flow flame was assumed for stationary and stable flame, and the temperature result in present study was overestimated rather than the experimental results from Huzel. From the difference of the temperature result, other properties, heat capacity, specific heat ratio and molecular weight had some differences against the experimental results. Moreover, the present results was more similar to the experimental results than those of the equilibrium analysis.

• Composites Research
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• v.30 no.4
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• pp.247-253
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• 2017

In this study, the mechanical behavior and interface properties of boron nitride nanotube-poly(methyl methacrylate) nanocomposites are predicted using the molecular dynamics simulations and the double inclusion model. After modeling nanocomposite unit cell embedding single-walled nanotube and polymer, the stiffness matrix is determined from uniaxial tension and shear tests. Through the orientation average of the transversely isotropic stiffness matrix, the effective isotropic elastic constants of randomly dispersed microstructure of nanocomposites. Compared with the double inclusion model solution with a perfect interfacial condition, it is found that the interface between boron nitride nanotube and polymer matrix is weak in nature. To characterize the interphase surrounding the nanotube, the two step domain decomposition method incorporating a linear spring model at the interface is adopted. As a result, various combinations of the interfacial compliance and the interphase elastic constants are successfully determined from an inverse analysis.