• Bulletin of the Korean Chemical Society
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• 제26권12호
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• pp.2007-2016
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• 2005

An artificial neural network (ANN) is successfully presented for prediction acidity constant (pKa) of various benzoic acids and phenols with diverse chemical structures using a nonlinear quantitative structure-property relationship. A three-layered feed forward ANN with back-propagation of error was generated using six molecular descriptors appearing in the multi-parameter linear regression (MLR) model. The polarizability term $(\pi_1)$, most positive charge of acidic hydrogen atom $(q^+)$, molecular weight (MW), most negative charge of the acidic oxygen atom $(q^-)$, the hydrogen-bond accepting ability $(\epsilon_B)$ and partial charge weighted topological electronic (PCWTE) descriptors are inputs and its output is pKa. It was found that properly selected and trained neural network with 205 compounds could fairly represent dependence of the acidity constant on molecular descriptors. For evaluation of the predictive power of the generated ANN, an optimized network was applied for prediction pKa values of 37 compounds in the prediction set, which were not used in the optimization procedure. Squared correlation coefficient $(R^2)$ and root mean square error (RMSE) of 0.9147 and 0.9388 for prediction set by the MLR model should be compared with the values of 0.9939 and 0.2575 by the ANN model. These improvements are due to the fact that acidity constant of benzoic acids and phenols in water shows nonlinear correlations with the molecular descriptors.

• 한국수소및신에너지학회논문집
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• 제24권3호
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• pp.264-274
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• 2013

Piping systems play an important role in gas and oil transferring system. In the piping system, there are many elements, such as valves and flow meters. In order to check their normal operating conditions, each signal from each element is displayed on the monitor in the pipe control room. By the way, there are several accidental cases in the piping system even if all signals from the local elements are judged to be normal on the monitor in the control room. Further, opposite cases often happen even the monitor shows abnormal while the local elements work normal. To overcome this abnormal functions, it is not so easy to construct the environment in which sensors detecting the working states of all elements installed in the piping system. In this paper, a new non-contact measurement technique which can calculate the elements' delicate displacements by using a PIV(particle image velocimetry) and diagnose their working states by using a neural network is proposed. The measurement system consists of a host computer, a micro system, a telescope and a high-resolution camera. As a preliminary test, the constructed measurement system was applied to measure delicate vibrations of mobile phones. For practical application, a pneumatic system was measured by the constructed system.

• 한국수소및신에너지학회논문집
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• 제31권5호
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• pp.436-443
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• 2020

The performance prediction model of a solid oxide fuel cell stack has been developed using deep neural network technique, one of the machine learning methods. The machine learning has been received much interest in various fields, including energy system mo- deling. Using machine learning technique can save time and cost requried in developing an energy system model being compared to the conventional method, that is a combination of a mathematical modeling and an experimental validation. Results reveal that the mean average percent error, root mean square error, and coefficient of determination (R2) range 1.7515, 0.1342, 0.8597, repectively, in maximum. To improve the predictability of the model, the pre-processing is effective and interpolative machine learning and application is more accurate than the extrapolative cases.

• 천문학논총
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• 제22권4호
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• pp.189-199
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• 2007

In this paper, we describe the proposed KVN (Korean VLBI Network) clock system in order to make the observation of the VLBI effectively. In general, the GPS system is widely used for the time information in the single dish observation. In the case of VLBI observation, a very high precise frequency standard is needed to perform the observation in accordance with the observation frequency using the radio telescope with over 100km distance. The objective of the high precise clock system is to insert the time-tagging information to the observed data and to synchronize it with the same clock in overall equipments which used in station. The AHM (Active Hydrogen Maser) and clock system are basically used as a frequency standard equipments at VLBI station. This system is also adopted in KVN. The proposed KVN clock system at each station consists of the AHM, GPS time comparator, standard clock system, time distributor, and frequency standard distributor. The basic experiments were performed to check the AHM system specification and to verify the effectiveness of implemented KVN clock system. In this paper, we briefly introduce the KVN clock system configuration and experimental results.

• 한국추진공학회지
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• 제25권6호
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• pp.1-11
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• 2021

층류화염편 라이브러리에 대한 효율적인 계산과정을 개발하기 위하여 초임계 압력조건의 기체수소/액체산소 연소기에 대해 인공신경망을 이용한 기계학습과정이 적용되었다. 학습성능과 계산효율성에 근거한 최적의 계산과정을 찾기 위하여 은닉층에 대한 ReLU와 쌍곡탄젠트 함수의 25가지 조합이 선택되었다. 정확성이 우수한 높은 학습성능을 얻는데 쌍곡탄젠트 활성화함수가 적절하였다. 인공신경망의 학습성능을 개선하기 위해서 학습데이터 변환이 제안되었다. 4개의 은닉층에 최적의 노드를 배치할 때 학습성능 및 계산비용 관점에서 모두 효율적인 것으로 나타났다. 층류화염편 라이브러리의 보간법보다 인공신경망을 사용하는 경우 전체 계산시간은 37%, 시스템 메모리는 99.98% 감소되었다.

• 한국가스학회지
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• 제28권1호
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• pp.1-10
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• 2024

본 연구에서는 농업 분야 에너지 자립 시스템 기술도입의 일환으로 농산부산물 기반 SOFC 열병합발전 시스템의 공정 모사 모델을 구축하고 열교환망 최적화를 진행하였다. 0.3 ton/d급 농산부산물 반탄화 연료 가스화기 실험 결과를 기반 농산부산물 SOFC 열병합발전 시스템 모델을 구축하여 4~20 kW급 SOFC 발전 용량별 열교환망 최적화를 진행하였다. 현재 시스템상에서 8 kW급 농산부산물 기반 SOFC 열병합발전 시스템이 최적으로 도출되었으며, 본 연구 결과를 기반으로 추후 상용 설비 설계 시 기초자료로 활용이 가능할 것으로 판단된다.

• Bulletin of the Korean Chemical Society
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• 제25권4호
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• pp.466-470
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• 2004

The crystals of the new melaminium salt, i.e. melaminium acetate acetic acid solvate monohydrate, $C_3H_7N_6^+ {\cdot}CH_3COO^- {\cdot}CH_3COOH{\cdot}H_2O$, were obtained by the slow evaporation of an aqueous solution at room temperature. Powder infrared and Raman spectra were measured and interpreted. The vibrational spectra in the region of internal vibrations of ions corroborate structural data recently published by Perpetuo and Janczak.$^1$ Some spectral features of this new crystal are referred to corresponding one for melamine crystal as well as other melamine complexes in crystalline form. Hydrogen-bonded network present in the crystal gives notable vibrational effect.

• 한국고분자학회:학술대회논문집
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• 한국고분자학회 2006년도 IUPAC International Symposium on Advanced Polymers for Emerging Technologies
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• pp.297-297
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• 2006

Recently columnar liquid crystals have been studied due to their possible application to organic conducting materials. Supramolecular columnar liquid crystals consist of mesogenic unit which can aggregate into discs that will make up the columns which associate to form a two-dimensional network. In this study, we prepared supramolecular columnar liquid crystals containing hydrogen bonding between carboxylic acid and, pyridine moieties. Thermal and structural properties of prepared complexe were investigated, and it exhibited hexagonal columnar structure ($Col_{h}$) at room temperature.

• 대한화학회지
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• 제16권1호
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• pp.6-12
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• 1972

The crystal structure of monoethanolamine hydrochloride is triclinic P1 with two formula units in a cell of dimensions a = $4.42\pm0.02$, b = $7.44\pm0.02$, c = $7.48\pm0.02$, $\alpha$ = $102.4\pm0.3$, $\beta$ = $91.1\pm0.3$, $\gamma$ = $77.2\pm0.3^{\circ}.$ The configuration of monoethanolamine is a gauche form with dihedral angle, $90^{\circ}$. The nitrogen atom forms four hydrogen bonds, three to Cl- ions(3.15, 3.24, $3.28\AA)$ and one to a hydroxyl group of another molecule (N${\cdot}{\cdot}{\cdot}$O, $2.90{\AA})$. The oxygen also forms two such bonds, one to a Cl- ion $(3.14\AA)$, one to an amine group of another molecule (O${\cdot}{\cdot}{\cdot}$N, $2.90{\AA}).$ Molecules are linked into two-dimensional network by hydrogen bonds.

• 한국펄프종이공학회:학술대회논문집
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• 한국펄프종이공학회 2006년도 PAN PACIFIC CONFERENCE vol.2
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• pp.423-426
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• 2006

Paper has fibers and fines network structure and it is strongly affected by interface bonding between fibers. Depending on the inter-fiber bonding, paper bulk is determined. Fines play an important roll in Campbell and consolidation effect through wet pressing and drying operations. Refined Sw-BKP, Hw-BKP and BCTMP fines were used to investigate the fines effect. Wet-web strength, breaking length, scattering coefficient, and hydrodynamic specific volume were measured. According to the result of experiments, chemical and morphological compositions of fines do not strongly affect to wet-web forming, but strongly affect to drying operations which form hydrogen bonding among fiber-fines-fiber matrixes. Paper bulk should be controlled by the extent of hydrogen bonding between fibers during drying operations.