• 소성∙가공
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• 제29권4호
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• pp.218-228
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• 2020

The prediction of final mass and optimized process conditions of injection molded products using Artificial Neural Network (ANN) were demonstrated. The ANN was modeled with 10 input parameters and one output parameter (mass). The input parameters, i.e.; melt temperature, mold temperature, injection speed, packing pressure, packing time, cooling time, back pressure, plastification speed, V/P switchover, and suck back were selected. To generate training data for the ANN model, 77 experiments based on the combination of orthogonal sampling and random sampling were performed. The collected training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. Grid search and random search method were used to find the optimized hyper-parameter of the ANN model. After the training of ANN model, optimized process conditions that satisfied the target mass of 41.14 g were predicted. The predicted process conditions were verified through actual injection molding experiments. Through the verification, it was found that the average deviation in the optimized conditions was 0.15±0.07 g. This value confirms that our proposed procedure can successfully predict the optimized process conditions for the target mass of injection molded products.

• 한국화재소방학회논문지
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• 제32권1호
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• pp.1-6
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• 2018

인화점은 산업현장에서 액체의 화재 및 폭발 위험을 결정하는데 사용되는 가장 중요한 변수 중 하나로써 가연성 물질의 화재 위험성을 나타내는 지표이며 안정성 평가에 많이 사용되고 있다. 따라서 본 연구는 다양한 산업에서 용매로 사용되는 이성분계 혼합물 중 {methanol+toluene}, {ethanol+toluene} 그리고 {1-propanol+toluene}에 대한 인화점을 SETA 밀폐식 인화점 측정기를 이용하여 측정하였다. 각 이성분계 혼합물에 대한 인화점을 예측하기 위해 Raoult's의 법칙, Wilson, NRTL 및 UNIQUAC 파라미터를 이용하였고 실험 결과와 비교하였다. Raoult's의 법칙을 제외한 비교 결과, 모든 예측값과 실험값은 유사한 값을 보였고 편차가 1.69 K이내의 결과를 보였다.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2002년도 강연요지집
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• pp.97-117
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• 2002

A chemoinfometrical method for quantitative determination of crystal content of indomethacin (IMC) polymorphs based on fourie-transformed near-infrared (FT-NIR) spectroscopy was established. A direct comparison of the data with the ones collected from using the conventional powder X-ray diffraction method was performed. Pure $\alpha$ and ${\gamma}$ forms of IMC were prepared using published methods. Powder X-ray diffraction profiles and NIR spectra were recorded for six kinds of standard materials with various content of ${\gamma}$ form IMC. The principal component regression (PCR) analyses were performed based on normalized NIR spectra sets of standard samples of known content of IMC ${\gamma}$ form. A calibration equation was determined to minimize the root mean square error of the prediction. The predicted ${\gamma}$ form content values were reproducible and had a relatively small standard deviation. The values of ${\gamma}$ form content predicted by two methods were in close agreement. The results were indicated that NIR spectroscopy provides for an accurate quantitative analysis of crystallinity in polymorphs compared with the results obtained by conventional powder X-ray diffractometry.

• 한국도로학회논문집
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• 제18권1호
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• pp.91-97
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• 2016

PURPOSES : The objective of this paper is to develop a pavement performance model based on the Bayesian algorithm, and compare the measured and predicted performance data. METHODS : In this paper, several pavement types such as SMA (stone mastic asphalt), PSMA (polymer-modified stone mastic asphalt), PMA (polymer-modified asphalt), SBS (styrene-butadiene-styrene) modified asphalt, and DGA (dense-graded asphalt) are modeled in terms of the performance evaluation of pavement structures, using the Bayesian algorithm. RESULTS : From case studies related to the performance model development, the statistical parameters of the mean value and standard deviation can be obtained through the Bayesian algorithm, using the initial performance data of two different pavement cases. Furthermore, an accurate performance model can be developed, based on the comparison between the measured and predicted performance data. CONCLUSIONS : Based on the results of the case studies, it is concluded that the determined coefficients of the nonlinear performance models can be used to accurately predict the long-term performance behaviors of DGA and modified asphalt concrete pavements. In addition, the developed models were evaluated through comparison studies between the initial measurement and prediction data, as well as between the final measurement and prediction data. In the model development, the initial measured data were used.

• Tribology and Lubricants
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• 제30권6호
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• pp.356-363
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• 2014

Marine diesel engines operate in environments in which damage easily occurs from corrosion. Recently, damage to cylinder liners has increased from corrosion wear caused by increased engine power. This damage can cause serious problems in the economy. Thus, many researchers have treated and studied damaged cylinder liners. However, a method is necessary for real-time monitoring of damage to cylinder liners during operation of the engine, before serious damage can occur. This study carries out reciprocating friction and wear tests on a cast iron specimen under various corrosion atmospheres and verifies the variations of friction coefficient and friction surface. Additionally, the friction coefficient and friction status are predicted by using a neural network that learns the vibration and frequency spectrum data from an acceleration sensor. According to our conclusions, amplitude is distributed highly at high frequencies, and values of standard deviation and kurtosis are high when damage to the friction surface is serious. The accuracy rate of the friction coefficient predicted by the neural network is over 80% of the real measured value without NaCl, and application of the neural network is very effective for diagnosing the friction condition and damage to the cylinder liner.

• 한국가시화정보학회지
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• 제20권3호
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• pp.109-116
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• 2022

The optimized design of airfoils is essential to increase the performance and efficiency of wind turbines. The aerodynamic characteristics of airfoils near the stall show large deviation from experiments and numerical simulations. Hence, it is needed to perform repetitive analysis of various shapes near the stall. To overcome this, the artificial intelligence is used and combined with numerical simulations. In this study, three types of airfoils are chosen, which are S809, S822 and SD7062 used in wind turbines. A convolutional neural network model is proposed in the combination of VGG16 and U-Net. Learning data are constructed by extracting pressure fields and aerodynamic characteristics through numerical analysis of 2D shape. Based on these data, the pressure field and lift coefficient of untrained airfoils are predicted. As a result, even in untrained airfoils, the pressure field is accurately predicted with an error of within 0.04%.

• 한국화재소방학회논문지
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• 제29권5호
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• pp.1-6
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• 2015

인화점은 화재 및 액체의 폭발 위험의 가능성을 결정하는 데 사용되는 가장 중요한 물리적 특성이고, 산업공정에서 안정성 평가시 중요한 연소특성 가운데 하나이다. 따라서 본 연구는 4류 위험물 중 알코올계 혼합물인 {methanol + 1-butanol}, {ethanol + 1-butanol} 그리고 {2-propanol + 1-butanol} 이성분계 101.3 kPa에서 최소인화점을 SETA closed cup flash point tester를 이용하여 측정하였다. 각 이성분계에 대하여 Wilson, NRTL 및 UNIQUAC 파라미터를 이용하여 혼합물에 대한 인화점 예측하고 실험 결과와 비교하였다. 비교결과 모든 예측값과 실험값은 유사한 값을 보였고 편차가 1.14 K 이내의 결과를 보였다.

• Computers and Concrete
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• 제1권3호
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• pp.325-354
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• 2004

Slabs in buildings and bridge decks, which are restrained against lateral displacements at the edges, have ultimate strengths far in excess of those predicted by analytical methods based on yield line theory. The increase in strength has been attributed to membrane action, which is due to the in-plane forces developed at the supports. The benefits of compressive membrane action are usually not taken into account in currently available design methods developed based on plastic flow theories assuming concrete to be a rigid-plastic material. By extending the existing knowledge of compressive membrane action, it is possible to design slabs in building and bridge structures economically with less than normal reinforcement. Recent research on building and bridge structures reflects the importance of membrane action in design. This paper describes the finite element modelling of membrane action in reinforced concrete slabs through optimisation of a simple concrete model. Through a series of parametric studies using the simple concrete model in the finite element simulation of eight fully clamped concrete slabs with significant membrane action, a set of fixed numerical model parameter values is identified and computational conditions established, which would guarantee reliable strength prediction of arbitrary slabs. The reliability of the identified values to simulate membrane action (for prediction purposes) is further verified by the direct simulation of 42 other slabs, which gave an average value of 0.9698 for the ratio of experimental to predicted strengths and a standard deviation of 0.117. A 'deflection factor' is also established for the slabs, relating the predicted peak deflection to experimental values, which, (for the same level of fixity at the supports), can be used for accurate displacement determination. The proposed optimised concrete model and finite element procedure can be used as a tool to simulate membrane action in slabs in building and bridge structures having variable support and loading conditions including fire. Other practical applications of the developed finite element procedure and design process are also discussed.

• 한국해안·해양공학회논문집
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• 제21권5호
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• pp.391-404
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• 2009

삼천포 화력발전소에서 냉각수로 이용되고 방류되는 해수를 이용한 소수력 발전소를 건설하였다. 본 연구에서는 해양소수력 발전소 건설시 가장 중요한 문제인 기존 화력발전소의 순환수 계통에 미치는 영향을 평가하기 위한 방안으로 배수로 수위의 해양소수력 건설 이전, 건설 중, 건설 이후 해양소수력 운전 상태에서의 변화를 예측한 값과 실제 계측값을 분석하였다. 설계시 일반적으로 이용되는 개수로 수리식에서부터 Flow 3D를 이용하여 3차원적인 수리해석 기법을 이용하는 것까지 다양한 예측을 시도하였고 관측을 통하여 검증하고자 하였다. 예측치와 실제 관측치의 비교 결과, 수위의 전체적인 평균값은 예측치와 관측치가 유사하였지만 수위의 변화 폭은 건설 중과 해양소수력 운전 상태에서 매우 크게 나타났다. 또한, 소수력 건설 이전에는 표준위어식과 Honma식의 예측값이 관측값과 가장 유사하였으나, 소수력 건설 이후에는 HEC-2, HEC-RAS, Flow-3D의 예측값이 실측값과 가까운 결과를 보였다.

• 멤브레인
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• 제6권1호
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• pp.22-31
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• 1996

35$^{\circ}$C에서 polydimethytsiloxane(PDMS)막에 의한 이소프로판올수용액의 투과증발실험을 행하여 이소프로판올의 부피분율이 0.5~0.7범위에서 이상적인 투과속도로부터 가장 크게 벗어났다. 이소프로판올의 가소화 영향은 물의 투과를 증가시키는 데 비하여 물의 존재는 이소프로판올의 투과를 감소시키는 경향을 나타내었다. 혼합물에서 농도에 의존하는 확산계수를 Vignes식으로 나타내고, Flory-Huggins열역학과 Maxwell-Stefan식을 이용하여 투과속도와 선택도를 예측하였다. 이소프로판올과 물 사이의 Flory-Huggins상호작용계수는 과잉Gibbs에너지를 이용하여 계산하였으며 각 액체 성분과 고분자 사이의 상호작용계수는 평행팽윤 실험에 의하여 결정하였다. 이론적으로 예측한 투과속도는 35%이내의 오차범위에서 실험값과 일치하였으며, 투과선택도는 전 농도 범위에서 실험값과 이론값이 잘 일치하였다.