• Tribology and Lubricants
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• v.33 no.2
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• pp.45-51
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• 2017

Engine oil is a substance used for the lubrication of internal combustion systems. However, in some case, defects in engine systems may contaminate engine oil with fuel. Contaminated engine oil can cause problems in the normal functioning of a vehicle. In this study, we investigate the functional properties of engine oil contaminated with diesel fuel. The test results indicate that the engine oil contaminated with diesel fuel has low flash point, pour point, density, kinematic viscosity and cold cranking simulator value. The contaminated engine oil which has low plash point can cause fire and explosion accident. Furthermore, a four ball test indicates that the contaminated engine oil increases wear scar to poor lubricity. Moreover, we investigate the GC pattern using SIMDIST (simulated distillation) for determination of diesel in engine oil. The SIMDIST analytic result, diesel was detected at earlier retention time than engine oil in chromatogram. Thus the SIMDIST method can define whether engine oil is contaminated by diesel fuel or not. We can use the SIMDIST method for the diagnosis of oil condition instead of analyzing other physical properties that require many analytic instruments, large volume of oil sample and long analysis time.

• Fire Science and Engineering
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• v.30 no.6
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• pp.31-36
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• 2016

The flash point is one of the most important properties for characterizing the fire and explosion hazard of liquid solutions. In this study, the flash points of two flammable binary mixtures, n-pentanol + n-propanol and n-pentanol + n-heptanol systems were measured using a Seta flash closed cup tester. The flash point was estimated using the methods based on Raoult's law and multiple regression analysis. The measured flash points were also compared with the predicted flash points. The absolute average errors (AAE) of the results calculated by Raout's law were $1.3^{\circ}C$ and $1.3^{\circ}C$ for the n-pentanol + n-propanol and n-pentanol + n-heptanol mixtures, respectively. The absolute average errors of the results calculated by multiple regression analysis were $0.4^{\circ}C$ and $0.3^{\circ}C$ for the n-pentanol + n-propanol and n-pentanol + n-heptanol mixtures, respectively. According to the AAE, the calculated values based on multiple regression analysis were better than those based on Raoult's law.

• Journal of the Korean Institute of Gas
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• v.16 no.5
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• pp.41-46
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• 2012

The flash point the lowest temperature at which the concentration of vapor of the substance in the air reaches the lower flammability limit(LFL), and is one of the most important physical properties used to determine the potential for fire and explosion hazards of industrial materials. The most published flash point data was for pure components and the flash points of the binary solutions that have flammable components, appear to be scarce in the literature. In the present study, the flash points of tert-pentanol+n-decane system were measured by Tag open-cup tester. The measured data were compared with the values calculated by the Raoult's law and the optimization methods based on the Wilson and NRTL equations. The calculated values by optimization methods were found to be better than those based on the Raoult's law.

• Journal of the Korean Institute of Gas
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• v.22 no.2
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• pp.52-58
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• 2018

The flash point is one of the most important properties to characterize fire and explosion hazard of flammable liquid mixture. In this paper, the flash points of ternary liquid mixture, n-nonane+n-decane+n-tridecane system, were measured using Seta flash closed cup tester. The measured values were compared with the calculated values using Raoult's law and multiple regression analysis. The absolute average errors(AAE) of the results calculated by Raoult's law is $0.6^{\circ}C$. The absolute average errors of the results calculated by multiple regression analysis is $0.4^{\circ}C$. As can be seen from AAE, the calculated values based on multiple regresstion analysis were found to be better than those based on Raoult's law.

• Journal of the Korean earth science society
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• v.42 no.6
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• pp.623-631
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• 2021

The increased transport of marine hazardous and noxious substances (HNS) has resulted in frequent HNS spill accidents domestically and internationally. There are about 6,000 species of HNS internationally, and most of them have toxic properties. When an accidental HNS spill occurs, it can destroys the marine ecosystem and can damage life and property due to explosion and fire. Constructing a spectral library of HNS according to wavelength and developing a detection algorithm would help prepare for accidents. In this study, a ground HNS spill experiment was conducted in France. The toluene spectrum was determined through hyperspectral sensor measurements. HNS present in the hyperspectral images were detected by applying the spectral mixture algorithm. Preprocessing principal component analysis (PCA) removed noise and performed dimensional compression. The endmember spectra of toluene and seawater were extracted through the N-FINDR technique. By calculating the abundance fraction of toluene and seawater based on the spectrum, the detection accuracy of HNS in all pixels was presented as a probability. The probability was compared with radiance images at a wavelength of 418.15 nm to select abundance fractions with maximum detection accuracy. The accuracy exceeded 99% at a ratio of approximately 42%. Response to marine spills of HNS are presently impeded by the restricted access to the site because of high risk of exposure to toxic compounds. The present experimental and detection results could help estimate the area of contamination with HNS based on hyperspectral remote sensing.

• Korean Chemical Engineering Research
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• v.48 no.6
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• pp.717-724
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• 2010

The flash point is one of the most important physical properties used to determine the potential for fire and explosion hazards of flammable liquids. Despite the needs of the experimental flash point data for the design and construction of chemical plants, there is often a significant gap between the demands for the data and their availability. This study have built and compared two models of partial least squares(PLS) and support vector machine(SVM) to predict the experimental flash points of 893 organic compounds out of DIPPR 801. As the independent variables of the models, 65 functional groups were chosen based on the group contribution method that was oriented from the assumption that each fragment of a molecule contributes a certain amount to the value of its physical property, and the logarithm of molecular weight was added. The prediction errors calculated from cross-validation were employed to determine the optimal parameters of two models. And, an optimization technique should be used to get three parameters of SVM model. This work adopted particle swarm optimization that is one of heuristic optimization methods. As the selection of training data can affect the prediction performance, 100 data sets of randomly selected data were generated and tested. The PLS and SVM results of the average absolute errors for the whole data range from 13.86 K to 14.55 K and 7.44 K to 10.26 K, respectively, indicating that the predictive ability of the SVM is much superior than PLS.

• Korean Chemical Engineering Research
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• v.59 no.4
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• pp.521-531
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• 2021

Vacuum Pressure Impregnation (VPI) is a process that enhances physical properties by coating some types of epoxy resins on windings of stator used in large rotators such as generators and motors. During vacuum and pressurization of the VPI process, resin gas is generated by vaporization of epoxy resin. When the tank is opened for curing after finishing impregnation, resin gas is leaked out of the tank. If the leaked resin gas spreads throughout the workplace, there are safety and environmental problems such as fire, explosion and respiratory problems. So, exhaust system for resin gas is required during the process. In this study, a case study of exhaust efficiency by location of vent was conducted using Computational Fluid Dynamics (CFD) in order to design a system for exhausting resin gas generated by the VPI process. The optimal exhaust system of this study allowed more than 90% of resin gas to be exhausted within 1,800 seconds and reduced the fraction of resin gas below the Low Explosive Limit (LEL).