• Journal of Korea Soil Environment Society
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• v.1 no.2
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• pp.3-13
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• 1996

The efficiency of bioremedation can be measured by the enumeration of microorganism, respiration rate and decomposition rate. The side-effect can be measured by using Daphnia, oyster larvae and rainbow trout. Oxygen transfer could be a problem in the on-site treatment. For these, hydrogen peroxide can be used for solvents such as benzenes. Oleophilic nitrogen and phosphorus can be added for the treatment of oil pollution. Mixed microbial population or pure culture can be used for the inoculum. The pure culture used is Pseudomonas and Phanerochate. Sometimes enzymes are added and Photodegadation is coupled to increase the efficiency. For the treatment of oil pollution residue on soil such as waste lubrication oil and machine oil sludges, top soil of 15cm∼20cm depth is plowed and oil residue with approximately 5% concentration is applied. The optimum pH range is 7∼8, the ratio of phosphorus to hydrocarbon is 1:800. Appropriate drainage is necessary. For the treatment of marine oil pollution residue, addition of oleophilic fertilizer is effective. Air pollutiant such as oder can be treated by bioremediation. In this case, biofilters or biosrubbers are used for the reactor.

• Steel and Composite Structures
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• v.49 no.6
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• pp.645-666
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• 2023

Due to the steadily declining supply of natural coarse aggregates, the concrete industry has shifted to substituting coarse aggregates generated from byproducts and industrial waste. Oil palm shell is a substantial waste product created during the production of palm oil (OPS). When considering the usage of OPSC, building engineers must consider its uniaxial compressive strength (UCS). Obtaining UCS is expensive and time-consuming, machine learning may help. This research established five innovative hybrid AI algorithms to predict UCS. Aquila optimizer (AO) is used with methods to discover optimum model parameters. Considered models are artificial neural network (AO - ANN), adaptive neuro-fuzzy inference system (AO - ANFIS), support vector regression (AO - SVR), random forest (AO - RF), and extreme gradient boosting (AO - XGB). To achieve this goal, a dataset of OPS-produced concrete specimens was compiled. The outputs depict that all five developed models have justifiable accuracy in UCS estimation process, showing the remarkable correlation between measured and estimated UCS and models' usefulness. All in all, findings depict that the proposed AO - XGB model performed more suitable than others in predicting UCS of OPSC (with R², RMSE, MAE, VAF and A_15-index at 0.9678, 1.4595, 1.1527, 97.6469, and 0.9077). The proposed model could be utilized in construction engineering to ensure enough mechanical workability of lightweight concrete and permit its safe usage for construction aims.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.3 s.192
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• pp.100-107
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• 2007

A internal lobe pump is suitable for oil hydraulics of machine tools, automotive engines, compressors, constructions and other various applications. In particular, the pump is an essential machine element of an automotive engine to feed lubricant oil. The subject of this paper is the theoretical analysis of internal lobe pump whose the main components are the rotors: usually the outer one is characterized by lobes with circular shape, while the inner rotor profile is determined as conjugate to the other. The topic of this paper is the design of a new rotor, which is based on specific performance as different types depending on the shape of the lobe of the outer rotor. First, the design of internal lobe pumps with circular, elliptical, and their combined lobe profiles is considered. The latter is a new type of lobe profile with special shape whose curvature follows a definite function. Then we introduce the performance indexes used for the comparison. Some of these indexes, such as flow rate and flow rate irregularity, are commonly used for the comparison, while specific slipping is particularly suitable in this case. It is possible to notice that the circular and elliptical type is comparable to the circular one or the elliptical one in terms of flow rate irregularity, but has improved performance in terms of specific slipping. Results obtained from the analysis enable the designer and manufacturer of oil pump to be more efficient in this field.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.9
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• pp.67-77
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• 2010

An internal lobe pump is suitable for oil hydraulics of machine tools, automotive engines, compressors, constructions and other various applications. In particular, the pump is an essential machine element of an automotive engine to feed lubricant oil. The subject of this paper is the theoretical analysis of internal lobe pump whose the main components are the rotors: usually the outer one is characterized by lobe with elliptical and involute shapes, while the inner rotor profile is determined as conjugate to the other. And the integrated design system which is composed of three main modules has been developed through AutoLISP under AutoCAD circumstance plus CFD-ACE+. It generates new lobe profile and calculates automatically the flow rate and flow rate irregularity according to the lobe profile generated. CFD simulation results show trends similar to those carried out in experiments, and a quantitative comparison is presented. Results obtained from the automotive integrated design system enable the designer and manufacturer of oil pump to be more efficient in this field.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.53-59
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• 2020

Initial response is important in marine oil spills, such as the Hebei Spirit oil spill, but it is very difficult to predict the movement of oil out of the ocean, where there are many variables. In order to solve this problem, the forecasting of oil spill has been carried out by expanding the particle prediction, which is an existing study that studies the movement of floats on the sea using the data of the float. In the ocean data format HDF5, the current and wind velocity data at a specific location were extracted using bilinear interpolation, and then the movement of numerous points was predicted by particles and the results were visualized using polygons and heat maps. In addition, we propose a spill oil particle matching algorithm to compensate for the lack of data and the difference between the spilled oil and movement. The spilled oil particle matching algorithm is an algorithm that tracks the movement of particles by granulating the appearance of surface oil spilled oil. The problem was segmented using principal component analysis and matched using genetic algorithm to the point where the variance of travel distance of effluent oil is minimized. As a result of verifying the effluent oil visualization data, it was confirmed that the particle matching algorithm using principal component analysis and genetic algorithm showed the best performance, and the mean data error was 3.2%.

• Journal of the Korea Convergence Society
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• v.8 no.10
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• pp.45-52
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• 2017

Drifter is an equipment for observing the characteristics of seawater in the ocean, and it can be used to predict effluent oil diffusion and to observe ocean currents. In this paper, we design models or the prediction of drifter trajectory using machine learning. We propose methods for estimating the trajectory of drifter using support vector regression, radial basis function network, Gaussian process, multilayer perceptron, and recurrent neural network. When the propose mothods were compared with the existing MOHID numerical model, performance was improve on three of the four cases. In particular, LSTM, the best performed method, showed the imporvement by 47.59% Future work will improve the accuracy by weighting using bagging and boosting.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.5
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• pp.247-255
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• 2018

In this research, the effect of normal load, sliding velocity, and texture density on thefriction coefficient of surfaces micro-textured on AISI 4140 under paraffin oil lubrication were investigated. The predicted tribological behavior by numerical calculation can be serves as guidance for the designer during the machine development stage. Therefore, in this research friction coefficient prediction model based on response surface methodology (RSM), support vector machine (SVM), and artificial neural network (ANN) were developed. The experimental result shows that the variation of load, speed and texture density were influence the friction coefficient. The RSM, ANN and SVM model was successfully developed based on the experimental data. The ANN model can effectively predict the tribological characteristics of micro-textured AISI 4140 in paraffin oil lubrication condition compare to RSM and SVM.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.3
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• pp.563-570
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• 2018

This paper proposes an efficient dissolved gas analysis(DGA) and classification method of an oil-filled transformer using machine learning algorithms to solve problems inherent in IEC 60599. In IEC 60599, a certain diagnosis criteria do not exist, and duplication area is existed. Thus, it is difficult to make a decision without any experts since the IEC 60599 standard can not support analysis and classification of gas date of a power transformer in that criteria. To address these issue. we propose a dissolved gas analysis(DGA) and classification method using a machine learning algorithm. We evaluate the performance of the proposed method using support vector machines with dissolved gas dataset extracted from a power transformer in the real industry. To validate the performance of the proposed method, we compares the proposed method with the IEC 60599 standard. Experimental results show that the proposed method outperforms the IEC 60599 in the classification accuracy.

• Advanced Composite Materials
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• v.18 no.4
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• pp.315-326
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• 2009

PCC (precipitated calcium carbonate) and ground calcium carbonate have been widely used in alkaline papermaking. Unfortunately, although increasing filler level in papers can improve the paper properties such as brightness, opacity, stiffness gloss, smoothness, porosity, and printability, as well as decrease cost, some strength of the paper is negatively affected. In this research, needle-like aragonite was synthesized using $Ca(OH)_2$ and $CO_2$ as reactants in the presence of $MgCl_2$ and characterized with scanning electronic microscopy (SEM) and X-ray diffraction (XRD). The physical and optical properties of the paper handsheets containing these needle-like aragonite fillers were evaluated. Results indicated that tensile strength, Z-direction tensile strength and folding endurance of the paper were improved by the needle-like aragonite crystals compared to the paper using commercial PCC (precipitated calcium carbonate) as filler. The stiffness of the paper handsheet on the machine direction was increased, but no evident difference in the cross direction was found. The improvement of paper strength mainly resulted from the twining effect between the aragonite whiskers and paper fibers. The optical properties of the paper were slightly decreased with the use of the needle-like aragonites compared to commercial PCC. These results suggest that paper cost can be decreased by increasing the content of needle-like aragonite filler while paper strength will not be decreased compared to PCC filler.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.3
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• pp.16-23
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• 2017

For most machine tools, it is necessary to remove chips and coolant oil because it they will continue to be created during the manufacture of workpieces. Existing products that are in use are installed and used as they reflect depending on the characteristics of each device separately. This study proposes a method to remove the security chip as well as developing an integrated system capable of reducing coolant damage. The Leverage AutoCAD and CATIA program was used for 2D and 3D design, shapes were identified by utilizing the KeyShot program, and the load and displacement analysis of the development apparatus was performed utilizing the ANSYS program. After the prototype underwent sufficient design review, the mixed oil separation device had a complete sensor control program using the LabVIEW program. The chip design process for transferring experiments and experiments on the mixed oil cooling device were developed for performance tests of the product. The final product resulted in an increase in space utilization during commercialization, reduced installation costs, and caused social effects such as pulmonary flow reduction, which, through the economic costs, reduces pollution, resulting in various benefits to the industry, such as deceased errors in the workplace decreases.