• Design & Manufacturing
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• v.13 no.2
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• pp.54-59
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• 2019

CNC(Computer Numerical Control) machine tools are being used in various industrial fields such as aircraft and automobiles. The machining conditions used in the mold industry are used, and the simulation and the experiment are compared. The tool used in the experiment was carried out to increase the reliability of the simulation of the cutting machining. The program used in the 3D-FEM (finite element method) was the AdvantEdge and predicted by down-milling. The tool model is used 3D-FEM simulation by using the cutting force, temperature prediction. In this study, we carried out the verification of cutting force by using a 3-axis tool dynamometer (Kistler 9257B) system when machining the plastic mold Steel machining of NAK-80. The cutting force experiment data using on the charge amplifier (5070A) is amplified, and the 3-axis cutting force data are saved as a TDMS file using the Lab-View based program using on NI-PXIe-1062Q. The machining condition 7 was the most similar to the simulation and the experimental results. The material properties of the NAK-80 material and the simulation trends reflected in the reverse design of the tool were derived similarly to the experimental results.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.5
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• pp.50-56
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• 2014

A technique based on the finite element method (FEM) is used in the simulation of metal cutting process. This offers the advantages of the prediction of the cutting force, the stresses, the temperature, the tool wear, and optimization of the cutting condition, the tool shape and the residual stress of the surface. However, the accuracy and reliability of prediction depend on the flow stress of the workpiece. There are various models which describe the relationship between the flow stress and the strain. The Johnson-Cook model is a well-known material model capable of doing this. Low-alloy steel is developed for a dry storage container for used nuclear fuel. Related to this, a process analysis of the plastic machining capability is necessary. For a plastic processing analysis of machining or forging, there are five parameters that must be input into the Johnson-Cook model in this paper. These are (1) the determination of the strain-hardening modulus and the strain hardening exponent through a room-temperature tensile test, (2) the determination of the thermal softening exponent through a high-temperature tensile test, (3) the determination of the cutting forces through an orthogonal cutting test at various cutting speeds, (4) the determination of the strain-rate hardening modulus comparing the orthogonal cutting test results with FEM results. (5) Finally, to validate the Johnson-Cook material parameters, a comparison of the room-temperature tensile test result with a quasi-static simulation using LS-Dyna is necessary.

• Journal of Korean Society on Water Environment
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• v.23 no.5
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• pp.591-599
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• 2007

The quality of water released from a stratified reservoir is dependent on various factors such as the location and shape of intake facility, structure of reservoir stratification, profile of water quality constituent, and withdrawal flux. Sometimes, selective withdrawal capabilities can provide the operational flexibility to meet the water quality demands both in-reservoir and downstream. The objective of this study was to evaluate the performance of a one-dimensional reservoir selective withdrawal model (SELECT) as a tool for supporting downstream water quality management for Daecheong and Imha reservoirs. The simulated water quality variables including water temperature, dissolved oxygen (DO), conductivity, turbidity were compared with the field data measured in tailwater. The model showed fairly satisfactory results and high reliability in simulating observations. The coefficients of determinant between simulated and observed turbidity values were 0.93 and 0.95 for Daecheong and Imha reservoirs, respectively. The outflow water quality was significantly influenced by water intake level under fully stratified condition, while the effect of intake amount was minor. In conclusion, the SELECT is simple but effective tool for supporting downstream water quality prediction and management for both reservoirs.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.4
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• pp.87-92
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• 2007

The full automation welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this paper, an attempt has been made to develop an neural network model to predict the weld top-bead height as a function of key process parameters in the welding. and to compare the developed models using three different training algorithms in order to select an adequate neural network model for prediction of top-bead height.

• Ocean Systems Engineering
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• v.6 no.4
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• pp.305-324
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• 2016

Wave load prediction at zero forward speed using finite depth Green function is a well-established method regularly used in the offshore and marine industry. The forward speed approximation in deep water condition, although with limitations, is also found to be quite useful for engineering applications. However, analysis of vessels with forward speed in finite water depth still requires efficient computing methods. In this paper, a method for analysis of wave induced forces and corresponding motion on freely floating three-dimensional bodies with low to moderate forward speed is presented. A finite depth Green function is developed and incorporated in a 3D frequency domain potential flow based tool to allow consideration of finite (or shallow) water depth conditions. First order forces and moments and mean second order forces and moments in six degree of freedom are obtained. The effect of hull flare angle in predicting added resistance is incorporated. This implementation provides the unique capability of predicting added resistance in finite water depth with flare angle effect using a Green function approach. The results are validated using a half immersed sphere and S-175 ship. Finally, the effect of finite depth on a tanker with forward speed is presented.

• Ocean Systems Engineering
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• v.3 no.4
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• pp.295-307
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• 2013

More FOWTs (floating offshore wind turbines) will be installed as relevant regulations and technological hurdles are removed in the coming years. In the present study, a numerical prediction tool has been developed for the fully coupled dynamic analysis of FOWTs in time domain including aero-loading, tower elasticity, blade-rotor dynamics and control, mooring dynamics, and platform motions so that the influence of rotor-control dynamics on the hull-mooring performance and vice versa can be assessed. The developed coupled analysis program is applied to Hywind spar design with 5 MW turbine. In case of spar-type floaters, the control strategy significantly influences the hull and mooring dynamics. If one of the control systems fails, the entire dynamic responses of FOWT can be significantly different. Therefore, it is important to maintain various control systems in a good operational condition. In this regard, the effects of failed blade pitch control system on FOWT performance including structural and dynamic responses of blades, tower, and floater are systematically investigated. Through this study, it is seen that the failure of one of the blade pitch control system can induce significant dynamic loadings on the other blades and the entire FOWT system. The developed technology and numerical tool are readily applicable to any types of floating wind farms in any combinations of irregular waves, dynamic winds, and steady currents.

• Annual Conference of KIPS
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• 2011.04a
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• pp.230-233
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• 2011

Chronic disease is linked to patient's' lifestyle. Therefore, doctor has to monitor his/her patient over time. This may involve reviewing many reports, finding any changes, and modifying several treatments. One solution to optimize the burden is using a visualizing tool over time such as a timeline-based visualization tool where all reports and medicine are integrated in a problem centric and time-based style to enable the doctor to predict and adjust the treatment plan. This solution was proposed by Bui et. al. [2] to observe the medical history of a patient. However, there was limitation of studying the diabetes patient's history to find out what was the cause of the current development in patient's condition; moreover what would be the prediction of current implication in one of the diabetes' related factors (such as fat, cholesterol, or potassium). In this paper, we propose a Grid-based Interactive Diabetes System (GIDS) to support bioinformatics analysis application for diabetes diseases. GIDS used an agglomerative clustering algorithm as clustering correlation algorithm as primary algorithm to focus medical researcher in the findings to predict the implication of the undertaken diabetes patient. The algorithm was Chronological Clustering proposed by P. Legendre [11] [12].

• KOREAN JOURNAL OF CROP SCIENCE
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• v.55 no.4
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• pp.357-364
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• 2010

Kjeldahl method used in many materials from various plant parts to determine protein contents, is laborious and time-consuming and utilizes hazardous chemicals. Near-infrared (NIR) reflectance spectroscopy, a rapid and environmentally benign technique, was investigated as a potential method for the prediction of protein content. Near-infrared reflectance spectra(1100-2400 nm) of coarse cereal grains(n=100 for each germplasm) were obtained using a dispersive spectrometer as both of grain itself and flour ground, and total protein contents determined according to Kjeldahl method. Using multivariate analysis, a modified partial least-squares model was developed for prediction of protein contents. The model had a multiple coefficient of determination of 0.99, 0.99, 0.99, 0.96 and 0.99 for foxtail millet, sorghum, millet, adzuki bean and mung bean germplasm, respectively. The model was tested with independent validation samples (n=10 for each germplasm). All samples were predicted with the coefficient of determination of 0.99, 0.99, 0.99, 0.91 and 0.99 for foxtail millet, sorghum, millet, adzuki bean and mung bean germplasm, respectively. The results indicate that NIR reflectance spectroscopy is an accurate and efficient tool for determining protein content of diverse coarse cereal germplasm for nutrition labeling of nutritional value. On the other hands appropriate condition of cereal material to predict protein using NIR was flour condition of grains.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.2101-2108
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• 2008

Most of train fires which occur in usual cases do not grow up significantly on a large scale enough to bring about casualties and harmful damages. However, the consequence of some train fire accidents can be devastating disaster so that it would be even recorded in history in unusual cases. Accordingly, such a probability of fire disaster cannot be ignored in aspect of the railway safety assesment. A scale of injury and damage is very difficult to predict and analyze. Because it is depend on various factors, i.e. fire load, burning period, facilities, environment condition, and so on. Thus, a prediction of fire load could be understood as a one methodology to estimate railway safety assesment. The summation method which is one of them is used to evaluate the overall fire load by assuming that sum of heat release rate per unit area or mass of each composite material equals the total. However, since the train fire is classified into a compartment fire in under-ventilation condition. The summation method do not estimate a fire load completely. In this journal, Various methods to predict fire load are introduced and evaluated. Especially the fire simulation tool FDS(Fire Dynamics Simulator)which is based on the CFD(Computational Fluid Dynamics) is introduced, too. Through the FDS simulation, numerical analyses for the fire load and flame spread are performed. Then, these results of the simulation are validated through the comparison study with the experimental data. Then, limitations and approximations including in simulation process are discussed. The future direction of research is proposed.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.300-302
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• 2008

For the evaluation of wind resources, numerical simulation was carried out as a tool for establishing wind map around the korean peninsula. Initial and boundary condition are given by 3 hourly RDAPS(Regional Data Assimilation and Prediction System) data of KMA(Korea Meteorology Administration) and high resolution terrain elevation land cover(30 seconds) data from USGS(United States Geological Survey). Furthermore, Data assimilation was adopted to improve initial meteorological data with buoy and QuikSCAT seawinds data. The simulation was performed from 2003 to 2006 year. To understand wind data correctly in complex terrain as the korean peninsula, at this research, Wind map was classified 4 categories by distance from coastline and elevation.