• 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.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.159-168
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• 2008

Since the term structure of interest rates (TSIR) has longitudinal data, we should consider as input variables both time left to maturity and time simultaneously to get a more useful and more efficient function estimation. However, since the resulting data set becomes very large, we need to develop a fast and reliable estimation method for large data set. Furthermore, it tends to overestimate TSIR because data are correlated. To solve these problems we propose a mixture of weighted least squares support vector machines. We recognize that the estimate is well smoothed and well explains effects of the third stock market crash in USA through applying the proposed method to the US Treasury bonds data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.519-526
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• 2016

As marine accidents happen frequently, it is required to establish a marine traffic monitoring system, which is designed to improve the safety and efficiency of navigation in VTS (Vessel Traffic Service). For this aim, recently, X-band marine radar is used for extracting the sea surface information and, it is necessary to retrieve wave information correctly and provide for the safe and efficient movement of vessel traffic within the VTS area. In this paper, three different current estimation algorithms including the classical least-squares (LS) fitting, a modified iterative least-square fitting routine and a normalized scalar product of variable current velocities are compared with buoy data and then, the iterative least-square method is modified to estimate wave information by improving the initial current velocity. Through several simulations with radar signals, it is shown that the proposed method is effective in retrieving the wave information compared to the conventional methods.

• Korean Journal of Agricultural Science
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• v.42 no.1
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• pp.53-61
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• 2015

Development of highly efficient and energy-saving tractors has been one of the issues in agricultural machinery. For design of such tractors, measurement and analysis of load on major power transmission parts of the tractors are the most important pre-requisite tasks. Objective of this study was to perform pre-processing procedures before effective analysis of load data of agricultural tractors (30, 75, and 82 kW) during major field operations such as plow tillage, rotary tillage, baling, bale wrapping, and to select the suitable pre-processing method for the analysis. A load measurement systems, equipped in the tractors, were consisted of strain-gauge, encoder, hydraulic pressure, and radar speed sensors to measure torque and rotational speed levels of transmission input shaft, PTO shaft, and driving axle shafts, pressure of the hydraulic inlet line, and travel speed, respectively. The entire sensor data were collected at a 200-Hz rate. Plow tillage, rotary tillage, baling, wrapping, and loader operations were selected as major field operations of agricultural tractors. Same or different farm works and driving levels were set differently for each of the load measuring experiment. Before load data analysis, pre-processing procedures such as outlier removal, low-pass filtering, and data division were performed. Data beyond the scope of the measuring range of the sensors and the operating range of the power transmission parts were removed. Considering engine and PTO rotational speeds, frequency components greater than 90, 60, and 60 Hz cut off frequencies were low-pass filtered for plow tillage, rotary tillage, and baler operations, respectively. Measured load data were divided into five parts: driving, working, implement up, implement down, and turning. Results of the study would provide useful information for load characteristics of tractors on major field operations.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.4
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• pp.490-496
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• 2012

The main object of this research is to minimize the shock effects which frequently result in fatal damage in offshore wind turbine on impact of barge. The collision between offshore wind turbine and barge is generally a complex problem and it is often impractical to perform rigorous finite element analyses to include all effects and sequences during the collision. On applying the impact force of a barge to the offshore wind turbine, the maximum acceleration, internal energy, and plastic strain are calculated for each load case using the finite element method. A parametric study is conducted with the experimental data in terms of the velocity of barge, thickness of the offshore wind turbine, and thickness and Mooney-Rivlin coefficient of the rubber fender. Through the analysis proposed in this study, it is possible to determine the proper size and material properties of the rubber fender and the optimal moving conditions of barge.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.123-130
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• 2007

The aim of this study was to propose a fusion and registration method with heterogeneous small animal acquisition system in small animal in-vivo study. After an intravenous injection of $^{18}F$-FDG through tail vain and 60 min delay for uptake, mouse was placed on an acryl plate with fiducial markers that were made for fusion between small animal PET (microPET R4, Concorde Microsystems, Knoxville TN) and Discovery LS CT images. The acquired emission list-mode data was sorted to temporally framed sinograms and reconstructed using FORE rebining and 2D-OSEM algorithms without correction of attenuation and scatter. After PET imaging, CT images were acquired by mean of a clinical PET/CT with high-resolution mode. The microPET and CT images were fusion and co-registered using the fiducial markers and segmented lung region in both data sets to perform a point-based rigid co-registration. This method improves the quantitative accuracy and interpretation of the tracer.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1471-1481
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• 2014

This paper presents the new power dissipation model of individual switching device in a high-level modular multilevel converter (MMC), which can be mostly used in voltage sourced converter (VSC) based high-voltage direct current (HVDC) system and flexible AC transmission system (FACTS). Also, the voltage balancing method based on sorting algorithm is newly proposed to advance the MMC functionalities by effectively adjusting switching variations of the sub-module (SM). The proposed power dissipation model does not fully calculate the average power dissipation for numerous switching devices in an arm module. Instead, it estimates the power dissipation of every switching element based on the inherent operational principle of SM in MMC. In other words, the power dissipation is computed in every single switching event by using the polynomial curve fitting model with minimum computational efforts and high accuracy, which are required to manage the large number of SMs. After estimating the value of power dissipation, the thermal condition of every switching element is considered in the case of external disturbance. Then, the arm modeling for high-level MMC and its control scheme is implemented with the electromagnetic transient simulation program. Finally, the case study for applying to the MMC based HVDC system is carried out to select the appropriate insulated-gate bipolar transistor (IGBT) module in a steady-state, as well as to estimate the proper thermal condition of every switching element in a transient state.

• Journal of Power Electronics
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• v.19 no.6
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• pp.1505-1514
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• 2019

The permanent magnet synchronous motor (PMSM) is widely used in various fields and the proportional-integral (PI) controller is popular in PMSM control systems. However, the motor parameters are usually unknown, which can lead to a complicated PI controller design and poor performance. In order to design a PI controller with good performance when the motor parameters are unknown, a control algorithm based on stability margin is proposed in this paper. First of all, based on the mathematical model of the PMSM and the least squares (LS) method, motor parameters are estimated offline. Then based on the estimation values of the motor parameters, natural angular frequency and phase margin, a PI controller is designed. Performance indices including the natural angular frequency and the phase margin are used directly to design the PI controller in this paper. Scalar functions of the d-loop and the q-loop are selected. It can be seen that the designed controller parameters satisfy Lyapunov large scale asymptotic stability theory if the natural angular frequencies of the d-loop and the q-loop are large than 0. Experimental results show that the parameter estimation method has good accuracy and the designed PI controller proposed in this paper has good static and dynamic performances.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.2
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• pp.85-91
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• 2016

The most important factor in the structural design of ships and offshore structures operating in arctic region is ice load, which results from ice-structure interaction during the ice collision process. The mechanical properties of ice related to strength and failure, however, show very complicated aspect varying with temperature, volume fraction of brine, grain size, strain rate and etc. So it is nearly impossible to establish a perfect material model of ice satisfying all the mechanical characteristics completely. Therefore, in general, ice collision analysis was carried out by relatively simple material models considering only specific aspects of mechanical characteristics of ice and it would be the most significant cause of inevitable errors in the analysis. Especially, it is well-known that the most distinctive mechanical property of ice is high dependency on strain rate. Ice shows brittle attribute in higher strain rate while it becomes ductile in lower strain rate range. In this study, the simulation method of ice collision to ship hull using the nonlinear dynamic FE analysis was dealt with. To consider the strain rate effects of ice during ice-structural interaction, strain rate dependent constitutive model in which yield stress and hardening behaviors vary with strain rate was adopted. To reduce the huge amount of computing time, the modeling range of ice and ship structure were restricted to the confined region of interest. Under the various scenario of ice-ship hull collision, the structural behavior of hull panels and failure modes of ice were examined by nonlinear FE analysis technique.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.4
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• pp.159-176
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• 2023

The conservation of the raccoon dog (Nyctereutes procyonoides) in South Korea requires the protection and preservation of natural habitats while additionally ensuring coexistence with human activities. Applying habitat map modeling techniques provides information regarding the distributional patterns of raccoon dogs and assists in the development of future conservation strategies. The purpose of this study is to generate potential habitat distribution maps for the raccoon dog in South Korea using geospatial technology-based models. These models include the frequency ratio (FR) as a bivariate statistical approach, the group method of data handling (GMDH) as a machine learning algorithm, and convolutional neural network (CNN) and long short-term memory (LSTM) as deep learning algorithms. Moreover, the imperialist competitive algorithm (ICA) is used to fine-tune the hyperparameters of the machine learning and deep learning models. Moreover, there are 14 habitat characteristics used for developing the models: elevation, slope, valley depth, topographic wetness index, terrain roughness index, slope height, surface area, slope length and steepness factor (LS factor), normalized difference vegetation index, normalized difference water index, distance to drainage, distance to roads, drainage density, and morphometric features. The accuracy of prediction is evaluated using the area under the receiver operating characteristic curve. The results indicate comparable performances of all models. However, the CNN demonstrates superior capacity for prediction, achieving accuracies of 76.3% and 75.7% for the training and validation processes, respectively. The maps of potential habitat distribution are generated for five different levels of potentiality: very low, low, moderate, high, and very high.