• Geophysics and Geophysical Exploration
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• v.17 no.1
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• pp.21-27
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• 2014

We analyzed response patterns of test field data acquired with new small loop electromagnetic (EM) system using three-dimensional (3D) electromagnetic modeling code. The size and shape of a conductor was adopted as experimental parameters for EM modeling to understand influencing factors of the response patterns due to a metallic object on the seafloor. Obtaining the responses for four models of difference sizes and shapes through 3D EM modeling, we confirmed that the shape of the object have a more critical factor on the response pattern than size. We also calculated "ppm" values with respect to different altitudes of the sensor and source frequencies. The modeling results show that the consistency of sensor altitude is important and imaginary part of ppm response is more sensitive than real part. We also visualized the contour map of the real and imaginary part of ppm value as a function of frequency and altitude so that we can estimate proper altitude for source frequency band of our survey system. The results of this paper are anticipated to give proper parameters in survey construction for seafloor massive sulfide deposit.

• 한국지구물리탐사학회:학술대회논문집
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• 2009.10a
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• pp.75-80
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• 2009

Despite its flexibility to complex geometry, three-dimensional (3D) electromagnetic(EM) modeling schemes using finite element method (FEM) have been faced to practical limitation due to the resulting large system of equations to be solved. An efficient 3D FEM modeling scheme has been developed, which can adopt either direct or iterative solver depending on the problems. The direct solver PARDISO can reduce the computing time remarkably by incorporating parallel computing on multi-core processor systems, which is appropriate for single frequency multi-source configurations. When limited memory, the iterative solver BiCGSTAB(1) can provide fast and stable convergence. Efficient 3D simulations can be performed by choosing an optimum solver depending on the computing environment and the problems to be solved. This modeling includes various types of controlled-sources and can be exploited as an efficient engine for 3D inversion.

• Geophysics and Geophysical Exploration
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• v.20 no.4
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• pp.216-225
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• 2017

Recently, steel casing became an interesting issue when applying controlled-source electromagnetic (EM) method to various fields because effects of steel casing on EM responses are not negligible. This study employed an approach that approximates the steel casing as a series of electric dipole sources in order to develop the numerical algorithm for the efficient simulation of EM responses in the presence of steel casing. After verifying the validity of the developed algorithm, we analyze effects of steel casing on EM responses with the synthetic model simulating geothermal reservoir environment. The analysis showed that the effects of steel casing on EM responses are localized near the casing and increase as the transmitter becomes close to the casing. In addition, through the analysis on the EM responses by the injection of clean water, we confirm that the effects of casing are negligible when interpreting the after-injection data acquired using the transmitter located far enough from the casing. Considering the difference in EM responses between before and after injection in inversion, the effects of the casing can be neglected although after-injection data shows considerable difference due to the close distance between the transmitter and casing. To investigate this kind steel casing effect, the precise analysis on EM responses should be preceded. The algorithm introduced in this study will contribute to the reliable calculations of EM responses distorted by the conductive steel casing.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.2
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• pp.111-122
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• 2015

This study purposed on introducing a new automated solution for detecting railway tracks and reconstructing track models from the mobile laser scanning data. The proposed solution completes following procedures; the study initiated with detecting a potential railway region, called Region Of Interest (ROI), and approximating the orientation of railway track trajectory with the raw data. At next, the knowledge-based detection of railway tracks was performed for localizing track candidates in the first strip. In here, a strip -referring the local track search region- is generated in the orthogonal direction to the orientation of track trajectory. Lastly, an initial track model generated over the candidate points, which were detected by GMM-EM (Gaussian Mixture Model-Expectation & Maximization) -based clustering strip- wisely grows to capture all track points of interest and thus converted into geometric track model in the tracking by detection framework. Therefore, the proposed railway track tracking process includes following key features; it is able to reduce the complexity in detecting track points by using a hypothetical track model. Also, it enhances the efficiency of track modeling process by simultaneously capturing track points and modeling tracks that resulted in the minimization of data processing time and cost. The proposed method was developed using the C++ program language and was evaluated by the LiDAR data, which was acquired from MMS over an urban railway track area with a complex railway scene as well.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.7
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• pp.710-721
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• 2013

The noise prediction of motor driving system is one of the most important parts in EV/HEV, as the number of power electronic devices increases. This paper describes the mechanism of noise making process and proposes a simulation model of motor driving system for the prediction of the conducted noise. Theoretical calculations and model based simulations were carried out. DOD-dependent-battery parameters were extracted by AC analysis, and an inverter model including dynamic diode was used. Furthermore, 2-D EM tool was used for the motor modeling and was combined with the circuit models of battery and inverter. The simulated voltages, currents and spectrums in the motor driving system showed qualitatively meaningful results, suggesting the validness of the suggested modeling methods.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2049-2057
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• 2014

In this paper, a numerical method for analyzing coupling between high-altitude electromagnetic pulse (HEMP) as external field and a shielded twisted pair (STP) cable is proposed, which is based on an expanded chain matrix. Load responses of electromagnetic (EM) field excitation in uniform transmission line (TL) are solved by Baum-Liu-Tesche (BLT) equations in frequency domain, however, it is difficult to apply BLT equations to solve load responses of STP cable because the iteratively changing configuration of each twisted pairs are involved in cable. To avoid this problem and decrease memory and CPU time, we proposed the expanded chain matrix modeling method that is calculated using ABCD parameters, and applied multi-conductor transmission line (MTL) theory to consider the EMP coupling effectiveness of each twisted pairs. The results implemented by the proposed method are presented and compared with those obtained by the finite-difference time domain (FDTD) method as a kind of 3D full wave analysis.

• Geophysics and Geophysical Exploration
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• v.17 no.3
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• pp.129-136
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• 2014

Electromagnetic (EM) methods are generally divided into frequency-domain EM (FDEM) and time-domain EM (TDEM) methods, depending on the source waveform. The FDEM and TDEM fields are mathematically related by the Fourier transformation, and the TDEM field can thus be obtained as the Fourier transformation of FDEM data. For modeling in time-domain, we can use fast frequency-domain modeling codes and then convert the results to the time domain with a suitable numerical method. Thus, frequency-to-time transformations are of interest to EM methods, which is generally attained through fast Fourier transform. However, faster frequency-to-time transformation is required for the 3D inversion of TDEM data or for the processing of vast air-borne TDEM data. The diffusion expansion method (DEM) is one of smart frequency-to-time transformation methods. In DEM, the EM field is expanded into a sequence of diffusion functions with a known frequency dependence, but with unknown diffusion-times that must be chosen based on the data to be transformed. Especially, accuracy of DEM is sensitive to the diffusion-time. In this study, we developed a method to determine the optimum range of diffusion-time values, minimizing the RMS error of the frequency-domain data approximated by the diffusion expansion. We confirmed that this method produces accurate results over a wider time range for a homogeneous half-space and two-layered model.

• Journal of computational fluids engineering
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• v.11 no.2 s.33
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• pp.32-39
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• 2006

A heat dissipation modeling method of EEE parts is developed for thermal design and analysis of an satellite electronic equipment. The power consumption measurement value of each functional breadboard is used for the heat dissipation modeling method. For the purpose of conduction heat transfer modeling of EEE parts, surface heat model using very thin ignorable thermal plates is considered instead of conventional lumped capacity nodes. These modeling methods are applied to the thermal design and analysis of CTU EM and EQM and verified by thermal cycling and vacuum tests.

• 한국지구과학회:학술대회논문집
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• 2004.02a
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• pp.52-57
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• 2004

Korean Peninsula located between Japan and China where earthquakes frequently occur, have little geophysical observation despite its tectonic importance. This study suggests the inland conductive structures inferred from GDS data measured in Korean Peninsula and try to interpret induction arrows quantitatively with the aid of 2- and 3-D geomagnetic induction modeling. Ogcheon Belt (OCB) and Imjin River Belt (IRB) are regarded as main conductive structures in Korea Peninsula, the induction arrows for the period of 60 minutes show very weak anomaly due to sea effect, which is supported by the results of 3-modeling also. However, for the period of 10 minutes, induction arrows at YIN and ICHN show anomalous patterns considered as the effect of IRB in spite of sea effect. The results of 2-D modeling which simplify geological situations provide overall information on IRB

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.246-253
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• 2016

Infrared (IR) imaging has been researched for various applications such as surveillance. IR radiation has the capability to detect thermal characteristics of objects under low-light conditions. However, automatic segmentation for finding the object of interest would be challenging since the IR detector often provides the low spatial and contrast resolution image without color and texture information. Another hindrance is that the image can be degraded by noise and clutters. This paper proposes multi-level segmentation for extracting regions of interest (ROIs) and objects of interest (OOIs) in the IR scene. Each level of the multi-level segmentation is composed of a k-means clustering algorithm, an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering initializes the parameters of the Gaussian mixture model (GMM), and the EM algorithm estimates those parameters iteratively. During the multi-level segmentation, the area extracted at one level becomes the input to the next level segmentation. Thus, the segmentation is consecutively performed narrowing the area to be processed. The foreground objects are individually extracted from the final ROI windows. In the experiments, the effectiveness of the proposed method is demonstrated using several IR images, in which human subjects are captured at a long distance. The average probability of error is shown to be lower than that obtained from other conventional methods such as Gonzalez, Otsu, k-means, and EM methods.