• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.4
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• pp.407-415
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• 2011

The stability condition and wideband characteristics of 3D ID-FDTD algorithm which has low dispersion error with isotropic dispersion are presented in this paper. 3D ID-FDTD method was proposed to improve the defect of the Yee FDTD such as the anisotropy and large dispersion error. The published paper calculated the stability condition of 3D ID-FDTD algorithm by using numerical method, however, it is thought that the examples were not sufficient to verify the stability condition. Thus, in this paper, various simulations are included in order to hold reliability under the conditions that the plane wave propagation is assumed with a single frequency and a wideband frequency. Also, the 3D ID-FDTD algorithm is compared to those that have the similar FDTD algorithm with ID-FDTD such as Forgy's method and non-standard FDTD method in a wideband. Finally, the radar cross section(RCS) for the large sphere with high dielectric constant is calculated.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.8 no.6
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• pp.665-680
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• 1997

The specific absorption rate (SAR) distributions in various models of the human head have been analyzed when the models are exposed to 350 MHz and 900 MHz plane waves. The numerical analysis is performed with the finite-difference time-domain (FDTD) method. A homogeneous sphere including a cylinderical neck, a homogeneous head shaped model, and a heterogeneous realistic model are used as models of human head. The incident plane wave used for these calculations is propagating from the front to the back or from the back to the front of the head model, with its E-field vector orientation being parallel to the major length of the body. The specific findings are: 1) the average SARs of the three models are similar mutually but the local SARs of them differ greatly mutually; 2) the power is deposed more deeply in the head at 350 MHz, which is roughly the resonant frequency of a human head, than at 900 MHz; 3) for a plane wave propagating from the back, "hot spot" is found in the neck region, not in the head; 4) for a plane wave propagating from the front, "hot spot" is found in the nose at 900 MHz, and in the upper part of the lip and the jaw region at 350 MHz.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.1
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• pp.98-105
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• 2013

This paper presents a finite-difference time-domain(FDTD) simulation and a data processing technique for radar sensing of the internal structure of a wall using an ultra-wide band antenna. We first designed an ultra-wide band anti-podal vivaldi antenna with a frequency range of 0.3~7 GHz which is chosen to be relatively low after considering the characteristics of wave attenuation, wall penetration, and range resolution. In this study the two-dimensional FDTD technique was used to simulate a wall-penetration-radar experiment under practical conditions. The next, the measured radiation pattern of the practical antenna is considered as an equivalent source in the FDTD simulation, and the reflection data of a concrete wall and targets are obtained by using the simulation. Then, a data processing technique has been applied to the FDTD reflection data to get a radar image for remote sensing of the internal structure of the wall. We compared the two different source excitations in the FDTD simulation; (1) commonly-used isotropic point sources and (2) polynomial curve fitting sources of the measured radiation pattern. As a result, when we apply the measured antenna pattern into the FDTD simulation, we could obtain about 2.5 dB higher signal to noise level than using a plane wave incidence with isotropic sources.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.4
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• pp.341-353
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• 2022

Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.3
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• pp.137-145
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• 2014

We present a design sensitivity analysis(DSA) method for multiscale problems based on bridging scale decomposition. In this paper, we utilize a bridging scale method for the coupled system analysis. Since the analysis of full MD systems requires huge amount of computational costs, a coupled system of MD-level and continuum-level simulation is usually preferred. The information exchange between the MD and continuum levels is taken place at the MD-continuum boundary. In the bridging scale method, a generalized Langevin equation(GLE) is introduced for the reduced MD system and the GLE force using a time history kernel is applied at the boundary atoms in the MD system. Therefore, we can separately analyze the MD and continuum level simulations, which can accelerate the computing process. Once the simulation of coupled problems is successful, the need for the DSA is naturally arising for the optimization of macro-scale design, where the macro scale performance of the system is maximized considering the micro scale effects. The finite difference sensitivity is impractical for the gradient based optimization of large scale problems due to the restriction of computing costs but the analytical sensitivity for the coupled system is always accurate. In this study, we derive the analytical design sensitivity to verify the accuracy and applicability to the design optimization of the coupled system.

• Tunnel and Underground Space
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• v.19 no.3
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• pp.203-212
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• 2009

The prediction of near field behavior around an underground high-level radioactive waste repository is important for the repository design as well as the safety assessment. In this study, a sensitivity analysis for seven parameters consisted of design parameters and material properties was carried out using a three-dimensional finite difference code. From the sensitivity analysis, it was found that the effects of borehole spacing, tunnel spacing, cooling time and rock thermal conductivity were more significant than the other parameters. For getting a statistical distribution of buffer and rock temperatures around the repository, an artificial neural network, backpropagation, was applied. The reliability of the trained neural network was tested with the cases with randomly chosen input parameters. When the parameter variation is within ${\pm}10%$, the prediction from the network was found to be reliable with about a 1% error. It was possible to calculate the temperature distribution for many cases quickly with the trained neural network. The buffer and rock temperatures showed a normal distribution with means of $98^{\circ}C$ and $83.9^{\circ}C$ standard deviations of $3.82^{\circ}C$ and $3.67^{\circ}C$, respectively. Using the neural network, it was also possible to estimate the required change in design parameters for reducing the buffer and rock temperatures for $1^{\circ}C$.

• The Korean Journal of Rheology
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• v.10 no.4
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• pp.217-226
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• 1998

The anisotropy caused by the fiber orientation, which is inevitably generated by the flow during injection molding of short fiber reinforced polymers, greatly influences dimensional accuracy, mechanical properties, and other quality of the final product. Since the filling stage of the injection molding process plays a vital role in determining fiber orientation, an accurate analysis of flow field for the filling stage is needed. Unbalanced filling occurs when a complex or a multi-cavity mold is used leading to development of regions where the fiber suspension is under compression. It is impossible to make an accurate calculation of the flow field during filling with the analysis assuming incompressible fluid. A mold with four cavities with different filling times was produced to compare the numerical analysis results with the experimental data. There was a good agreement between the experimental and theoretical results when the compressibility of the polymer melt was considered for the numerical simulation. The fiber orientation states for compressible and incompressible fluids were also compared qualitatively as well as quantitatively in this study.

• Journal of the Korean Geotechnical Society
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• v.32 no.4
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• pp.5-14
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• 2016

Numerical simulation of dynamic soil-pile-structure interaction embedded in a dry sand was carried out. 3D model of the dynamic centrifuge model tests was formulated in a time domain to consider nonlinear behavior of soil using the finite difference method program, FLAC3D. As a modeling methodology, Mohr-Coulomb criteria was adopted as soil constitutive model. Soil nonlinearity was considered by adopting the hysteretic damping model, and an interface model which can simulate separation and slip between soil and pile was adopted. Simplified continuum modeling (Kim et al., 2012) was used as boundary condition to reduce analysis time. Calibration process for numerical modeling results and test results was performed through the parametric study. Verification process was then performed by comparing numerical modeling results with another test results. Based on the calibration and validation procedure, it is identified that proposed modeling method can properly simulate dynamic behavior of soil-pile system in dry condition.

• Journal of the Korean Geotechnical Society
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• v.32 no.9
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• pp.51-62
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• 2016

Parametric studies for various site conditions by using 3d numerical model were carried out in order to estimate dynamic behavior of soil-pile-structure system in dry soil deposits. Proposed model was analyzed in time domain using FLAC3D which is commercial finite difference code to properly simulate nonlinear response of soil under strong earthquake. Mohr-Coulomb criterion was adopted as soil constitutive model. Soil nonlinearity was considered by adopting the hysteretic damping model, and an interface model which can simulate separation and slip between soil and pile was adopted. Simplified continuum modeling was used as boundary condition to reduce analysis time. Also, initial shear modulus and yield depth were appropriately determined for accurate simulation of system's nonlinear behavior. Parametric study was performed by varying weight of superstructure, pile length, pile head fixity, soil relative density with proposed numerical model. From the results of parametric study, it is identified that inertial force induced by superstructure is dominant on dynamic behavior of soil-pile-structure system and effect of kinematic force induced by soil movement was relatively small. Difference in dynamic behavior according to the pile length and pile head fixity was also numerically investigated.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.29-36
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• 2022

The importance of subsurface information is becoming crucial in urban area due to increase of underground construction. The position of underground facilities should be identified precisely before excavation work. Geophyiscal exporation method such as ground penetration radar (GPR) can be useful to investigate the subsurface facilities. GPR transmits electromagnetic waves to the ground and analyzes the reflected signals to determine the location and depth of subsurface facilities. Unfortunately, the readability of GPR signal is not favorable. To overcome this deficiency and automate the GPR signal processing, deep learning technique has been introduced recently. The accuracy of deep learning model can be improved with abundant training data. The ground is inherently heteorogeneous and the spacially variable ground properties can affact on the GPR signal. However, the effect of ground heterogeneity on the GPR signal has yet to be fully investigated. In this study, ground heterogeneity is simulated based on the fractal theory and GPR simulation is carried out by using gprMax. It is found that as the fractal dimension increases exceed 2.0, the error of fitting parameter reduces significantly. And the range of water content should be less than 0.14 to secure the validity of analysis.