• Journal of the Korean Geotechnical Society
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• v.20 no.8
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• pp.77-87
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• 2004

In this paper a back-propagation neural network model is developed to estimate the preconsolidation pressure of Korean soft soils based on 176 oedometer tests and 63 piezocone test results, which were compiled from 11 sites - western and southern parts of Korea. Only 147 data were used for the training of the neural network and 29 data, which were not used during the training phase, were used for the verification of trained network. Empirical and theoretical models were compared with the developed neural network model. A simple 4-4-9-1 multi-layered neural network has been developed. The cone tip resistance $q_T$ penetration pore pressure $u_2$, total overburden pressure $\sigma_{vo}$ and effective overburden pressure $\sigma'_{vo}$ were selected as input variables. The developed neural network model was validated by comparing the prediction results of the proposed neural network model for the new data which were not used for the training of the model with the measured preconsolidation pressures. It can also predict more precise and reliable preconsolidation pressures than the analytical and empirical model. Furthermore, it can be carefully concluded that neural network model can be used as a generalized model for prediction of preconsolidation pressure throughout Korea since developed model shows good performance for the new data which were not used in both training and testing data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.8 no.1
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• pp.87-95
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• 1988

In the arctic offshore regions, massive offshore gravity platforms are recommended to be construced because of severe environments. In such structures which is so large that its characteristic length is of the order of the wave length, wave-structure interaction problem has been solved using linear diffraction theory. Structural analysis of the large scale offshore structures requires wave force distribution along depth and wave pressure distribution on the body surface. In this study, existing computer program which calculates the total wave force acting on axisymmetric bodies has been modified to calculate wave force distribution along depth and wave pressure distribution on the body surface. Numerical results of pressure distribution for a fixed vertical cylinder obtained from this analysis has been compared with the results of an analytic solution of MacCamy-Fuchs, and good agreements has been obtained. It is desirable to use 6 in the case of analytic solution, and 5 in the case of numerical solution as the Fourier Mode of Green function. The results in this study are expected to be utilized for structural analysis such as pseudo-static analysis, dynamic analysis and fatigue analysis.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.1068-1072
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• 2005

조석이란, 해면의 완만한 주기적 승강을 말하며, 보통 그 승강은 1일 약 2회이나, 곳에 따라서는 1일 1회의 곳도 있다. 조석에 있어서는 이 밖에 수일의 주기를 갖는 약간 불규칙한 승강, 반년, 또는 1년을 주기로 하는 다소 규칙적인 승강까지 포함하여 취급한다. 그러나, 각 항만마다 갖는 특정적인 주기인 수분내지 수십분의 주기의 승강은 조석으로 취급하지 않는다. 조석은 해양의 제현상 중에서 예측가능성이 가장 큰 현장으로 이는 조석이 천체의 운행과 연관되기 때문이다. 조석이란 지구로부터 일정한 거리에서 각 고유의 속도를 가지는 적도상을 운행하는 무수의 가상천체에 기인하는 규칙적인 개개의 조석을 합성한 것이며 이 개개의 조석을 분조(Constituent)라 한다. 여기에서 사용되는 신경망 모형은 입력과 출력으로 구성되는 블랙박스 모형으로서 하나의 시스템을 병렬적으로 비선형적으로 구축할 수 있다는 장점 때문에 과거 하천유역의 강우-유출과정에서의 경우 유출현상을 해석하고 유출과정을 모형화 하기 위해 사용하였다. 본 연구에서는 기존의 조위 예측방법인 조화분석법이 아닌 인공신경망을 이용하여 조위예측을 실시하였다. 학습이라는 최적화 과정을 통해 구조와 기능이 복잡한 자연현상을 그대로 받아들여 축적시킴으로써 이를 지식으로 현상에 대한 재현능력이 뛰어나고, 또한 신경회로망의 연상기억능력에 적용하여 수학적으로 표현이 불가능한 불확실한 조위곡선에 적용하기에 유리한 장점을 가지고 있다. 본 연구의 목적은 과거 조위이론을 통해 이루었던 조위예측을 우리가 알기 쉬운 여러 기후인자(해면기압, 풍향, 풍속, 음력 등)에 따른 조위곡선을 예측하기 위해 신경망 모형을 이용하여 여수지역의 조위에 적용하여 비교 분석하고자 한다. May가 제안한 공식을 더 확장하여 적용할 수 있는 실험 공식으로 개선하였으며 다양한 조건에 대한 실험을 수행하여 보다 정밀한 공식으로 개선할 수 있었다.$10,924m^3/s$ 및 $10,075m^3/s$로서 실험 I의 $2,757m^3/s$에 비해 통수능이 많이 개선되었음을 알 수 있다.함을 알 수 있다. 상수관로 설계 기준에서는 관로내 수압을 $1.5\~4.0kg/cm^2$으로 나타내고 있는데 $6kg/cm^2$보다 과수압을 나타내는 경우가 $100\%$로 밸브를 개방하였을 때보다 $60\%,\;80\%$ 개방하였을 때가 더 빈번히 발생하고 있으므로 대상지역의 밸브 개폐는 $100\%$ 개방하는 것이 선계기준에 적합한 것으로 나타났다. 밸브 개폐에 따른 수압 변화를 모의한 결과 밸브 개폐도를 적절히 유지하여 필요수량의 확보 및 누수방지대책에 활용할 수 있을 것으로 판단된다.8R(mm)(r^2=0.84)$로 지수적으로 증가하는 경향을 나타내었다. 유거수량은 토성별로 양토를 1.0으로 기준할 때 사양토가 0.86으로 가장 작았고, 식양토 1.09, 식토 1.15로 평가되어 침투수에 비해 토성별 차이가 크게 나타났다. 이는 토성이 세립질일 수록 유거수의 저항이 작기 때문으로 생각된다. 경사에 따라서는 경사도가 증가할수록 증가하였으며 $10\% 경사일 때를 기준으로 $Ro(mm)=Ro_{10}{\times}0.797{\times}e^{-0.021s(\%)}$로 나타났다.천성 승모판 폐쇄 부전등을 초래하는 심각한 선

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.19-24
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• 2020

The interest in renewable energy is increasing due to the depletion of fossil fuels. In particular, active research on wave power, which is highly predictable and abundant, is being conducted. The coaxial accelerator-type wave power generator used in this study was designed to improve the power generation efficiency by converting bidirectional linear motion into a rotational force. In an offshore engineering basin, waves were generated, and case tests were performed according to the wave period and wave height. The experimental results were verified by the theoretical method related to the frequency response, and the overall trend was confirmed to be consistent. These results are expected to be useful in estimating the power of wave generators and designing parameters to improve the efficiency of wave energy in the design stage before manufacturing. In addition, the manufacturer can predict the wave energy efficiency of wave generators, which can reduce the development time and cost by preventing trial and error processes.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.1
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• pp.1-8
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• 2010

The Fourier series uses a vibrating wave that possesses an amplitude that is like the one of the sine curve. Therefore, the functions used in the Fourier series do not change due to the value of the frequency and that set a limit to express irregular signals with rapid oscillations or with discontinuities in localized regions. However, the wavelet series analysis(WSA) method supplements these limits of the Fourier series by a linear combination of a suitable number of wavelets. By using the wavelet that is focused on time, it is able to give changes to the range in the cycle. Also, this enables to express a signal more efficiently that has singular configuration and that is flowing. The main objective of this study is to propose a scheme called wavelet series analysis for the application of wavelet theory to one-dimensional problems represented by the second-order elliptic equation and to evaluate theperformance of proposed scheme comparing with the finite element analysis. After a through evaluation of different types of wavelets, the HAT wavelet system is chosen as a wavelet function as well as a scaling function. It can be stated that the WSA method is as efficient as the FEA method in the case of axial bars with distributed loads, but the WSA method is more accurate than the FEA method at the singular points and its computation time is less.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.11
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• pp.828-833
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• 2018

It is well known that reflected waves and resonance affect phase distortion. In addition, phase delay can be distorted by antenna impedance. In this study, we analyze the phase delay variation caused by the antenna impedance, considering mutual coupling effects. In addition, we confirm the beam steering characteristics. When was -10 dB and -7 dB, the maximum phase delay error was $18.5^{\circ}$ and $26.5^{\circ}$, respectively. The Monte Carlo simulation with an eight-element linear array antenna demonstrated that the RMS error of the beam steering angle ranged from $0.19^{\circ}$ to $0.4^{\circ}$, and the standard deviation ranged from $0.14^{\circ}$ to $0.33^{\circ}$ when the beam steering angle was in the range of $0^{\circ}$ to $30^{\circ}$, with the uniformly distributed phase error of $18.5^{\circ}$ and $26.5^{\circ}$. The side lobe level increased from 0.74 dB to 1.21 dB by the phase error from the theoretical value of -12.8 dB, with a standard deviation of 0.31 dB to 0.51 dB. This is verified by designing an eight-element spiral array antenna.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6B
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• pp.597-603
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• 2006

The purpose of this study is to improve the short term rainfall forecast skill using neural network model that can deal with the non-linear behavior between satellite data and ground observation, and minimize the flood damage. To overcome the geographical limitation of Korean peninsula and get the long forecast lead time of 3 to 6 hour, the developed rainfall forecast model took satellite imageries and wide range AWS data. The architecture of neural network model is a multi-layer neural network which consists of one input layer, one hidden layer, and one output layer. Neural network is trained using a momentum back propagation algorithm. Flood was estimated using rainfall forecasts. We developed a dynamic flood inundation model which is associated with 1-dimensional flood routing model. Therefore the model can forecast flood aspect in a protected lowland by levee failure of river. In the case of multiple levee breaks at main stream and tributaries, the developed flood inundation model can estimate flood level in a river and inundation level and area in a protected lowland simultaneously.