• Structural Engineering and Mechanics
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• 제23권2호
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• pp.177-193
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• 2006

Determining the hysteretic energy demand and dissipation capacity and level of damage of the structure to a predefined earthquake ground motion is a highly non-linear problem and is one of the questions involved in predicting the structure's response for low-performance levels (life safe, near collapse, collapse) in performance-based earthquake resistant design. Neural Network (NN) analysis offers an alternative approach for investigation of non-linear relationships in engineering problems. The results of NN yield a more realistic and accurate prediction. A NN model can help the engineer to predict the seismic performance of the structure and to design the structural elements, even when there is not adequate information at the early stages of the design process. The principal aim of this study is to develop and test multi-layered feedforward NNs trained with the back-propagation algorithm to model the non-linear relationship between the structural and ground motion parameters and the hysteretic energy demand in steel moment resisting frames. The approach adapted in this study was shown to be capable of providing accurate estimates of hysteretic energy demand by using the six design parameters.

• International Journal of Naval Architecture and Ocean Engineering
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• 제13권1호
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• pp.292-305
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• 2021

The present study concerns uncertainty assessment of powering prediction from towing tank model tests, suggested by the International Towing Tank Conference (ITTC). The systematic uncertainty of towing tank tests was estimated by allowance of test setup and measurement accuracy of ITTC. The random uncertainty was varied from 0 to 8% of the measurement. Randomly generated inputs of test conditions and measurement data sets under systematic and random uncertainty are used to statistically analyze resistance and propulsive performance parameters at the full scale. The error propagation through an extrapolation procedure is investigated in terms of the sensitivity and coefficient of determination. By the uncertainty assessment, it is found that the uncertainty of resultant powering prediction was smaller than the test uncertainty.

• Geomechanics and Engineering
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• 제20권5호
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• pp.385-397
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• 2020

This paper presents an application of artificial neural networks (ANNs) in settlement prediction of a foundation on sandy soil. In order to train the ANN model, a wide experimental database about settlement of foundations acquired from available literatures was collected. The data used in the ANNs model were arranged using the following five-input parameters that covered both geometrical foundation and sandy soil properties: breadth of foundation B, length to width L/B, embedment ratio D_f/B, foundation net applied pressure q_net, and average SPT blow count N. The backpropagation algorithm was implemented to develop an explicit predicting formulation. The settlement results are compared with the results of previous studies. The accuracy of the proposed formula proves that the ANNs method has a huge potential for predicting the settlement of foundations on sandy soils.

• 한국음향학회지
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• 제16권4호
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• pp.29-34
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• 1997

원거리에서 수동소나에 의한 탐지거리를 예측하기 위해서는 소나방정식이 이용된다. 본 연구에서는 거리와 깊이함수의 신호이득 및 탐지확률을 구한 후 이를 거리로 적분하여 거리의존 해양환경에서 탐지거리를 계산하는 탐지거리 예측모델을 개발하였다. 개발된 모델은 기존에 발표된 거리독립 해양환경에서의 결과와 비교하여 검증하였고, 이를 바탕으로 거리의존 해양환경에서 수동소나에 의한 표적탐지에 큰 영향을 주는 난수성 소용돌이 해양환경에 확장 적용하여 표적의 탐지거리를 예측하였으며, 그 결과에 대하여 소개한다.

• 비파괴검사학회지
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• 제28권3호
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• pp.245-253
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• 2008

A precise description of the material is a key point to obtain reliable results when using wave propagation codes. In the case of multipass welds, the material is very difficult to describe due to its anisotropic and heterogeneous properties. Two main advances are presented in the following. The first advance is a model which describes the anisotropy resulting from the metal solidification and thus the model reproduces an anisotropy that is correlated with the grain orientation. The model is called MINA for modelling anisotropy from Notebook of Arc welding. With this kind of material model1ing a good description of the behaviour of the wave propagation is obtained, such as beam deviation or even beam division. But another advance is also necessary to have a good amplitude prediction: a good quantification of the attenuation, particularly due to grain scattering, is also required as far as attenuation exhibits a strong anisotropic behaviour too. Measurement of attenuation is difficult to achieve in anisotropic materials. An experimental approach has been based both on the decomposition of experimental beams into plane waves angular spectra and on the propagation modelling through the anisotropic material via transmission coefficients computed in generally triclinic case. Various examples of results are showed and also some prospects to continue refining numerical simulation of wave propagation.

• 한국해안해양공학회지
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• 제4권1호
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• pp.18-25
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• 1992

임의의 수심 및 흐름상의 풍파에 대한 성장, 박파 및 감쇠에 대한 이산형 스펙트럼 모형을 구성하였다. 변화되는 수심 및 흐름으로 인한 절대주파수의 변화를 포함한 파낭과 흐름간의 상호작용을 고려하였고 함장 및 감쇠과정은 Inoue의 방법을 사용했다. 전파기법은 2차의 정도를 가지며 굴절과 수심 및 흐름으로 인한 주파수의 변위도 2차의 기법을 사용하여 고정 격자에서 계산하였다.

• 대한토목학회논문집
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• 제28권5B호
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• pp.485-493
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• 2008

한반도 영역을 대상으로 RDAPS모형의 수치예보자료, AWS의 관측강수, 상층기상관측(upper-air sounding)의 관측자료를 이용하여 권역별 강수발생확률을 예측할 수 있는 인공신경망 모형을 제시하였다. 사용된 자료의 기간은 2001년 7, 8월과 2002년 6월로 홍수기를 대상으로 하였다. 500/750/1000 hPa에서의 지위고도, 500-1000 hPa에서의 층후(thickness), 500 hPa에서의 X와 Y방향 바람성분, 750 hPa에서의 X와 Y방향 바람성분, 표면풍속, 500/750 hPa/표면에서의 온도, 평균해면기압, 3시간 누적 강수, AWS관측소에서 관측된 RDAPS모형 실행전의 6시간과 12시간동안의 누적강수, 가강수량, 상대습도등을 신경망의 예측인자로 사용하였다. 신경망의 구조는 3층 MLP(Multi Layer Perceptron)로 구성하여 역전파알고리즘(Back-propagation)을 학습방법으로 사용하였다. 신경망예측결과 한반도전체에 대한 예측성과의 개선은 H가 6.8%상승하였고, 특히 TS와 POD는 각각 99.2%와 148.1% 상승함으로서 강수예측에 대한 신경망모형이 효과적인 도구가 될 수 있음을 확인하였다. KSS 역시 92.8% 개선됨으로서 RDAPS 예측에 비하여 뚜렷이 개선된 결과를 보여주고 있다.

• 한국컴퓨터산업학회논문지
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• 제3권5호
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• pp.547-556
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• 2002

본 논문은 MLP 모델과 전파 특성 파라미터를 이용하여 실내환경에서 무선근거리통신망에 대한 전파 경로 손실 예측 알고리듬을 제안하였다. 100mW의 송신출력과 2.4GHz의 주파수를 갖는 무선근거리통신망에 대한 실내 경로손실을 예측하고 측정된 값과 비교하였다. 비교된 측정값과 예측값 사이의 차이는 다양한 경로손실 요인들에 대한 정확한 분석을 통하여 감소시킬 수 있다. 제안된 전파 경로 손실 예측 모델을 이용하여 특정 실내환경에서의 AP 위치를 선정함으로써 최적 셀 설계를 수행하였다.

• 한국항해항만학회지
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• 제45권5호
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• pp.231-237
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• 2021

Enhancing the performance of maritime wireless communication has been highlighted by the issue of cell planning in the sea area because of lack of an appropriate Propagation Loss Model (PLM). To resolve the cell planning issue in vast sea areas, it was essential to develop the (PLM) matching the intended sea area. However, there were considerable gaps between the prediction of legacy PLMs and field measurement in propagation loss and there was a need to develop the adjusted PLM (A-PLM). Therefore, cell planning was performed on this adjusted model, including modification of the base station's location, altitude, and antenna azimuth to meet the quality objectives. Furthermore, in order to verify the availability of the cell planning, Communication Service Quality Monitoring System (CS-QMS) was developed in the LTE-Maritime project to collect LTE signal quality information from the onboard equipment at regular intervals and to ensure that the service quality was high enough to satisfy the goals in each designated grid. As a result of verification, the success rate of RSRP was 95.7% for the intensive management zone (IMZ) and 96.4% for the interested zone (IZ), respectively.

• 한국군사과학기술학회지
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• 제23권2호
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• pp.159-167
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• 2020

In actual battlefield environment, IFF radar plays an important role in distinguishing friend or foe targets and assigning unique identification code to management. Performance of IFF radar is greatly affected by radio environment including atmosphere and terrain, target maneuvering and operation mode. In this paper, M&S tool is consisted of interrogator(IFF radar) and answering machine(target) for radar performance analysis. The wave propagation model using APM(Advanced Propagation Model) and radar actuator system were modeled by considering beam waveform of individual operation beam mode. Using this tool, IFF radar performance was analyzed through two experimental results. As a result, it is expected that performance of IFF radar can be predicted in the operational environment by considering target maneuvering and operation beam mode.