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Fe 계열 이종 연자성 합금 분말을 함유한 폴리머 복합시트의 전파흡수특성
김상문(Sang-Mun Kim) 한국자기학회 2019 韓國磁氣學會誌 Vol.29 No.6
In this paper, we studied electromagnetic wave noise absorbing properties for quasi-microwave band with Fe-based magnetic composite sheet. The magnetic composite sheets were made of polymer and of soft magnetic FeSiCr flake powders and Fe80Ni flake powders with the thickness of about 0.5~1.0㎛. In the composite sheets for clarifying the mixing effect of two kind of the magnetic powders, the magnetic properties such as saturation magnetization and residual magnetization by use of VSM, and such as the complex permeability by impedance analyzer, and then the electromagnetic wave absorption properties and the shift of the matching frequency were investigated by Network Analyzer.
수계 상류 관측 수위자료를 이용한 하류 홍수위 예측기법
김상문(Sang Mun Kim),최병웅(Byungwoong Choi),이남주(Namjoo Lee) 응용생태공학회 2020 Ecology and resilient infrastructure Vol.7 No.4
최근 하천범람에 따른 피해를 최소화하기 위해서는 대피를 위한 선행시간을 확보하는 것이 매우 중요하다. 본 연구에서는 현재 하천에서 측정되고 있는 수위 관측 자료를 이용하여 이상호우 발생시 하류의 수위를 예측하였다. 수위 예측을 위해 다중회귀모형 및 인공신경망 모형을 섬강시험유역에 적용하였다. 다중회귀모형 및 인공신경망 모형의 학습에는 섬강시험유역의 2002년부터 2010년까지의 수위 관측 자료를 이용하였으며, 학습된 모형을 이용하여 발생 가능한 수위를 예측하였다. 모의 결과 인공신경망 수위예측모형의 결정계수는 0.991 - 0.999로 나타났으며, 다중회귀수위예측 모형의 결정계수는 0.945 - 0.990로 나타나 인공신경망을 이용한 수위예측모형이 다중회귀모형보다 좀 더 나은 예측 결과를 나타내는 것을 확인할 수 있었다. 본 연구결과는 향후 하천에서 선행시간을 확보한 홍수 예보 구축에 활용할 수 있을 것으로 판단된다. Securing the lead time for evacuation is crucial to minimize flood damage. In this study, downstream water levels for heavy rainfall were predicted using measured water level observation data. Multiple regression analysis and artificial neural networks were applied to the Seom River experimental watershed to predict the water level. Water level observation data for the Seom River experimental watershed from 2002 to 2010 were used to perform the multiple regression analysis and to train the artificial neural networks. The water level was predicted using the trained model. The simulation results for the coefficients of determination of the artificial neural network level prediction ranged from 0.991 to 0.999, while those of the multiple regression analysis ranged from 0.945 to 0.990. The water level prediction model developed using an artificial neural network was better than the multiple-regression analysis model. This technique for forecasting downstream water levels is expected to contribute toward flooding warning systems that secure the lead time for streams.
자기 Tape의 전자 변환 특성에 대한 자성분의 Size와 그 특성의 영향
김상문(Sang Mun Kim),김태옥(Tae Ok Kim) 한국자기학회 1996 韓國磁氣學會誌 Vol.6 No.5
In order to investigate the influence of the magnetic particle size and its properties on the particulate magnetic material, we evaluated the dispersion of magnetic particles and the electromagnetic properties in magnetic tape made from the magnetic paints by use of each magnetic particles witch were different from particle size and its properties. The dispersion of magnetic particles depends on the surface chemical properties rather than particle size. As particle size is smaller, the packing ratio of magnetic particle and the magnetic flux density in tape increase. The output levels in playing back of tape increase in wide frequency range from 315 ㎐ to 10 ㎑ and the noises decrease. It is very important to choose the size, the shape, the surface chemical properties and the magnetic properties of the magnetic particle in producing the high quality magnetic tape.