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간접냉각이 이용된 지중송전케이블의 적정냉각조건에 관한 연구
박만흥,최규식,서정윤,김재근,이재헌,Park, M.H,Che, G.S.,Seo, J.Y.,Kim, J.G.,Lee, Jae-Heon 대한설비공학회 1992 설비공학 논문집 Vol.4 No.4
The transmission current in a power cable is determined under the condition of separate pipe cooling. To this end, the thermal analysis is conducted with the standard condition of separate pipe cooling system, which constitutes one of the underground power transmission system. The changes of transmission current in a power cable with respect to the variation of temperatures and flow rates of inlet cooling water as well as the cooling spans are also determined. As a consequnce, the corresponding transmission current is shown to vary within allowable limit, resulting in the linear variation of the current for most of the cable routes. The abrupt changes of current, however, for the given flow rate of inlet cooling water in some cooling span lead to the adverse effects on the smooth current transmission within the underground power transmission system. In practice, it is expected that the desinging of the separate pipe cooling system in conjunction with the evaluation of system capacity should take into account the effects of design condition on the inlet cooling flow rate.
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박만흥,김재근,이재헌,Park, M.H.,Kim, J.K.,Lee, J.H. 대한설비공학회 1993 설비공학 논문집 Vol.5 No.4
Recently, underground transmission system is growing continuously according to the electric power demand increase in the downtown area. Even if domestic cable makers are manufacturing 154kV oil filled cable and joint, the design technology of cable-joint has not been fully self-reliance. This study is aimed at the detail heat transfer analysis of 154kV cable-joint. So, that is cut into the five sections in order to analyze a conjugate natural convection in two dimensional $r-{\theta}$ coordinate. The streamline and temperature distributions are obtained for each sections. Also the changes of those are analyzed with respect to the variation of transmission currents and cable-joint surface heat transfer coefficients. The same analyses are also shown in view point of the maximum temperature of conductor and local equivalent conductivity.
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박만흥,김광추,이승철 대한설비공학회 2006 설비공학 논문집 Vol.18 No.7
A variety of schemes were sought for a mitigation of thermal stratification phenomenon in the branch piping of domestic nuclear power plant. Several mechanisms of thermal stratification occurrence were introduced in this paper. A number of factors were selected to find out the schemes for thermal stratification mitigation and the computational analysis were performed. The length of vertical branch piping, the diameter, the radius of curvature of the elbow, the direction of connection between main piping and branch piping, the slope of branch piping, the leakage flow rate, the installation of additional valve, the change of the 1st valve position and another branch piping connected with branch piping were mentioned as factors in this paper.
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비행데이터 이미지 기반 Deep Learning을 통한 항공기 피로수명 예측
전병철(Byungchul Jeon),백세일(Seil Baek),김신곤(Sinkon Kim),이홍철(Hongchul Lee) 대한기계학회 2021 대한기계학회 춘추학술대회 Vol.2021 No.5
항공기는 설계/개발단계에서 주요 피로취약부위에 대해 예측 운영환경을 반영한 구조해석, 피로해석을 통해 안전성을 확보한다. 실제 운영환경은 설계와 다르게 운영되므로 군용 항공기는 실제 운영 상태의 비행데이터를 반영하여 피로수명 해석을 수행하고 있다. 일부 항공기는 비행데이터에서 직접 하중/응력 스펙트럼을 생성하고 피로수명 해석을 수행함으로써 장시간의 복잡한 계산 시스템을 필요로 한다. 본 연구에서는 항공기 비행 파라미터에 대한 이미지화 과정 및 Deep Learning 기계학습 적용을 통해 효과적이고 효율적인 피로수명 예측 방안을 제시하고자 한다. 비행 파라미터에 대한 이미지화 과정은 다차원의 대량 축적된 비행데이터에 대한 Deep Learning 적용 적합성 향상에 기여하였으며, 이러한 기계학습 과정을 통해 정확도가 유지된 상태에서 수명예측 시간 단축이 가능함을 확인하였다. In the aircraft design/development stage, flight safety is confirmed through structural analysis and fatigue analysis reflecting the predicted operating environment for fatigue critical locations. Since the actual environment is operated differently from the design, the military aircraft is performing fatigue analysis by reflecting flight data of actual operating conditions. Some aircraft require time consuming and complex calculation system by generating load/stress spectra directly from flight data and performing fatigue life analysis. In this study, we propose an effective and efficient fatigue life prediction method through the application of deep learning by imaging process for aircraft flight parameters. The process of imaging flight parameters contributed to the improvement of the suitability of deep learning application to multi-dimensional mass accumulated flight data, and it was confirmed that the fatigue life prediction can be shortened while maintaining accuracy through this deep learning process.
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