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용민철(Minchul Yong),이권재(Kwonjae Lee),김청래(Cheongrae Kim),박찬정(Chanjung Park) 대한기계학회 2018 대한기계학회 춘추학술대회 Vol.2018 No.12
The human desire to drink clean water is increasing more and more. Todays, the market for direct water purifiers are increasing, not purifiered tank water. In recent years, the development of a cooling system has been actively conducted to make the purified water immediately drinkable. This paper is a more effective and efficient improvement of the ice storage cooling system that was conducted in 2017, and it deals with the study of optimizing the heat exchange between the ice storage and purifiered water.
분사노즐을 이용한 빙축수 순환방식과 주름관을 이용한 빙축열 냉각 시스템 구현
용민철(Minchul Yong),예병효(Byunghyo Ye),김청래(Cheongrae Kim),박찬정(Chanjung Park) 대한기계학회 2017 대한기계학회 춘추학술대회 Vol.2017 No.11
With the introduction of direct water purification system in water purifier, the necessity of cold water using instantaneous cooling method is emerging. The ice storage system was used in this study as a method of cooling purified water to below 10℃ through a filter. The circulation of the cooling water inside ice storage system was optimized by using the injection nozzle. A corrugated SUS tube was used to increase the cooling efficiency making cold water. Using the above technique, we developed a direct water purifier capable of realizing the lowest temperature.
유전자 알고리즘을 이용한 항공기용 가스터빈 엔진의 단일 결함 진단에 대한 연구
김승민(Seungmin Kim),용민철(Minchul Yong),노태성(Taeseong Roh),최동환(Dongwhan Choi) 한국항공우주학회 2007 韓國航空宇宙學會誌 Vol.35 No.3
유전자 알고리즘은 자연선택과 유전법칙을 적용하여 최적해를 탐색하는 방법으로, 본 연구에서 항공기용 가스터빈 엔진의 결함 진단을 위한 학습 알고리즘으로 사용되었다. 성능 저하를 고려한 구성요소는 압축기, 가스발생기 터빈, 동력 터빈이며, 설계점에서 엔진의 단일 구성요소에 대하여 각각 성능 저하 예측을 수행한 후, 이를 바탕으로 결함 진단을 수행하였다. 학습데이터 수의 증가가 유전자 알고리즘을 이용한 성능 저하 예측 및 결함 진단에 미치는 영향을 분석하였으며, 결과적으로 결함치에 대한 RMS 오차율이 모두 3% 이내로 예측됨을 확인하였다. Genetic Algorithms(GA) which searches optimum solution using natural selection and the law of heredity has been applied to learning algorithms in order to estimate performance deterioration of the aircraft gas turbine engine. The compressor, gas generator turbine and power turbine are considered for engine performance deterioration and estimation for performance deterioration of a single component at design point was conducted. As a result of that, defect diagnostics has been conducted. The input criteria for the genetic algorithm to guarantee the high stability and reliability was discussed as increasing learning data sets. As a result, the accuracy of defect estimation and diagnostics were verified with its RMS error within 3%.