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논문 기본 정보

자료유형
학술저널
저자정보
조수용 (경상대학교) 이영덕 (한국기계연구원) 안국영 (한국기계연구원) 김영철 (한국기계연구원)
저널정보
한국유체기계학회 한국유체기계학회 논문집 한국유체기계학회 논문집 제16권 제1호
발행연도
2013.2
수록면
11 - 16 (6page)

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초록· 키워드

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A numerical study was conducted to improve the performance of an impeller of centrifugal compressor. Nine design variables were chosen with constraints. Only meridional contours and blade profile were adjusted. ANN (Artificial Neural Net) was adopted as a main optimization algorithm with PSO (Particle Swarm Optimization) in order to reduce the optimization time. At first, ANN was learned and trained with the design variable sets which were obtained using DOE (Design of Experiment). This ANN was continuously improved its accuracy for each generation of which population was one hundred. New design variable set in each generation was selected using a non-gradient based method of PSO in order to obtain the global optimized result. After 7th generation, the prediction difference of efficiency and pressure ratio between ANN and CFD was less than 0.6%. From more than 1,200 design variable sets, a pareto of efficiency versus pressure ratio was obtained and an optimized result was selected based on the multi-objective function. On this optimized impeller, the efficiency and pressure ratio were improved by 1% and 9.3%, respectively.

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ABSTRACT
1. 서론
2. 최적화할 압축기 임펠러
3. 임펠러 설계변수
4. 최적화 기법
5. 목적함수
6. 최적화 과정 및 결과
7. 결론
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UCI(KEPA) : I410-ECN-0101-2014-554-000306892