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http://dx.doi.org/10.5139/JKSAS.2011.39.5.433

Optimization of a Centrifugal Compressor Impeller(II): Artificial Neural Network and Genetic Algorithm  

Choi, Hyoung-Jun (경상대학교 항공공학과 대학원)
Park, Young-Ha (경상대학교 항공공학과 대학원)
Kim, Chae-Sil (창원대학교 기계공학과)
Cho, Soo-Yong (경상대학교 항공기부품기술연구센터)
Publication Information
Journal of the Korean Society for Aeronautical & Space Sciences / v.39, no.5, 2011 , pp. 433-441 More about this Journal
Abstract
The optimization of a centrifugal compressor was conducted. The ANN (Artificial Neural Network) was adopted as an optimization algorithm, and it was learned and trained with the DOE (Design of Experiment). In the DOE, it was predicted the main effect and the interaction effect of design variables to the objective function. The ANN was improved in the optimization process using the GA (Genetic Algorithm). When any output at each generation was reached a standard level, it was re-calculated by the CFD (Computational Fluid Dynamics) and it was applied to develop a new ANN. After 6th generation, the prediction difference between ANN and CFD was less than 1%. A pareto of the efficiency versus the pressure ratio was obtained through the 21th generation. Using this method, the computational time for the optimization was equivalent to the time consumed by the gradient method, and the optimized results of multi-objective function were obtained.
Keywords
Centrifugal Compressor; ANN; GA; DOE; Impeller Optimization;
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Times Cited By KSCI : 1  (Citation Analysis)
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