Abstract
Fluent's built-in Latin hypercube sampling is used to generate a sample space, a total of 32 design points, a high-precision calculation model needs to be generated by CFD, the design parameters and their value ranges are determined, the response surface is used to establish a surrogate model, and the particle swarm optimization algorithm is used to obtain the optimal design parameters of the impeller with the pressure ratio and efficiency of the single-stage centrifugal compressor as the optimization goal, so as to achieve better performance of the impeller of the single-stage centrifugal compressor.
Publisher
Berger Scientific Press Limited
Reference5 articles.
1. Chen, D., Wu, H., Zhang, C. Analysis and research on main aerodynamic design parameters for impeller of centrifugal compressor. Chinese Journal of Turbomachinery, 2006, 3:1-4. https://doi.org/10.3969/j.issn.1006-8155.2006.03.001 (in Chinese)
2. Chen, X., Miao, Y. The compuation of intertnal flow fields in centrifugal compressor impellers. Journal of Engineering Thermophysics, 1992, 18(3): 277-281. (in Chinese)
3. Cortés, O., Urquiza, G., Hernández, J. A. Optimization of operating conditions for compressor performance by means of neural network inverse. Applied Energy, 2009, 86(11): 2487-2493. https://doi.org/10.1016/j.apenergy.2009.03.001
4. Bacak, A., Çolak, A. B., Dalkılıç, A. S. Investigating hermetic reciprocating compressor performance by using various machine learning methods. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2023, 09544062231213276 https://doi.org/10.1177/09544062231213276
5. Wu, D., Asl, B. B., Razban, A., Chen, J. Air compressor load forecasting using artificial neural network. Expert Systems with Applications, 2021, 168, 114209. https://doi.org/10.1016/j.eswa.2020.114209