Open Access
Issue
E3S Web Conf.
Volume 220, 2020
Sustainable Energy Systems: Innovative Perspectives (SES-2020)
Article Number 01067
Number of page(s) 6
DOI https://doi.org/10.1051/e3sconf/202022001067
Published online 16 December 2020
  1. P. Lampart, S. Yershov, 3D optimization of turbomachinery blading, TASK Quarterly, 6 (1) (2002) [Google Scholar]
  2. R. Eisinger, A. Ruprecht, Automatic shape optimization of hydro turbine components based on CFD, TASK Quarterly, 6 (1) (2002). [Google Scholar]
  3. R.A. Van den Braembussche, Turbomachinery component design by means CFD, TASK Quarterly, 6, (1) (2002). [Google Scholar]
  4. I.F. Lobareva, V.A. Skorospelov, et al. On one approach to optimizing the shape of a hydraulic turbine bladem, Computational technologies, 10, (6) (2005). [Google Scholar]
  5. I.F. Lobareva, S.G. Cherny, D.V. Chirkov et al. Multi-criterial optimization of the hydraulic turbine blade shape, Computational technologies, 11 (5) (2006). [Google Scholar]
  6. A. Alnaga, et. al. Optimal Design of Hydraulic Turbine Distributor, WSEAS Transactions on Fluid Mechanics, 2008, 3, (2). Georgopoulou H.A., Kyriacou S.A., Giannakoglou K.C, Grafenberger P., Parkinson E. Constrained Multi-Objective Design Optimization of Hydraulic Components Using a Hierarchical Metamodel Assisted Evolutionary Algorithm. Part 1: Theory. − Proceedings of IAHR 24th Symposium on Hydraulic Machinery and Systems (Brazil, Foz do Iguassu, October 27-31), (2008). [Google Scholar]
  7. P. Grafenberger, E. Parkinson, H.A. Georgopoulou, S.A. Kyriacou, K.C. Giannakoglou, Constrained Multi-Objective Design Optimization of Hydraulic Components Using a Hierarchical Metamodel Assisted Evolutionary Algorithm. Part 2: Applications. − Proceedings of 24th IAHR Symposium (Brazil, Foz do Iguassu, October 27-31 (2008). [Google Scholar]
  8. D.V. Bannikov, S.G. Cherny, D. V. Chirkov et. al. Multimode optimization of the turnine impeller shape, Computational technologies, 14, (2) (2009). [Google Scholar]
  9. J.H. Kim, H.G. Choi, Performance enhancement of axial fan blade through multi-objective optimization techniques, Journal of Mechanical Science and Technology, 24 (10) (2010). [Google Scholar]
  10. L. Wang, The Optimal Design based on CFD combined with CAD for Turbine Runner. Journal of Software, 7 (8) (2012). [Google Scholar]
  11. A.V. Semenova, D.V. Chirkov, D.A. Skorospelov, Application of the method of multi-criterial optimization for designing the shape of the impeller blade of a Kaplan hydraulic turbine, Bulletin of the Samara Scientific Center of the Russian Academy of Sciences, 15 (4) (2013). [Google Scholar]
  12. F. Ayancik, U. Aradag, et. al. Hydroturbine Runner Design and Manufacturing. International Journal of Materials, Mechanics and Manufacturing, 1, (2) (2013). [Google Scholar]
  13. Y. Kawajiri, Y. Enomoto, S. Kurosawa, Design optimization method for Francis turbine. − Proceedings of 27th IAHR Symposium on Hydraulic Machinery and Systems IAHR 2014 (Montreal, Canada, 22-26 Sept.), (2014). [Google Scholar]
  14. D. Himmelblau, Applied nonlinear programming. Moskva. Mir Publisher (1975). [Google Scholar]
  15. S. Finikov, Differential geometry course. Moskva. KomKniga Publisher (2006). [Google Scholar]
  16. D. Rogers, J. Adams, Mathematical foundations of computer graphics. Moskva. Mir Publisher (2001). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.