DOI QR코드

DOI QR Code

Design Optimization of a High Specific Speed Francis Turbine Using Multi-Objective Genetic Algorithm

  • Nakamura, Kazuyuki (Rotating Machine Technology R&D Department, TOSHIBA Corporation) ;
  • Kurosawa, Sadao (Rotating Machine Technology R&D Department, TOSHIBA Corporation)
  • Received : 2008.10.23
  • Accepted : 2009.03.27
  • Published : 2009.06.01

Abstract

A design optimization system for Francis turbine was developed. The system consists of design program and CFD solver. Flow passage shapes are optimized automatically by using the system with Multi-Objective Genetic Algorithm (MOGA). In this study, the system was applied to a high specific speed Francis turbine (nSP = 250m-kW). The runner profile and the draft tube shape were optimized to decrease hydraulic losses. As the results, it was shown that the turbine efficiency was improved in wide operating range, furthermore, the height of draft tube was reduced with the hydraulic performance kept.

Keywords

References

  1. Manfred, S. et al. “The design of Francis Turbine Runners by 3D Euler Simulations Coupled to a Breeder Genetic Algorithm,”Proceedings of 20th IAHR Symposium, Aug. 2000.
  2. Kanzaki, M. et al. “The Design Optimization of Intake/Exhaust Performance of a Car Engine Using MOGA,” Proceedings ofEUROGEN 2001, Athens, Sept. 2001.
  3. Matsuo, A. et al. “Turbine Airfoil Optimization by Genetic Algorithm,” Proceedings of 7th Asian International Conference onFluid Machinery, Fukuoka, Oct. 2003.
  4. Kurosawa, S. et al. “Design Optimization of a Francis Turbine Runner using Multi-Objective Genetic Algorithm,” Proceedingsof 22nd IAHR Symposium, Stockholm, June 2004.
  5. Nagafuji, T. et al. “Navier-Stokes Prediction on Performance of a Francis Turbine with High Specific Speed,” Proceedings of3rd ASME/JSME Joint Fluids Engineering Conference, San Francisco, July 1999.

Cited by

  1. Simulation-based design and optimization of Francis turbine runners by using multiple types of metamodels vol.231, pp.8, 2017, https://doi.org/10.1177/0954406216658078
  2. Multi-objective shape optimization of a hydraulic turbine runner using efficiency, strength and weight criteria vol.58, pp.2, 2018, https://doi.org/10.1007/s00158-018-1914-6