Nowadays, the challenge in hydraulic turbine design is
the multi-objective design of turbine runner to reach higher
efficiency. The hydraulic performance of a turbine is strictly depends
on runner blades shape. The present paper focuses on the application
of the multi-objective optimization algorithm to the design of a small
Francis turbine runner. The optimization exercise focuses on the
efficiency improvement at the best efficiency operating point (BEP)
of the GAMM Francis turbine. A global optimization method based
on artificial neural networks (ANN) and genetic algorithms (GA)
coupled by 3D Navier-Stokes flow solver has been used to improve
the performance of an initial geometry of a Francis runner. The
results show the good ability of optimization algorithm and the final
geometry has better efficiency with initial geometry. The goal was to
optimize the geometry of the blades of GAMM turbine runner which
leads to maximum total efficiency by changing the design parameters
of camber line in at least 5 sections of a blade. The efficiency of the
optimized geometry is improved from 90.7% to 92.5%. Finally,
design parameters and the way of selection have been considered and
discussed.
[1] A. Demeulenaere, Ch. Hirsch,"Application of Multipoint Optimization
to the Design of Turbomachinery Blades," ASME Paper GT-2004-
53110.
[2] G.N. Vanderplaats, Numerical optimization techniques for engineering
design, McGraw-Hill, 1984.
[3] D.E. Goldberg, Genetic Algorithm, Addison Wesley, 1994.
[4] A. Demeulenaere, A. Purwanto, A. Ligout, C. Hirsch, R. Dijkers, F.
Visser, "Design and Optimization of an Industrial Pump: Application of
Genetic Algorithm and Neural Network," in Proc of insert Conf.
abbreviation, ASME Fluid Engineering Summer Conf., Houston, Texas,
June 2005.
[5] A. Alnaga, J.L. Kueny," Optimal Design of Hydraulic Turbine
Distributor," WSEAS Transactions on Fluid Mechanics, Issue 2, Volume
3, April 2008.
[6] J.L Kueny, R. Lestriez, A. Helali, and C. Hirsch, "Optimal design of a
small hydraulic turbine," 22nd IAHR Symposium on Hydraulic
Machinery and Systems, Stockholm, Sweden, 2004.
[7] H. Nilsson, L. Davidson, "A validation of parallel multiblock CFD
against the GAMM Francis water turbine runner at best efficiency and
off-design operating conditions," Int.rep.01/02, Dept. of Thermo and
Fluid Dynamics, Chalmers University of Technology, Gothen-burg,
2001.
[8] F. Avellan , P. Dupont , M. Farhat, B. Gindroz, P. Henry, M. Hussain, E.
Parkinson, O. Santal, "Flow survey and blade pressure measurements in
a Francis turbine model," Pejovic S. (ed) Proceedings of the 15th IAHR
Symposium on Hydraulic Machinery and Cavitation, Belgrade,
Yugoslavia, 1990, vol 2, I5, pp 1-14.
[9] S. Derakhshan, B. Mohammadi and A. Nourbakhsh, "Incomplete
Sensitivities for 3D Radial Turbomachinery Blade Optimization,"
Comput. Fluids, 37, pp. 1354-1363, 2008.
[10] S. Derakhshan, B. Mohammadi and A. Nourbakhsh, "Efficiency
Improvement of Centrifugal Reverse Pumps," Journal of Fluids
Engineering, Vol. 131, 021103-1-9, February 2009.
[1] A. Demeulenaere, Ch. Hirsch,"Application of Multipoint Optimization
to the Design of Turbomachinery Blades," ASME Paper GT-2004-
53110.
[2] G.N. Vanderplaats, Numerical optimization techniques for engineering
design, McGraw-Hill, 1984.
[3] D.E. Goldberg, Genetic Algorithm, Addison Wesley, 1994.
[4] A. Demeulenaere, A. Purwanto, A. Ligout, C. Hirsch, R. Dijkers, F.
Visser, "Design and Optimization of an Industrial Pump: Application of
Genetic Algorithm and Neural Network," in Proc of insert Conf.
abbreviation, ASME Fluid Engineering Summer Conf., Houston, Texas,
June 2005.
[5] A. Alnaga, J.L. Kueny," Optimal Design of Hydraulic Turbine
Distributor," WSEAS Transactions on Fluid Mechanics, Issue 2, Volume
3, April 2008.
[6] J.L Kueny, R. Lestriez, A. Helali, and C. Hirsch, "Optimal design of a
small hydraulic turbine," 22nd IAHR Symposium on Hydraulic
Machinery and Systems, Stockholm, Sweden, 2004.
[7] H. Nilsson, L. Davidson, "A validation of parallel multiblock CFD
against the GAMM Francis water turbine runner at best efficiency and
off-design operating conditions," Int.rep.01/02, Dept. of Thermo and
Fluid Dynamics, Chalmers University of Technology, Gothen-burg,
2001.
[8] F. Avellan , P. Dupont , M. Farhat, B. Gindroz, P. Henry, M. Hussain, E.
Parkinson, O. Santal, "Flow survey and blade pressure measurements in
a Francis turbine model," Pejovic S. (ed) Proceedings of the 15th IAHR
Symposium on Hydraulic Machinery and Cavitation, Belgrade,
Yugoslavia, 1990, vol 2, I5, pp 1-14.
[9] S. Derakhshan, B. Mohammadi and A. Nourbakhsh, "Incomplete
Sensitivities for 3D Radial Turbomachinery Blade Optimization,"
Comput. Fluids, 37, pp. 1354-1363, 2008.
[10] S. Derakhshan, B. Mohammadi and A. Nourbakhsh, "Efficiency
Improvement of Centrifugal Reverse Pumps," Journal of Fluids
Engineering, Vol. 131, 021103-1-9, February 2009.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:54090", author = "Sh. Derakhshan and A. Mostafavi", title = "Optimization of GAMM Francis Turbine Runner", abstract = "Nowadays, the challenge in hydraulic turbine design is
the multi-objective design of turbine runner to reach higher
efficiency. The hydraulic performance of a turbine is strictly depends
on runner blades shape. The present paper focuses on the application
of the multi-objective optimization algorithm to the design of a small
Francis turbine runner. The optimization exercise focuses on the
efficiency improvement at the best efficiency operating point (BEP)
of the GAMM Francis turbine. A global optimization method based
on artificial neural networks (ANN) and genetic algorithms (GA)
coupled by 3D Navier-Stokes flow solver has been used to improve
the performance of an initial geometry of a Francis runner. The
results show the good ability of optimization algorithm and the final
geometry has better efficiency with initial geometry. The goal was to
optimize the geometry of the blades of GAMM turbine runner which
leads to maximum total efficiency by changing the design parameters
of camber line in at least 5 sections of a blade. The efficiency of the
optimized geometry is improved from 90.7% to 92.5%. Finally,
design parameters and the way of selection have been considered and
discussed.", keywords = "Francis Turbine, Runner, Optimization, CFD", volume = "5", number = "11", pages = "2254-7", }