Abstract
A development and application of an automated optimization method for aerodynamic design of centrifugal impeller blades has been presented in this paper. A Non-uniform mutation and Pareto tournament and Fitness-sharing techniques based Multi-Objective Genetic Algorithm (MOGA) has been developed. The fast speed to convergence and well ability to search the Pareto front of the MOGA has been demonstrated through single-objective and multi-objective function tests. By introducing the MOGA, a three-dimensional reconstruction system for centrifugal impeller blades using non-uniform rational B-spline (NURBS) and a commercial software NUMECA, an aerodynamic automated optimization design system has been established. To a centrifugal impeller, the maximization of the absolute total pressure ratio and the isentropic efficiency has been taken as the design targets. The Pareto solutions have been obtained by using the present optimization technique. Through analysis and comparison the optimized design and the initial design, the validity and feasibility of the developed optimization design system is confirmed. The optimized results showed the performance of the optimized impeller has been improved.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
David E, Goldberg, 1989, “Genetic algorithms in search, optimization, and machine learning”, Addison-Wesley Pub. Co., Mass
Davis L, 1991, “Handbook of Genetic Algorithms”, Van Nostrand Reinhold, New York
De Jong, 1975, “An Analysis of the Behavior of a Class of Genetic Adaptive Systems”, University of Michigan
Eshelman L, J Schaffer, 1993, “Real-coded genetic algorithms and intervalschemata”, Foundations for Genetic Algorithms, vol.2, pp.187–202
FENG Zhen-ping, LI Jun, REN Bin, SONG Li-ming, 2003, “Evolutionary Computation in Aerodynamic Optimization Design”, THERMAL TURBINE, pp. 6–16
Giuseppe Briasco, Dario Bruna, Carlo Cravero, 2008, “A Nurbs-based Optimization Tool for Axial Compressor Cascade at Design and Off Design Conditions”, Proceedings of ASME Turbo Expo 2008, GT2008-50622
K Chiba, S Obayashi, K Nakahashi, 2006, “Design Exploration of Aerodynamic Wing Shape for Reusable Launch Vehicle Flyback Booster”, Journal of Aircraft, Vol.43, No. 3, pp. 832–836
Kalyanmoy Deb, Amrit Pratap, Sameer Agarwal, and T Meyarivan, 2002, “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II”, IEEE Transactions on Evolutionary Computation, Vol. 6, No. 2
Krain H, and Hoffman W, 1989, “Verification of an Impeller Design by Laser Measurements and 3D-Viscous Flow Calculations”, ASME Paper, 89-GT-159
Lakshminarayna B, 1991, “An Assessment of Computational Fluid Dynamic Techniques in the Analysis and Design of Turbomachinery”, Journal of Fluid Engineering, Transaction of the ASME, Vol.113
Mitsuo Gen, Runwei Cheng, 2000, “Genetic algorithms and engineering optimization”, Wiley-Interscience, New York
Obayashi S, Takanshi S, 1996, “Genetic optimization of target pressure distributions for inverse design method”, AIAA Journal, pp:881–886
Özhan ÖKSÜZ—brahim Sinan AKMANDOR, “Mnuti-objective Aerodynamic Optimization of Axial Turbine Blades using Novel multi-level Genetic Algorithm”, Proceedings of ASME Turbo Expo 2008, GT2008-50521
Tong Tong, Feng Zhen-ping, Li Jun, 1999, “on of gentic algorithm to multiobjective optimization design for turbine cascades”, Proceedings of the CSEE, Vol 19, No.6, pp. 74–77
WANG Xiao-peng, 2001, “Hybrid genetic algorithm and its application in multi-objective aerodynamic optimization design of airfoil”, ACTA Aerody Namica Sinica, Vol.19, No.3, pp. 256–261
XI Guang, 2000, “Discussion on the geometry and the secondary flow vortex structure of krain’s experimental compressor impeller”, Journal of engineering thermophysics, Vol.21, No.4, pp. 440–442
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Tsinghua University Press, Beijing and Springer-Verlag GmbH Berlin Heidelberg
About this paper
Cite this paper
Zhang, W., Liu, X. (2009). Multi-Objective Automated Optimization of Centrifugal Impeller Using Genetic Algorithm. In: Xu, J., Wu, Y., Zhang, Y., Zhang, J. (eds) Fluid Machinery and Fluid Mechanics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89749-1_17
Download citation
DOI: https://doi.org/10.1007/978-3-540-89749-1_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89748-4
Online ISBN: 978-3-540-89749-1
eBook Packages: EngineeringEngineering (R0)