Skip to main content
SpringerLink
Log in

An integrated blade optimization approach based on parallel ANN and GA with hierarchical fair competition dynamic-niche

  • Published:
Journal of Mechanical Science and Technology Aims and scope Submit manuscript

Abstract

This work presented an available multi-point blade optimization procedure for better aerodynamic performances. Based on the proposed Parallel ANN and GA with hierarchical fair competition dynamic-niche (GA-HFCDN), an integrated approach for the blade optimization design was put forward by combining Bezier parameterization with FINE/TURBO solver. In the optimization design, parallel ANN was employed to build a more proper approximate model. GA-HFCDN was proposed to obtain the global optimization solution more efficiently for the blade design. Two research cases, including plane cascades blade optimization and the optimization and experimental study of a low specific speed centrifugal blower blade, were performed by using the above approach. The conclusions showed the rationality and validity of the optimization approach.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. V. D. Casas, F. L. Pena and R. J. Duro, Automatic design and optimization of wind turbine blades, Proceedings of the International Conference on Computational Intelligence for Modeling Control and Automation (2006) 205–210.

  2. Y. Karam and H. M. N. Maalawi, Optimal frequency design of wind turbine blades, Journal of Wind Engineering and Industrial Aerodynamics, 90 (2002) 961–986.

    Article  Google Scholar 

  3. T. Sasaki and F. Breugelmans, Comparison of sweep and dihedral effects on compressor cascade performance, ASME Journal of Fluids Engineering, 120 (1998) 454–464.

    Google Scholar 

  4. S. Y. Lee and K. Y. Kim, Design optimization of axial flow compressor blades with three-dimensional Navier-Stokes Solver, KSME Int. J., 14 (2000) 1005–1012.

    Google Scholar 

  5. N. E. Sevant, M. I. Bloor and M. J. Wilson, Aerodynamic design of a flying wing using response surface methodology, J. Aircr., 37 (2000) 562–569.

    Article  Google Scholar 

  6. K. Y. Kim and S. S. Kim, Shape optimization of ribroughened surface to enhance turbulent heat transfer, Int. J. Heat Mass Transfer, 45 (2002) 2719–2727.

    Article  MATH  Google Scholar 

  7. C. S. Ahn and K. Y. Kim, Aerodynamic design optimization of an axial flow compressor using response surface methodology, Proceedings of the Institution of Mechanical Engineers, Part A: Journal of power and energy, 217 (2003) 179–184.

    Article  Google Scholar 

  8. K. S. Lee, K. Y. Kim and A. Samad, Design optimization of low-speed axial flow fan blade with three-dimensional RANS analysis, Journal of mechanical science and technology, 22 (2008) 1864–1869.

    Article  Google Scholar 

  9. K. Y. Kim and S. J. Seo, Application of numerical optimization technique to design of forward-curved blades centrifugal fan, JSME Int. J., 49(1) (2006) 152–158.

    Article  MathSciNet  Google Scholar 

  10. S. Y. Han and J. S. Maeng, Shape optimization of cutoff in a multiblade fan/scroll system using response surface methodology, Numerical Heat Transfer Part B, 42 (2004) 1–12.

    Google Scholar 

  11. A. Samad, Shape optimization of turbo-machinery blade using multiple surrogate models, ASME Joint-U.S.-European Fluids Engineering Summer Meeting, Miami, FL, USA, FEDSM 2006-98368 (2006).

  12. X. Shu, Ch. Gu, J. Xiao and C. Gao, Centrifugal compressor blade optimization based on uniform design and genetic algorithms, Front. Energy Power Eng. China, 2(4) (2008) 453–456.

    Article  Google Scholar 

  13. Yang, Li, Hua, Ouyang, Zhao-Hui and Du, Optimization design and experimental study of low-pressure axial fan with forward skewed blades, International Journal of Rotating Machinery, 1–10 (2007).

  14. Yang, Li, Hua, Ouyang, Zhao-Hui and Du, Experimental research on aerodynamic performance and exit flow field of low pressure axial flow fan with circumferential skewed blades, Journal of Hydrodynamics, Ser. B, 19(5) (2007) 579–586.

    Article  Google Scholar 

  15. R. B. Samuel, 3D computer graphics: A mathematical introduction with openGL [M], Cambridge University Press (England), (2003).

    Google Scholar 

  16. H. Yu, X. Yuan, Optimized aerodynamic design of multiblade rows of an axial compressor, Journal of Engineering for Thermal Energy and Power, 20(6) (2005) 603–606.

    MathSciNet  Google Scholar 

  17. FINETm, Numeca’s flow integrated environment, NUMECA international, Brussels, Belgium, User manual, version 8.7 (2009).

    Google Scholar 

  18. M. L. Mansour, Validation and calibration of modern CFD RANS codes for the prediction of transonic axial centrifugal compressors, ASME Turbo Expo, No. 6, GT2008-76691 (2008).

  19. T. Hagan, Neural network design [M]. Boston, PWS Publishing, Edition 2 (2006).

    Google Scholar 

  20. L. N. Long and A. Gupta, Scalable massively parallel artificial neural networks, Journal of Aerospace Computing, Information and Communication, 5(1) (2008) 3–15.

    Article  Google Scholar 

  21. J. Hu, D. Erik and K. Seo et al., Adaptive hierarchical fair competition (AHFC) model for parallel evolutionary algorithms, Proceedings of the Genetic and Evolutionary Computation Conference, New York: Morgan Kaufmann Publishers (2002) 772–779.

    Google Scholar 

  22. D. X. Chang, A robust dynamic niching genetic algorithm with niche migration for automatic clustering problem, Pattern recognition, 43(4) (2010) 1346–1360.

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Key Lab. for Power Machinery and Engineering (Ministry of Education), Shanghai Jiao Tong University, Shanghai, 200240, China

    Bin Zhang, Tong Wang, Chuan-gang Gu & Xin-Wei Shu

  2. Blower Research Center, Shanghai Electric Group, Shanghai, 200001, China

    Xin-Wei Shu

Authors
  1. Bin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tong Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chuan-gang Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xin-Wei Shu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bin Zhang.

Additional information

This paper was recommended for publication in revised form by Associate Editor Byeong Rog Shin

Bin Zhang is currently a Ph. D. candidate in Shanghai Jiao Tong University (SJTU). He has received his B.Sc. from Central South University in 2005. Afterwards, he has been recommended to further study for Ph. D. degree in SJTU. His research interest: Numerical and Experimental Investigation in Fluid Engineering.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhang, B., Wang, T., Gu, Cg. et al. An integrated blade optimization approach based on parallel ANN and GA with hierarchical fair competition dynamic-niche. J Mech Sci Technol 25, 1457–1463 (2011). https://doi.org/10.1007/s12206-011-0413-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12206-011-0413-0

Keywords

Search

Navigation