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Article citations


Bonaiuti, D. and Zangeneh, M. (2009) On the Coupling of Inverse Design and Optimization Techniques for the Multiobjective, Multipoint Design of Turbomachinery Blades. Journal of Turbomachinery, 131, 1-16.

has been cited by the following article:

  • TITLE: Optimization of a Centrifugal Impeller with the Constraint on Efficiency at the Stall Point

    AUTHORS: Kaibin Wang, Xin Ai, Ruizi Zhang, Jingyin Li

    KEYWORDS: Optimization, Impeller, Inverse Design, Angular Momentum, Aerodynamic Constraint

    JOURNAL NAME: Open Journal of Fluid Dynamics, Vol.8 No.1, March 9, 2018

    ABSTRACT: An optimization strategy is presented concerning the aerodynamic performance of an impeller at the design point with a constraint of efficiency at the stall point, on the basis of the combination of three-dimensional inverse design method and the response surface methodology (RSM). A specific inlet angular momentum is given in the prescribed blade loading to facilitate the change of the blade inlet angle at either the hub or shroud of the impeller. Three variables, the inlet angular momentums at both the hub and shroud as well as a coefficient relation with blade loading, were chosen as the optimization variables after a sensitivity analysis, which is conducted by means of the orthogonal design experiment. The candidate impellers were generated by different angular momentum distributions determined by the Box-Behnken design, and the performances of corresponding compressors were simulated. The response surface models of the performances of the compressors were obtained at the design and stall points. Thus the optimal impeller was obtained and the compressor’s performance at the design flow rate could be predicted under the constraint of a specified efficiency at the stall flow rate. A comparison between the computational results of the original and optimized impeller indicates that a considerable improvement of the efficiency of the compressor over the whole working range is obtained, which confirms the validity of the optimization strategy.